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1
Scannapieco, A. F., A. Renga, G. Fasano, and A. Moccia. "ULTRALIGHT RADAR FOR SMALL AND MICRO-UAV NAVIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 24, 2017): 333–38. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-333-2017.
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This paper presents a radar approach to navigation of small and micro Unmanned Aerial Vehicles (UAV) in environments challenging for common sensors. A technique based on radar odometry is briefly explained and schemes for complete integration with other sensors are proposed. The focus of the paper is set on ultralight radars and interpretation of outputs of such sensor when dealing with autonomous navigation in complex scenario. The experimental setup used to analyse the proposed approach comprises one multi-rotor UAV and one ultralight commercial radar. Results from flight tests in which both forward-only motion and mixed motion are presented and analysed, providing a reference for understanding outputs of radar in complex scenarios. The radar odometry solution is compared with ground truth provided by GPS sensor.
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Weidinger, C., T. Kadiofsky, P. Glira, C. Zinner, and W. Kubinger. "3D ONLINE TERRAIN MAPPING WITH SCANNING RADAR SENSORS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 125–32. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-125-2020.
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Abstract. Environmental perception is one of the core requirements in autonomous vehicle navigation. If exposed to harsh conditions, commonly deployed sensors like cameras or lidars deliver poor sensing performance. Millimeter wave radars enable robust sensing of the environment, but suffer from specular reflections and large beamwidths. To incorporate the sensor noise and lateral uncertainty, a new probabilistic, voxel-based recursive mapping method is presented to enable online terrain mapping using scanning radar sensors. For map accuracy evaluation, test measurements are performed with a scanning radar sensor in an off-road area. The voxel map is used to derive a digital terrain model, which can be compared with ground-truth data from an image-based photogrammetric reconstruction of the terrain. The method evaluation shows promising results for terrain mapping solely performed with radar scanners. However, small terrain structures still pose a problem due to larger beamwidths in comparison to lidar sensors.
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Skaria, Sruthy, Akram Al-Hourani, Robin J. Evans, Kandeepan Sithamparanathan, and Udaya Parampalli. "Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences." Sensors 19, no. 20 (2019): 4459. http://dx.doi.org/10.3390/s19204459.
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The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.
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Lee, JeeEun, and Sun K. Yoo. "Radar-Based Detection of Respiration Rate with Adaptive Harmonic Quefrency Selection." Sensors 20, no. 6 (2020): 1607. http://dx.doi.org/10.3390/s20061607.
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Continuous respiration monitoring is important for predicting a potential disease. Due to respiration measurements using contact sensors, it is difficult to achieve continuous measurement because the sensors are inconvenient to attach. In this study, a radar sensor was used for non-contact respiration measurements. The radar sensor had a high precision and could even be used in the dark. It could also be used continuously regardless of time and place. The radar sensor relied on the periodicity of respiration to detect the respiration rate. A respiration adaptive interval was set and the respiration rate was detected through harmonic quefrency selection. As a result, it was confirmed that there was no difference between the respiratory rate measured using a respiration belt and the respiratory rate detected using a radar sensor. Furthermore, case studies on changes in the radar position and about measurement for long periods confirmed that the radar sensor could detect respiration rate continuously regardless of the position and measurement duration.
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Et. al., M. Hyndhavi,. "DEVELOPMENT OF VEHICLE TRACKING USING SENSOR FUSION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (2021): 731–39. http://dx.doi.org/10.17762/itii.v9i2.406.
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The development of vehicle tracking using sensor fusion is presented in this paper. Advanced driver assistance systems (ADAS) are becoming more popular in recent years. These systems use sensor information for real-time control. To improve the standard and robustness, especially in the presence of environmental noises like varying lighting, weather conditions, and fusion of sensors has been the center of attention in recent studies. Faced with complex traffic conditions, the single sensor has been unable to meet the security requirements of ADAS and autonomous driving. The common environment perception sensors consist of radar, camera, and lidar which have both pros and cons. The sensor fusion is a necessary technology for autonomous driving which provides a better vision and understanding of vehicles surrounding. We mainly focus on highway scenarios that enable an autonomous car to comfortably follow other cars at various speeds while keeping a secure distance and mix the advantages of both sensors with a sensor fusion approach. The radar and vision sensor information are fused to produce robust and accurate measurements. And the experimental results indicate that the comparison of using only radar sensors and sensor fusion of both camera and radar sensors is presented in this paper. The algorithm is described along with simulation results by using MATLAB.
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Fritsche, Paul, and Bernardo Wagner. "Evaluation of a Novel Radar Based Scanning Method." Journal of Sensors 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6952075.
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The following paper introduces a novel scanning method for mapping and localization purposes in mobile robotics. Our method is based on a rotating monostatic radar network, which determines the positions of objects around the scanner via a continuously running lateration algorithm. The estimation of surfaces with ultrawideband radar networks has been studied experimentally in lab environments, especially with lateration, envelopes of spheres, and SEABED algorithms. But we do not see a link to the field of mapping and localization of mobile robots, where laser scanners are dominating. Indeed, only few research groups use radars for mapping and localization, but their applied sensor principle is based on a rotating focused radar beam. Consequently, only 2D radar scanners are known inside the robotic world and methods for 3D scanning with radars need to be investigated. This paper will derive the theoretical background of the sensor principle, which is based on a radar network on a rotating joint, and discuss its erroneous influences. We were performing first scans of standard geometries and deriving a model in order to compare theoretical and experimental measurement results. Furthermore, we present first mapping approaches and a simulation of a scanner with multiple sensors.
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Saveliev, A. N., A. N. Semenov, and M. D. Kalnoy. "Analysis of the Potential Space Resolution in Multi-position Surface Movement Radar System." Mechanical Engineering and Computer Science, no. 12 (January 4, 2018): 32–44. http://dx.doi.org/10.24108/1217.0001357.
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Specialized surface movement radar (SMR) systems for visual observations of the airfield are one of the mandatory systems ensuring the safety of flights and control service of aerodromes. Design of multi-position SMR systems comprising a set of simple and low-cost radar sensors (RS) is a promising trend. A problem to estimate a potential resolution in a multi-position SMR system is relevant.The paper describes two approaches to estimate the potential resolution using the "joint" ambiguity function, namely additive and multiplicative. Both approaches allow taking into account a type of the radar signal used, an antenna radiation pattern (ARP), and the location of radar sensors on the airfield.To implement the considered approaches to the resolution estimation, was used a software package to analyse the multi-position SMR system characteristics. For a particular example to locate radar sensors, the calculation results of the ambiguity function are given.The paper presents an estimated space resolution in the multi-position SMR system in Cartesian coordinate system. Draws conclusions about the possibility for obtaining the multi-position SMR system resolution that exceeds the resolution of a single radar sensor with the exception of the isotropic radiation pattern of radar sensor and the additive estimation method.The developed software package can be used to analyse and justify the following:- space resolution requirements to the radar sensor;- recommendations on the location of the radar sensors;- resolution of the multi-position SMR system space including a radar sensor with known characteristics.
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Galajda, Pavol, Alena Galajdova, Stanislav Slovak, et al. "Robot vision ultra-wideband wireless sensor in non-cooperative industrial environments." International Journal of Advanced Robotic Systems 15, no. 4 (2018): 172988141879576. http://dx.doi.org/10.1177/1729881418795767.
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In this article, the ultra-wideband technology for localization and tracking of the robot gripper (behind the obstacles) in industrial environments is presented. We explore the possibilities of ultra-wideband radar sensor network employing the centralized data fusion method that can significantly improve tracking capabilities in a complex environment. In this article, we present ultra-wideband radar sensor network hardware demonstrator that uses a new wireless ultra-wideband sensor with an embedded controller to detect and track online or off-line movement of the robot gripper. This sensor uses M-sequence ultra-wideband radars front-end and low-cost powerful processors on a system on chip with the advanced RISC machines (ARM) architecture as a main signal processing block. The ARM-based single board computer ODROID-XU4 platform used in our ultra-wideband sensor can provide processing power for the preprocessing of received raw radar signals, algorithms for detection and estimation of target’s coordinates, and finally, compression of data sent to the data fusion center. Data streams of compressed target coordinates are sent from each sensor node to the data fusion center in the central node using standard the wireless local area network (WLAN) interface that is the feature of the ODROID-XU4 platform. The article contains experimental results from measurements where sensors and antennas are located behind the wall or opaque material. Experimental testing confirmed capability of real-time performance of developed ultra-wideband radar sensor network hardware and acceptable precision of software. The introduced modular architecture of ultra-wideband radar sensor network can be used for fast development and testing of new real-time localization and tracking applications in industrial environments.
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Brüggenwirth, Stefan, and Fernando Rial. "Robotic control for cognitive UWB radar." Encyclopedia with Semantic Computing and Robotic Intelligence 02, no. 01 (2018): 1850009. http://dx.doi.org/10.1142/s2529737618500090.
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In the paper, we describe a trajectory planning problem for a six-DoF robotic manipulator arm that carries an ultra-wideband (UWB) radar sensor with synthetic aperture (SAR). The resolution depends on the trajectory and velocity profile of the sensor head. The constraints can be modeled as an optimization problem to obtain a feasible, collision-free target trajectory of the end-effector of the manipulator arm in Cartesian coordinates that minimizes observation time. For 3D reconstruction, the target is observed in multiple height slices. For through-the-wall radar the sensor can be operated in sliding mode for scanning larger areas. For IED inspection the spotlight mode is preferred, constantly pointing the antennas towards the target to obtain maximum azimuth resolution. UWB sensors typically use a wide spectrum shared by other RF communication systems. This may become a limiting factor on system sensitivity and severely degrade the image quality. Cognitive radars can adapt dynamically their bandwidth, frequency and other transmit parameters to the radio frequency environment to avoid interference with primary users.
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Nobis, Felix, Ehsan Shafiei, Phillip Karle, Johannes Betz, and Markus Lienkamp. "Radar Voxel Fusion for 3D Object Detection." Applied Sciences 11, no. 12 (2021): 5598. http://dx.doi.org/10.3390/app11125598.
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Automotive traffic scenes are complex due to the variety of possible scenarios, objects, and weather conditions that need to be handled. In contrast to more constrained environments, such as automated underground trains, automotive perception systems cannot be tailored to a narrow field of specific tasks but must handle an ever-changing environment with unforeseen events. As currently no single sensor is able to reliably perceive all relevant activity in the surroundings, sensor data fusion is applied to perceive as much information as possible. Data fusion of different sensors and sensor modalities on a low abstraction level enables the compensation of sensor weaknesses and misdetections among the sensors before the information-rich sensor data are compressed and thereby information is lost after a sensor-individual object detection. This paper develops a low-level sensor fusion network for 3D object detection, which fuses lidar, camera, and radar data. The fusion network is trained and evaluated on the nuScenes data set. On the test set, fusion of radar data increases the resulting AP (Average Precision) detection score by about 5.1% in comparison to the baseline lidar network. The radar sensor fusion proves especially beneficial in inclement conditions such as rain and night scenes. Fusing additional camera data contributes positively only in conjunction with the radar fusion, which shows that interdependencies of the sensors are important for the detection result. Additionally, the paper proposes a novel loss to handle the discontinuity of a simple yaw representation for object detection. Our updated loss increases the detection and orientation estimation performance for all sensor input configurations. The code for this research has been made available on GitHub.
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Korotun, M., L. Weizman, A. Drori, et al. "0584 Detecting Sleep Disordered Breathing Using Sub-Terahertz Radio-Frequency Micro-Radar." Sleep 43, Supplement_1 (2020): A224. http://dx.doi.org/10.1093/sleep/zsaa056.581.
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Abstract Introduction New sensor technologies are entering sleep testing at a rapid pace; Neteera™ developed a novel sensor and algorithm for sleep apnea detection utilizing a contact-free, radar-based sensor system. The system utilizes a high-frequency, low-power, directional micro-radar which operates at ~120GHz and a sampling rate of 2500Hz as well as algorithms which are able to detect both pulse and respiratory activity of subjects during sleep. Methods Adult subjects undergoing diagnostic PSG for clinical purposes were simultaneously assessed with the novel micro-radar system with sensors under the mattress. Disordered breathing events (DBEs) were scored from the PSG using AASM scoring guidelines and were compared with those detected by the micro-radar sensor. Test data were grouped into three sets: 1. Single under mattress sensor; 2. Two under mattress sensors on each side of the bed (to improve signal capture); 3. After software optimization. The micro-radar sensor detected DBEs but software to describe the type of DBEs (obstructive apnea/central apnea/hypopnea) is still under development. Detection rate of DBEs was compared between the two methodologies and the development sets. Results n=22 (12 F, 10 M), Age=50.8±12.4 years, BMI=35.32±7.37 kg/m2. Diagnostic PSG AHI: 19.7±29.4/hr, T90=15.8±25.7%. Percent DBEs missed by the micro-radar sensor: 1st set=14.6±10.6%; 2nd set=9.4±8.3%; 3rd set=1.2±2.6%. Number of DBEs assessed for each set was 646, 1144, 125 events, respectively. With each successive set, the detection rate improved. Conclusion A novel micro-radar, non-contact sensor technology can be used to detect DBEs during sleep. Detection rate improved with utilization of two sensors per bed and software optimization. Future software development is expected to improve detection rate and facilitate breathing event classification into obstructive apneas/central apneas/hypopneas. Support None.
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Moses, Allistair, Matthew J. Rutherford, Michail Kontitsis, and Kimon P. Valavanis. "UAV-borne X-band radar for collision avoidance." Robotica 32, no. 1 (2013): 97–114. http://dx.doi.org/10.1017/s0263574713000659.
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SUMMARYThe increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.
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Hargrave, Chad, Lance Munday, Gareth Kennedy, and André de Kock. "Mine Machine Radar Sensor for Emergency Escape." Resources 9, no. 2 (2020): 16. http://dx.doi.org/10.3390/resources9020016.
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This paper presents the results of recent work to develop and trial a mine machine radar sensor for underground coal mine vehicles. There is an urgent industry need for an integrated solution to the problem of operating an underground vehicle in conditions of dense ambient dust and/or smoke, such as may occur in underground coal mines after a fire or explosion. Under these conditions, sensors such as cameras and lidar offer limited assistance due to their inability to penetrate thick dust. Thermal infrared can penetrate dust but still results in poor vision, as there is insufficient temperature contrast between the tunnel walls and the ambient air. Microwave radar sensors are able to penetrate the dust, and suitable radar sensors have been developed for use in the automation industry. Adapting such sensors for use in an underground coal mining environment was the focus of this research effort, and involved trialing a suitable sensor in dust and smoke chambers as well as trials in an underground coal mine with introduced dust. Data processing and the development of a suitable user interface were key aspects of the research. Since any sensor would have to operate in an explosive atmosphere, a related research work developed a flameproof dielectric enclosure to allow the use of the radar in the mine environment.
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Bhutani, Akanksha, Sören Marahrens, Michael Gehringer, Benjamin Göttel, Mario Pauli, and Thomas Zwick. "The Role of Millimeter-Waves in the Distance Measurement Accuracy of an FMCW Radar Sensor." Sensors 19, no. 18 (2019): 3938. http://dx.doi.org/10.3390/s19183938.
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High-accuracy, short-range distance measurement is required in a variety of industrial applications e.g., positioning of robots in a fully automated production process, level measurement of liquids in small containers. An FMCW radar sensor is suitable for this purpose, since many of these applications involve harsh environments. Due to the progress in the field of semiconductor technology, FMCW radar sensors operating in different millimeter-wave frequency bands are available today. An important question in this context, which has not been investigated so far is how does a millimeter-wave frequency band influence the sensor accuracy, when thousands of distance measurements are performed with a sensor. This topic has been dealt with for the first time in this paper. The method used for analyzing the FMCW radar signal combines a frequency- and phase-estimation algorithm. The frequency-estimation algorithm based on the fast Fourier transform and the chirp-z transform provides a coarse estimate of the target distance. Subsequently, the phase-estimation algorithm based on a cross-correlation function provides a fine estimate of the target distance. The novel aspects of this paper are as follows. First, the estimation theory concept of Cramér-Rao lower bound (CRLB) has been used to compare the accuracy of two millimeter-wave FMCW radars operating at 60 GHz and 122 GHz. In this comparison, the measurement parameters (e.g., bandwidth, signal-to-noise ratio) as well as the signal-processing algorithm used for both the radars are the same, thus ensuring an unbiased comparison of the FMCW radars, solely based on the choice of millimeter-wave frequency band. Second, the improvement in distance measurement accuracy obtained after each step of the combined frequency- and phase-estimation algorithm has been experimentally demonstrated for both the radars. A total of 5100 short-range distance measurements are made using the 60 GHz and 122 GHz FMCW radar. The measurement results are analyzed at various stages of the frequency- and phase-estimation algorithm and the measurement error is calculated using a nanometer-precision linear motor. At every stage, the mean error values measured with the 60 GHz and 122 GHz FMCW radars are compared. The final accuracy achieved using both radars is of the order of a few micrometers. The measured standard deviation values of the 60 GHz and 122 GHz FMCW radar have been compared against the CRLB. As predicted by the CRLB, this paper experimentally validates for the first time that the 122 GHz FMCW radar provides a higher repeatability of micrometer-accuracy distance measurements than the 60 GHz FMCW radar.
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Rodrigues, Davi V. Q., and Changzhi Li. "A Review on Low-Cost Microwave Doppler Radar Systems for Structural Health Monitoring." Sensors 21, no. 8 (2021): 2612. http://dx.doi.org/10.3390/s21082612.
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Portable, low-cost, microwave radars have attracted researchers’ attention for being an alternative noncontact solution for structural condition monitoring. In addition, by leveraging their capability of providing the target velocity information, the radar-based remote monitoring of complex rotating structures can also be accomplished. Modern radar systems are compact, able to be easily integrated in sensor networks, and can deliver high accuracy measurements. This paper reviews the recent technical advances in low-cost Doppler radar systems for phase-demodulated displacement measurements and time-Doppler analysis for structural health information, including digital signal processing and emerging applications related to radar sensor networks.
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Wang, Wen-Qin, and Huaizong Shao. "Radar-to-Radar Interference Suppression for Distributed Radar Sensor Networks." Remote Sensing 6, no. 1 (2014): 740–55. http://dx.doi.org/10.3390/rs6010740.
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Czyżewski, Andrzej, Józef Kotus, and Grzegorz Szwoch. "Estimating Traffic Intensity Employing Passive Acoustic Radar and Enhanced Microwave Doppler Radar Sensor." Remote Sensing 12, no. 1 (2019): 110. http://dx.doi.org/10.3390/rs12010110.
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Innovative road signs that can autonomously display the speed limit in cases where the traffic situation requires it are under development. The autonomous road sign contains many types of sensors, of which the subject of interest in this article is the Doppler sensor that we have improved and the constructed and calibrated acoustic probe. An algorithm for performing vehicle detection and tracking, as well as vehicle speed measurement, in a signal acquired with a continuous wave Doppler sensor, is discussed. A method is also experimentally presented and studied for counting vehicles and for determining their movement direction by means of acoustic vector sensor application. The assumptions of the method employing spatial distribution of sound intensity determined with the help of an integrated three-dimensional (3D) sound intensity probe are discussed. The enhanced Doppler radar and the developed sound intensity probe were used for the experiments that are described and analyzed in the paper.
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Liu, Yan Ju, Chun Xiang Xie, and Jian Hui Song. "Research on Fusion Tracking Technology in Heterogeneous Multi-Sensor." Advanced Materials Research 1056 (October 2014): 158–61. http://dx.doi.org/10.4028/www.scientific.net/amr.1056.158.
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Heterogeneous multi-sensor’s fusion tracking can detect precise distance and angle to the target. For heterogeneous multi-sensor issues, radar, infrared sensor and laser sensor’s data fusion, and target tracking are studied, weighted fusion algorithm based on Lagrange and unscented kalman filter are adopted, which make date fusion and tracking filtering for target. Simulation results show that the radar / infrared / laser sensors can realize data fusion and tracking to the target, and the accuracy is significantly higher than radar and infrared/laser, and then tracking effect is better.
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Tarchi, Dario, Michele Vespe, Ciro Gioia, Francesco Sermi, Vladimir Kyovtorov, and Giorgio Guglieri. "Low-Cost Mini Radar: Design Prototyping and Tests." Journal of Sensors 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/8029364.
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Radar systems are largely employed for surveillance of wide and remote areas; the recent advent of drones gives the opportunity to exploit radar sensors on board of unmanned aerial platforms. Nevertheless, whereas drone radars are currently available for military applications, their employment in the civilian domain is still limited. The present research focuses on design, prototyping, and testing of an agile, low-cost, mini radar system, to be carried on board of Remotely Piloted Aircraft (RPAs) or tethered aerostats. In particular, the paper faces the challenge to integrate the in-house developed radar sensor with a low-cost navigation board, which is used to estimate attitude and positioning data. In fact, a suitable synchronization between radar and navigation data is essential to properly reconstruct the radar picture whenever the platform is moving or the radar is scanning different azimuthal sectors. Preliminary results, relative to tests conducted in preoperational conditions, are provided and exploited to assert the suitable consistency of the obtained radar pictures. From the results, there is a high consistency between the radar images and the picture of the current environment emerges; finally, the comparison of radar images obtained in different scans shows the stability of the platform.
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RENALDI, LUKY, SUGONDO HADIYOSO, and DADAN NUR RAMADAN. "Purwarupa Radar sebagai Pendeteksi Benda Diam menggunakan Ultrasonik." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 6, no. 3 (2018): 317. http://dx.doi.org/10.26760/elkomika.v6i3.317.
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ABSTRAKDeteksi keberadaan objek secara otomatis pada ruangan diperlukan ketika terdapat keterbatasan dalam melakukan penginderaan. Pemanfaatan sistem radar menjadi saah satu solusi untuk penginderaan objek. Pada paper ini, diimplementasikan prototipe radar menggunakan sensor ultrasonik, mikrokontroller Arduino UNO R3 dan motor servo. Sistem ini dirancang dengan tiga buah sensor ultrasonik dengan motor sebagai penggerak horizontal dan vertikal dalam sistem pemindainya. Sensor yang berjumlah tiga buah, diletakkan pada titik yang berbeda sehingga dapat membaca jarak, sudut dan ketinggian objek dari arah titik tersebut, hasil dari pengukuran objek ditampilkan pada PC melalui aplikasi pemograman GUI. Dari hasil pengujian, radar mampu mendeteksi objek antara 5 cm dari depan radar dengan jarak maksimum 30 cm dan diperoleh tingkat kesalahan pengukuran jarak dan ketinggian sebesar 1 - 2 cm sedangkan untuk sudut 1˚- 3˚.Kata kunci: Deteksi, Radar, Ultrasonik, Jarak, SudutABSTRACTAutomatic detection of objects in the room is required when there are limitations in the sensing. Utilization of radar system becomes one solution for sensing object. In this paper, we implemented a prototype radar using ultrasonic sensor, Arduino UNO R3 microcontroller and servo motor. The system is designed with three ultrasonic sensors with motors as horizontal and vertical drive in the scanning system. Three sensors are placed at different points so that they can read the distance, angle and height of the object from that point, the result of measuring the object displayed on the PC through the GUI programming application. From the test results, the radar is able to detect objects between 5 cm from the front of the radar with a maximum distance of 30 cm and obtained the error rate measurement of distance and altitude of 1 - 2 cm while for the angle of 1˚ - 3˚.Keywords: Detection, Radar, Ultrasonic, Distance, Angle
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Toker, Onur, and Suleiman Alsweiss. "Design of a Cyberattack Resilient 77 GHz Automotive Radar Sensor." Electronics 9, no. 4 (2020): 573. http://dx.doi.org/10.3390/electronics9040573.
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In this paper, we propose a novel 77 GHz automotive radar sensor, and demonstrate its cyberattack resilience using real measurements. The proposed system is built upon a standard Frequency Modulated Continuous Wave (FMCW) radar RF-front end, and the novelty is in the DSP algorithm used at the firmware level. All attack scenarios are based on real radar signals generated by Texas Instruments AWR series 77 GHz radars, and all measurements are done using the same radar family. For sensor networks, including interconnected autonomous vehicles sharing radar measurements, cyberattacks at the network/communication layer is a known critical problem, and has been addressed by several different researchers. What is addressed in this paper is cyberattacks at the physical layer, that is, adversarial agents generating 77 GHz electromagnetic waves which may cause a false target detection, false distance/velocity estimation, or not detecting an existing target. The main algorithm proposed in this paper is not a predictive filtering based cyberattack detection scheme where an “unusual” difference between measured and predicted values triggers an alarm. The core idea is based on a kind of physical challenge-response authentication, and its integration into the radar DSP firmware.
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Murthy, SGK, and M. V. R. Murthy. "Air Object Height Estimation with 2-D Radars using Fuzzy Logic." Defence Science Journal 61, no. 5 (2011): 485. http://dx.doi.org/10.14429/dsj.61.403.
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<p>Multi sensor tracking is a widely used technique in aerospace applications to estimate the target kinematics precisely. Particularly naval-based tracking systems utilize, different types of Radars (2-D, 3-D) in multi sensor tracking scenario for robust estimation. As the supplied information from 2-D Radar contains only range and azimuth values, it is difficult to estimate the height of an air object using 2-D Radar. In order to over come the limitation, a geometric method is considered to combine the information obtained from two 2-D Radars located in two different locations. As the solution of the geometric method depends upon certain geometric features, it is not possible to get good results with one pair of sensors. However to obtain better results, it is proposed and experimented more than two 2-D Radars that combined with a fuzzy logic based validation. This paper discusses the issues related to 2-D Radar tracking and the method comprising Triangulation geometry and fuzzy logic based validation method to improve the height estimation accuracy in real time.</p><p><strong>Defence Science Journal, 2011, 61(5), pp.485-490</strong><strong><strong>, DOI:http://dx.doi.org/10.14429/dsj.61.403</strong></strong></p>
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Kim, Taeklim, and Tae-Hyoung Park. "Extended Kalman Filter (EKF) Design for Vehicle Position Tracking Using Reliability Function of Radar and Lidar." Sensors 20, no. 15 (2020): 4126. http://dx.doi.org/10.3390/s20154126.
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Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations.
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Rasshofer, R. H., and K. Gresser. "Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions." Advances in Radio Science 3 (May 12, 2005): 205–9. http://dx.doi.org/10.5194/ars-3-205-2005.
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Abstract. Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.
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Essen, Helmut, Wolfgang Koch, Sebastian Hantscher, et al. "A multimodal sensor system for runway debris detection." International Journal of Microwave and Wireless Technologies 4, no. 2 (2012): 155–62. http://dx.doi.org/10.1017/s1759078712000116.
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For foreign object detection on runways, highly sensitive radar sensors give the opportunity to detect even very small objects, metallic and non-metallic, also under adverse weather conditions. As it is desirable for airport applications to install only small but robust installations along the traffic areas, millimeter-wave radars offer the advantage of small antenna apertures and miniaturized system hardware. A 220-GHz radar was developed, which is capable to serve this application, if several of these are netted to cover the whole traffic area. Although under fortunate conditions the radar allows a classification or even an identification of the debris, the complete system design incorporates 3-D time-of-flight cameras for assistance in the identification process, which are also distributed along the traffic areas. The system approach further relies upon a change detection algorithm on the netted information to discriminate non-stationary alarms and reduce the false alarm ratio.
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Yuan, Yichao, and Chung-Tse Michael Wu. "Recent Development of Non-Contact Multi-Target Vital Sign Detection and Location Tracking Based on Metamaterial Leaky Wave Antennas." Sensors 21, no. 11 (2021): 3619. http://dx.doi.org/10.3390/s21113619.
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Microwave radar sensors have been developed for non-contact monitoring of the health condition and location of targets, which will cause minimal discomfort and eliminate sanitation issues, especially in a pandemic situation. To this end, several radar sensor architectures and algorithms have been proposed to detect multiple targets at different locations. Traditionally, beamforming techniques incorporating phase shifters or mechanical rotors are utilized, which is relatively complex and costly. On the other hand, metamaterial (MTM) leaky wave antennas (LWAs) have a unique property of launching waves of different spectral components in different directions. This feature can be utilized to detect multiple targets at different locations to obtain their healthcare and location information accurately, without complex structure and high cost. To this end, this paper reviews the recent development of MTM LWA-based radar sensor architectures for vital sign detection and location tracking. The experimental results demonstrate the effectiveness of MTM vital sign radar compared with different radar sensor architectures.
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Bo, Yuming, Zhimin Chen, Mingfeng Yin, and Tianxiong Wang. "Improved Different Dimensional Sensors Combined Space Registration Algorithm." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/289825.
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To address the problem of deviation and registration of 3D radar and infrared sensor, this paper presents and improves a method based on the state value and space deviation of federated filtering of unscented Kalman filter and standard Kalman filter, which conduces to real time registering of system deviation of radar and IF sensors. In the method presented here, a covariance matching criteria-based approach was employed for judgment of filtering divergent trend, while self-adaptive attenuation factor was introduced for correction of the predicted error covariance so as to inhibit the divergent phenomenon. The experiment results indicated that the method presented here conduces to improvement of the precision and speed of space registration, showing practical value in deviation registration of 3D radars and infrared sensors.
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Gaitanakis, George-Konstantinos, George Limnaios, and Konstantinos C. Zikidis. "On the use of AESA (Active Electronically Scanned Array) Radar and IRST (InfraRed Search&Track) System to Detect and Track Low Observable Threats." MATEC Web of Conferences 304 (2019): 04001. http://dx.doi.org/10.1051/matecconf/201930404001.
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The radar has been indisputably the most important sensor in the battlefield, allowing early warning and tracking of air vehicles. Modern fighter ircraft employing AESA fire control radars are able to acquire and track targets at long ranges, in the order of 50 nautical miles or more. However, the proliferation of low observable or stealth technology has contested radar capabilities, reducing their detection / tracking ranges roughly to one third. This degradation is more severe concerning fighter aircraft radars, since most stealth threats are optimised for higher frequency bands, as in the case of fire control radars. Hence, other parts of the electromagnetic spectrum have been reconsidered, such as infrared radiation (IR). Every aircraft is a source of IR, due to fuel combustion, aerodynamic friction and IR reflection. In this way, a jet fighter can be detected by an IR sensor against the cold background of the sky. Therefore, IRST systems have re-emerged, offering an alternative to the radar. Apart from their capabilities concerning target detection (whether stealth or not), IRST systems also exhibit passive operation, resilience to jamming and better angular accuracy. On the other hand, they are prone to weather conditions, especially moisture, while they cannot measure distance directly, as in the case of the radar. This work explores and compares the capabilities and limitations of the two approaches, AESA radars and IRST systems, offering also some insight to the benefits of sensor fusion.
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Mohd Basir, Shafinaz, Idnin Pasya, Tajmalludin Yaakob, Nur Emileen Abd Rashid, and Takehiko Kobayashi. "Improvement of Doppler measurement using multiple-input multiple-output (MIMO) concept in radar-based automotive sensor detecting pedestrians." Sensor Review 38, no. 2 (2018): 239–47. http://dx.doi.org/10.1108/sr-04-2017-0060.
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Purpose This paper aims to present an approach of utilizing multiple-input multiple-output (MIMO) radar concept to enhance pedestrian classification in automotive sensors. In a practical environment, radar signals reflected from pedestrians and slow-moving vehicles are similar in terms of reflecting angle and Doppler returns, inducing difficulty for target discrimination. An efficient discrimination between the two targets depends on the ability of the sensor to extract unique characteristics from each target, for example, by exploiting Doppler signatures. This study describes the utilization of MIMO radar for Doppler measurement and demonstrates its application to improve pedestrian classification through actual laboratory measurements. Design/methodology/approach Multiple non-modulated sinusoidal signals are transmitted orthogonally over a MIMO array using time division scheme, illuminating human and non-human targets. The reflected signal entering each of the receiving antenna are combined at the radar receiver prior to Doppler processing. Doppler histogram was formulated based on a series of measurements, and the Doppler spread of the targets was determined from the histograms. Results were compared between MIMO and conventional single antenna systems. Findings Measurement results indicated that the MIMO configuration provides able to capture more Doppler information compared to conventional single antenna systems, enabling a more precise discrimination between pedestrian and other slow-moving objects on the road. Originality/value The study demonstrated the effectiveness of using MIMO configuration in radar-based automotive sensor to enhance the accuracy of Doppler estimation, which is seldom highlighted in literature of MIMO radars. The result also indicated its usefulness in improving target discrimination capability of the radar, through actual measurement.
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Dankert, Heiko, and Jochen Horstmann. "A Marine Radar Wind Sensor." Journal of Atmospheric and Oceanic Technology 24, no. 9 (2007): 1629–42. http://dx.doi.org/10.1175/jtech2083.1.
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Abstract A new method for retrieving the wind vector from radar-image sequences is presented. This method, called WiRAR, uses a marine X-band radar to analyze the backscatter of the ocean surface in space and time with respect to surface winds. Wind direction is found using wind-induced streaks, which are very well aligned with the mean surface wind direction and have a typical spacing above 50 m. Wind speeds are derived using a neural network by parameterizing the relationship between the wind vector and the normalized radar cross section (NRCS). To improve performance, it is also considered how the NRCS depends on sea state and atmospheric parameters such as air–sea temperature and humidity. Since the signal-to-noise ratio in the radar sequences is directly related to the significant wave height, this ratio is used to obtain sea state parameters. All radar datasets were acquired in the German Bight of the North Sea from the research platform FINO-I, which provides environmental data such as wind measurements at different heights, sea state, air–sea temperatures, humidity, and other meteorological and oceanographic parameters. The radar-image sequences were recorded by a marine X-band radar installed aboard FINO-I, which operates at grazing incidence and horizontal polarization in transmit and receive. For validation WiRAR is applied to the radar data and compared to the in situ wind measurements from FINO-I. The comparison of wind directions resulted in a correlation coefficient of 0.99 with a standard deviation of 12.8°, and that of wind speeds resulted in a correlation coefficient of 0.99 with a standard deviation of 0.41 m s−1. In contrast to traditional offshore wind sensors, the retrieval of the wind vector from the NRCS of the ocean surface makes the system independent of the sensors’ motion and installation height as well as the effects due to platform-induced turbulence.
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Mahmudin, Dadin, Andri Setya Dharma, Erwin Susanto, and Yuyu Wahyu. "Perancangan dan Implementasi Pengontrol Arah Pancaran Radar Pengawas Pantai Terhadap Sudut Tertentu." Jurnal Elektronika dan Telekomunikasi 14, no. 1 (2016): 29. http://dx.doi.org/10.14203/jet.v14.29-35.
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Dewasa ini telah banyak dilakukan penelitian dan pengembangan radar . Salah satunya adalah radar yang ditempatkan di Kapal Laut. Penempatan radar di kapal laut mempunyai kendala pada tiang agung kapal. Tiang agung akan mengganggu fungsi radar karena adanya pantulan sinyal jarak dekat pada tiang agung. Hal ini dapat diantisipasi dengan mematikan pancaran radar saat arah pancaran radar menuju pada tiang agung kapal laut.Oleh sebab itu didalam penelitian ini dirancang prototype untuk mengatur otomatis aktif dan tidaknya pancaran radar berdasarkan arah pancaran radar. Kontrol aktif dan tidaknya pancaran radar ini dikontrol menggunakan perpaduan sensor ultrasonik dan sensor kompas dengan dilengkapi metode fuzzy sebagai logika jauh dekatnya tiang agung. Jika sensor ultrasonik membaca adanya halangan maka pancaran tidak aktif begitu sebaliknya. Penggabungan kedua sensor ini bertujuan jika sensor ultrasonik tidak dapat bekerja karena hujan maka kontrol sudut pada sensor kompas yang akan bekerjaSetelah dilakukan perancangan dan pengujian pada alat ini maka diperoleh sudut deviasi dengan range 14,30 – 29,30 dengan eror ± 30. Dengan acuan jangkauan titik tiang agung 60-120cm dari poros radar dengan lebar tiang 30cm. Kecepatan yang diperoleh saat fuzzy berlangsung sebesar 20 kali rpm dari kecepatan normal saat prototype mengenai halangan. Serta adanya sensor hujan berperan sebagai switch sensor ultrasonik ke mode off dan mode on untuk sensor kompas dengan menggunakan inisialisasi awal. Dari data yang dihasilkan prototype ini maka diperoleh keberhasilan sebesar 85% dilihat dari pengujian beberapa sensor dan peggabungannya. Oleh sebab itu apabila prototype ini direalisasikan akan membantu penelitian industri perkapalan dalam pembuatan radar sesungguhnya.
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Chiani, Marco, Andrea Giorgetti, and Enrico Paolini. "Sensor Radar for Object Tracking." Proceedings of the IEEE 106, no. 6 (2018): 1022–41. http://dx.doi.org/10.1109/jproc.2018.2819697.
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Cheng, G. F., T. H. Ho, W. T. Wang, C. Y. Chang, and S. J. Chung. "Highly integrated automotive radar sensor." Electronics Letters 43, no. 18 (2007): 994. http://dx.doi.org/10.1049/el:20071065.
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Chufo, R. L., and W. J. Johnson. "A radar coal thickness sensor." IEEE Transactions on Industry Applications 29, no. 5 (1993): 834–40. http://dx.doi.org/10.1109/28.245703.
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Tejero, S., U. Siart, and J. Detlefsen. "Coherent and non-coherent processing of multiband radar sensor data." Advances in Radio Science 4 (September 4, 2006): 73–78. http://dx.doi.org/10.5194/ars-4-73-2006.
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Abstract. Increasing resolution is an attractive goal for all types of radar sensor applications. Obtaining high radar resolution is strongly related to the signal bandwidth which can be used. The currently available frequency bands however, restrict the available bandwidth and consequently the achievable range resolution. As nowadays more sensors become available e.g. on automotive platforms, methods of combining sensor information stemming from sensors operating in different and not necessarily overlapping frequency bands are of concern. It will be shown that it is possible to derive benefit from perceiving the same radar scenery with two or more sensors in distinct frequency bands. Beyond ordinary sensor fusion methods, radar information can be combined more effectively if one compensates for the lack of mutual coherence, thus taking advantage of phase information. At high frequencies, complex scatterers can be approximately modeled as a group of single scattering centers with constant delay and slowly varying amplitude, i.e. a set of complex exponentials buried in noise. The eigenanalysis algorithms are well known for their capability to better resolve complex exponentials as compared to the classical spectral analysis methods. These methods exploit the statistical properties of those signals to estimate their frequencies. Here, two main approaches to extend the statistical analysis for the case of data collected at two different subbands are presented. One method relies on the use of the band gap information (and therefore, coherent data collection is needed) and achieves an increased resolution capability compared with the single-band case. On the other hand, the second approach does not use the band gap information and represents a robust way to process radar data collected with incoherent sensors. Combining the information obtained with these two approaches a robust estimator of the target locations with increased resolution can be built.
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Yoo, Kyung Ha, Jun Young Yoo, Myung Chul Park, and Yun Seong Eo. "Single Antenna Radar Sensor with FMCW Radar Transceiver IC." Journal of Korean Institute of Electromagnetic Engineering and Science 29, no. 8 (2018): 632–39. http://dx.doi.org/10.5515/kjkiees.2018.29.8.632.
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Abdu, Fahad Jibrin, Yixiong Zhang, Maozhong Fu, Yuhan Li, and Zhenmiao Deng. "Application of Deep Learning on Millimeter-Wave Radar Signals: A Review." Sensors 21, no. 6 (2021): 1951. http://dx.doi.org/10.3390/s21061951.
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The progress brought by the deep learning technology over the last decade has inspired many research domains, such as radar signal processing, speech and audio recognition, etc., to apply it to their respective problems. Most of the prominent deep learning models exploit data representations acquired with either Lidar or camera sensors, leaving automotive radars rarely used. This is despite the vital potential of radars in adverse weather conditions, as well as their ability to simultaneously measure an object’s range and radial velocity seamlessly. As radar signals have not been exploited very much so far, there is a lack of available benchmark data. However, recently, there has been a lot of interest in applying radar data as input to various deep learning algorithms, as more datasets are being provided. To this end, this paper presents a survey of various deep learning approaches processing radar signals to accomplish some significant tasks in an autonomous driving application, such as detection and classification. We have itemized the review based on different radar signal representations, as it is one of the critical aspects while using radar data with deep learning models. Furthermore, we give an extensive review of the recent deep learning-based multi-sensor fusion models exploiting radar signals and camera images for object detection tasks. We then provide a summary of the available datasets containing radar data. Finally, we discuss the gaps and important innovations in the reviewed papers and highlight some possible future research prospects.
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Beckwith, Dana M., and Katharine M. Hunter-Zaworski. "Passive Pedestrian Detection at Unsignalized Crossings." Transportation Research Record: Journal of the Transportation Research Board 1636, no. 1 (1998): 96–103. http://dx.doi.org/10.3141/1636-16.
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The city of Portland, Oregon, is researching ways to provide safe unsignalized crossings for pedestrians. A concept that shows promise is known as passive pedestrian detection. Passive pedestrian detection is the detection of pedestrians in a stationary or moving state at the curbside of or in a pedestrian crossing by means other than those requiring physical response by the pedestrian. Research was conducted to find sensor technologies that can be used to passively detect pedestrians. Five technologies were found to be options for this type of detection: passive infrared, ultrasonic, microwave radar, video imaging, and piezometric. Of these five technologies, passive infrared, ultrasonic, and microwave radar were selected for testing. An unbiased selection of sensors was made by using a decision matrix in the form of the quality function deployment method, which also provides a record of sensor information for future research. Preliminary testing was conducted on the sensors to ensure that the detection of pedestrians was possible and to determine sensor operating characteristics. Sensors then went through secondary tests to ensure proper operation at an unsignalized crossing. The secondary test site was retrofitted with reflective pedestrian crossing signs, yellow beacons, Doppler radar, and passive infrared sensors chosen from the preliminary tests. Initial secondary tests have shown promising results for the Doppler radar and especially for the passive infrared sensors. Future applications of passive pedestrian detection in Portland will involve installation of sensors at signalized pedestrian crossings.
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Zhang, Jian, Kenneth Howard, Carrie Langston, et al. "Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities." Bulletin of the American Meteorological Society 97, no. 4 (2016): 621–38. http://dx.doi.org/10.1175/bams-d-14-00174.1.
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Abstract Rapid advancements of computer technologies in recent years made the real-time transferring and integration of high-volume, multisource data at a centralized location a possibility. The Multi-Radar Multi-Sensor (MRMS) system recently implemented at the National Centers for Environmental Prediction demonstrates such capabilities by integrating about 180 operational weather radars from the conterminous United States and Canada into a seamless national 3D radar mosaic with very high spatial (1 km) and temporal (2 min) resolution. The radar data can be integrated with high-resolution numerical weather prediction model data, satellite data, and lightning and rain gauge observations to generate a suite of severe weather and quantitative precipitation estimation (QPE) products. This paper provides an overview of the initial operating capabilities of MRMS QPE products.
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Park, Jae-Hyun, Yeo-Jin Jeong, Ga-Eun Lee, Jun-Taek Oh, and Jong-Ryul Yang. "915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs." Electronics 8, no. 5 (2019): 561. http://dx.doi.org/10.3390/electronics8050561.
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A miniaturized continuous-wave Doppler radar sensor operating at 915 MHz to remotely detect both respiration and heart rate (beats per minute) is presented. The proposed radar sensor comprises a front-end module including an implemented complementary metal-oxide semiconductor low-noise amplifier (LNA) and fractal-slot patch antennas, whose area was reduced by 15.2%. The two-stage inverter-based LNA was designed with an interstage capacitor and a feedback resistor to acquire ultrawide bandwidth. Two operating frequencies, 915 MHz and 2.45 GHz, were analyzed with regard to path loss for efficient operation because frequency affects detection sensitivity, reflected signal power from the human body, and measurement distance in a far-field condition. Path-loss calculation based on the simplified layer model indicates that the reflected power of the 915 MHz radar could be higher than that of the 2.45 GHz radar. The implemented radar front-end module excluding the LNA occupies 35 × 55 mm2. Vital signs were obtained via a fast Fourier transform and digital filtering using raw signals. In an experiment with six subjects, the respiration and heart rate obtained at 0.8 m using the proposed radar sensor exhibited mean accuracies of 99.4% and 97.6% with respect to commercialized reference sensors, respectively.
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Pegau, W. Scott, Jessica Garron, Leonard Zabilansky, et al. "Detection of oil in and under ice." International Oil Spill Conference Proceedings 2017, no. 1 (2017): 1857–76. http://dx.doi.org/10.7901/2169-3358-2017.1.1857.
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ABSTRACT (2017-147) In 2014, researchers from ten organizations came to the U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory (CRREL) in New Hampshire to conduct a first of its kind large-scale experiment aimed at determining current sensor capabilities for detecting oil in and under sea ice. This project was the second phase of the Oil Spill Detection in Low Visibility and Ice research project of the International Association of Oil and Gas Producers (IOGP), Arctic Oil Spill Response Technology - Joint Industry Programme. The objectives of the project were to:Acquire acoustic, thermal, optical and radar signatures of oil on, within, and underneath a level sheet of laboratory sea ice.Determine the capabilities of various sensors to detect oil in specific ice environments created in a test tank, including freeze-up, growth and melt.Model the potential performance of the sensors under realistic field conditions using the test data for validation.Recommend the most effective sensor suite of existing sensors for detecting oil in the ice environment. The sensor testing spanned a two-month ice growth phase and a one-month decay/melt period. The growth phase produced an 80 centimeter thick level sheet of salt water ice representative of natural sea ice grown under quiescent conditions. Above-ice sensors included frequency modulated continuous wave radar, ground penetrating radar, laser fluorescence polarization sensor, spectral radiometer, visible and infrared cameras. Below-ice sensors included acoustics (broadband, narrowband, and multibeam sonars), spectral radiometers, cameras, and fluorescence polarization. Measurements of physical and electrical properties of the ice and oil within the ice were provided to optical, acoustic, and radar modelers as inputs into their models. The models were then used to extrapolate the sensors’ laboratory performance to potential performance over a range of field conditions. All selected sensors detected oil under some conditions. The radar systems were the only above-ice sensors capable of detecting oil below or trapped within the ice. Cameras below the ice detected oil at all stages of ice growth, and the acoustic and fluorescence systems detected encapsulated oil through limited amounts of new ice growth beneath the oil. No single sensor detected oil in and below ice under all conditions tested. However, we used the test results to identify suites of sensors that could be deployed today both above and below the ice to detect and map an oil spill within ice covered waters.
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Sickinger, Frank, Ernst Weissbrodt, and Martin Vossiek. "76–81 GHz LTCC antenna for an automotive miniature radar frontend." International Journal of Microwave and Wireless Technologies 10, no. 5-6 (2018): 729–36. http://dx.doi.org/10.1017/s1759078718000855.
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AbstractFor a fully 360° detection around a vehicle, novel automotive radar system concepts consist of up to eight radar sensors. The existing sensor-mounting areas, such as front grill or bumper corners would no longer be sufficient. Therefore, additional mounting positions such as B-pillars and side skirts have to be considered, where the radar can observe the side area of the vehicle. However, these new mounting positions usually offer significantly less space, than the established mounting areas. The solution is, to build separate miniature radar frontends that can be placed all over the vehicle and are connected to one central signal processing and power supply unit. Investigations for a miniature radar frontend have been done, based on RF360 low loss non-shrinkage low-temperature cofired ceramic (LTCC) substrate. For the automotive radar band (76–81 GHz), an array antenna has been simulated, manufactured, and the radiation pattern has been measured. A first sensor with a miniature radar frontend based on an LTCC multilayer has been designed and manufactured.
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Hellbrück, Horst, Gunther Ardelt, Philipp Wegerich, and Hartmut Gehring. "Brachialis Pulse Wave Measurements with Ultra-Wide Band and Continuous Wave Radar, Photoplethysmography and Ultrasonic Doppler Sensors." Sensors 21, no. 1 (2020): 165. http://dx.doi.org/10.3390/s21010165.
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The measurement and analysis of the arterial pulse wave provides information about the state of vascular health. When measuring blood pressure according to Riva-Rocci, the systolic and diastolic blood pressure is measured non-invasively with an inflatable pressure cuff on the upper arm. Today’s blood pressure monitors analyze the pulse wave in reference to the rising or falling cuff pressure. With the help of additional pulse wave analysis, one can determine the pulse rate and the heart rate variability. In this paper, we investigated the concept, the construction, and the limitations of ultrawideband (UWB) radar and continuous wave (CW) radar, which provide continuous and non-invasive pulse wave measurements. We integrated the sensors into a complete measurement system. We measured the pulse wave of the cuff pressure, the radar sensor (both UWB and CW), the optical sensor, and ultrasonic Doppler as a reference. We discussed the results and the sensor characteristics. The main conclusion was that the resolution of the pulse radar was too low, even with a maximum bandwidth of 10 GHz, to measure pulse waves reliably. The continuous wave radar provides promising results for a phantom if adjusted properly with phase shifts and frequency. In the future, we intend to develop a CW radar solution with frequency adaption.
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Palandro, David, and Joseph Mullin. "Advances in Remote Sensing Research on Oil and Ice from the IOGP Arctic Oil Spill Response Technology JIP." International Oil Spill Conference Proceedings 2017, no. 1 (2017): 1819–35. http://dx.doi.org/10.7901/2169-3358-2017.1.1819.
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ABSTRACT (2017-044) The IOGP Arctic Oil Spill Response Technology Joint Industry Program’s Remote Sensing Technical Working Group was initiated in 2012 with the objective to expand the oil industry’s detection and monitoring capabilities for spills on, under, around or in ice. The first phase produced two state-of-knowledge reports assessing sensor capabilities above and below the ice. A key finding from these studies was that many existing remote sensing platforms and sensors originally developed for oil on open water can also provide effective sensing in a broad range of ice conditions. The second phase covered an integrated experiment that included sensor testing in a cold basin, followed by modeling to determine potential applicability of different sensors in a wider range of sea-ice conditions. Five above-ice (Frequency Modulated Continuous Wave Radar (FMCW), ground penetrating radar (GPR), visible and infrared cameras and laser fluorescence polarization [LP] sensor) and seven below-ice (high dynamic range optical camera, visible and infrared spectrometer, LP sensor, broadband and narrowband sonar and multibeam echo sounder) sensors were tested with varying ice thickness and oil concentrations at the US Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) over a three-month period. All of the sensors used during this experiment showed some ability to detect oil on, in, or below ice under certain conditions and major advances in the knowledge of sensor applicability were made. Three follow-on projects (late 2016) include an operations guide providing a concise operationally oriented review of the different sensor technologies in key oil and ice scenarios, and additional field testing with medium to long-wave infrared, and the FMCW radar.
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Lee, Seongwook, Song-Yi Kwon, Bong-Jun Kim, Hae-Seung Lim, and Jae-Eun Lee. "Dual-Mode Radar Sensor for Indoor Environment Mapping." Sensors 21, no. 7 (2021): 2469. http://dx.doi.org/10.3390/s21072469.
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In this paper, we introduce mapping results in an indoor environment based on our own developed dual-mode radar sensor. Our radar system uses a frequency-modulated continuous wave (FMCW) with a center frequency of 62 GHz and a multiple-input multiple-output antenna system. In addition, the FMCW radar sensor we designed is capable of dual-mode detection, which alternately transmits two waveforms using different bandwidths within one frame. The first waveform is for long-range detection, and the second waveform is for short-range detection. This radar system is mounted on a small robot that moves in indoor environments such as rooms or hallways, and the radar and the robot send and receive necessary information to each other. The radar estimates the distance, velocity, and angle information of targets around the radar-equipped robot. Then, the radar receives information about the robot’s motion from the robot, such as its speed and rotation angle. Finally, by combining the motion information and the detection results, the radar-equipped robot maps the indoor environment while finding its own position. Compared to the actual map data, the radar-based mapping is effectively achieved through the radar system we developed.
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Kirincich, Anthony. "Toward Real-Time, Remote Observations of the Coastal Wind Resource Using High-Frequency Radar." Marine Technology Society Journal 47, no. 4 (2013): 206–17. http://dx.doi.org/10.4031/mtsj.47.4.22.
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AbstractThere is now a large installed base of high-frequency (HF) coastal ocean radars in the United States able to measure surface currents on an operational basis. However, these instruments also have the potential to provide estimates of the spatially variable surface wind field over distances ranging from 10 to 200 km offshore. This study investigates the ability of direction-finding HF radars to recover spatial maps of wind speed and direction from the dominant first-order region radar returns using empirical models. Observations of radar backscatter from the Martha’s Vineyard Coastal Observatory HF radar system were compared to wind observations from an offshore tower, finding significant correlations between wind speed and the backscatter power for a range of angles between the wind and radar loop directions. Models for the directional spreading of wind waves were analyzed in comparison to data-based results, finding potentially significant differences between the model and data-based spreading relationships. Using empirical fits, radar-based estimates of wind speed and direction at the location of the in situ wind sensor had error rates of 2 m/s and 60°, which decreased with hourly averaging. Attempts to extrapolate the results to the larger domain illustrated that spatially dependent transfer functions for wind speed and direction appear possible for large coastal ocean domains based on a small number of temporary, or potentially mobile, in situ wind sensors.
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Yim, Daehyeon, Won Lee, Johanna Kim, et al. "Quantified Activity Measurement for Medical Use in Movement Disorders through IR-UWB Radar Sensor." Sensors 19, no. 3 (2019): 688. http://dx.doi.org/10.3390/s19030688.
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Movement disorders, such as Parkinson’s disease, dystonia, tic disorder, and attention-deficit/hyperactivity disorder (ADHD) are clinical syndromes with either an excess of movement or a paucity of voluntary and involuntary movements. As the assessment of most movement disorders depends on subjective rating scales and clinical observations, the objective quantification of activity remains a challenging area. The purpose of our study was to verify whether an impulse radio ultra-wideband (IR-UWB) radar sensor technique is useful for an objective measurement of activity. Thus, we proposed an activity measurement algorithm and quantitative activity indicators for clinical assistance, based on IR-UWB radar sensors. The received signals of the sensor are sufficiently sensitive to measure heart rate, and multiple sensors can be used together to track the positions of people. To measure activity using these two features, we divided movement into two categories. For verification, we divided these into several scenarios, depending on the amount of activity, and compared with an actigraphy sensor to confirm the clinical feasibility of the proposed indicators. The experimental environment is similar to the environment of the comprehensive attention test (CAT), but with the inclusion of the IR-UWB radar. The experiment was carried out, according to a predefined scenario. Experiments demonstrate that the proposed indicators can measure movement quantitatively, and can be used as a quantified index to clinically record and compare patient activity. Therefore, this study suggests the possibility of clinical application of radar sensors for standardized diagnosis.
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Yoo, Sungwon, Shahzad Ahmed, Sun Kang, et al. "Radar Recorded Child Vital Sign Public Dataset and Deep Learning-Based Age Group Classification Framework for Vehicular Application." Sensors 21, no. 7 (2021): 2412. http://dx.doi.org/10.3390/s21072412.
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The ongoing intense development of short-range radar systems and their improved capability of measuring small movements make these systems reliable solutions for the extraction of human vital signs in a contactless fashion. The continuous contactless monitoring of vital signs can be considered in a wide range of applications, such as remote healthcare solutions and context-aware smart sensor development. Currently, the provision of radar-recorded datasets of human vital signs is still an open issue. In this paper, we present a new frequency-modulated continuous wave (FMCW) radar-recorded vital sign dataset for 50 children aged less than 13 years. A clinically approved vital sign monitoring sensor was also deployed as a reference, and data from both sensors were time-synchronized. With the presented dataset, a new child age-group classification system based on GoogLeNet is proposed to develop a child safety sensor for smart vehicles. The radar-recorded vital signs of children are divided into several age groups, and the GoogLeNet framework is trained to predict the age of unknown human test subjects.
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Siart, U., S. Tejero, and J. Detlefsen. "Exponential Modelling for Mutual-Cohering of Subband Radar Data." Advances in Radio Science 3 (May 12, 2005): 199–204. http://dx.doi.org/10.5194/ars-3-199-2005.
Full textAbstract:
Abstract. Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.
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Gaitanakis, George-Konstantinos, George Limnaios, and Konstantinos Zikidis. "AESA radar and IRST against low observable threats." Aircraft Engineering and Aerospace Technology 92, no. 9 (2020): 1421–28. http://dx.doi.org/10.1108/aeat-01-2020-0011.
Full textAbstract:
Purpose Modern fighter aircraft using active electronically scanned array (AESA) fire control radars are able to detect and track targets at long ranges, in the order of 50 nautical miles or more. Low observable or stealth technology has contested the radar capabilities, reducing detection/tracking ranges roughly to one-third (or even less, for fighter aircraft radar). Hence, infrared search and track (IRST) systems have been reconsidered as an alternative to the radar. This study aims to explore and compare the capabilities and limitations of these two technologies, AESA radars and IRST systems, as well as their synergy through sensor fusion. Design/methodology/approach The AESA radar range is calculated with the help of the radar equation under certain assumptions, taking into account heat dissipation requirements, using the F-16 fighter as a case study. Concerning the IRST sensor, a new model is proposed for the estimation of the detection range, based on the emitted infrared radiation caused by aerodynamic heating. Findings The maximum detection range provided by an AESA radar could be restricted because of the increased waste heat which is produced and the relevant constraints concerning the cooling capacity of the carrying aircraft. On the other hand, IRST systems exhibit certain advantages over radars against low observable threats. IRST could be combined with a datalink with the help of data fusion, offering weapons-quality track. Originality/value An original approach is provided for the IRST detection range estimation. The AESA/IRST comparison offers valuable insight, while it allows for more efficient planning, at the military acquisition phase, as well as at the tactical level.