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Journal articles on the topic 'CA-CFAR algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Kamal, Mustafa Subhi, and Jiwa Abdullah. "New algorithm for multi targets detection in clutter edge radar environments." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 420. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp420-427.

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<p>This paper deals with the problem of multi target detection that appears inside clutter cloud which represent the worst radar environments by using constant false alarm rate CFAR algorithm, in order to achieve maximum probability of detection with constant false alarm rate, to detect target in such environments it need to construct robust constant false alarm CFAR algorithm that excise the target spikes from CFAR window and deal with clutter edges in order to give best possible estimation to the noise background. Modified cell averaged (CA-CFAR) is analyzed and compared with Two impor

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Leila, Tabet, and Faouzi Soltan. "A modified environmental adaptive CFAR detector in non-homogenous gaussian clutter." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 2 (2024): e10580. http://dx.doi.org/10.54021/seesv5n2-527.

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The Environmental Adaptive CFAR (EA-CFAR ) detector, which is based on both Cell-Averaging CFAR (CA-CFAR) and the ordered statistics CFAR (OS-CFAR) detectors, selects an optimal CFAR detector depending on the environment. A mathematical analysis of the EA-CFAR validates the robustness of the detector in homogenous and non homogenous background. Since the Censored Mean Level detector CFAR (CMLD-CFAR) has a better performance in a multiple target environment than the OS-CFAR, in this paper; we propose a new CFAR algorithm which is a generalization of the EA-CFAR., namely, the MEA-CFAR (Modified

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Radosavljević, Zvonko, and Dejan Ivković. "An approach of constant false alarm ratio for improved target tracking." Scientific Technical Review 70, no. 3 (2020): 17–23. http://dx.doi.org/10.5937/str2003017r.

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Each radar has the function of surveillance of certain areas of interest. In particular, the radar also has the function of tracking moving targets in that territory with some probability of detection, which depends on the type of detector. Constant false alarm ratio (CFAR) is a very commonly used detector. Changing the probability of target detection can directly affect the quality of tracking the moving targets. The paper presents the theoretical basis of the influence of CFAR detectors on the quality of tracking, as well as an approach to the selection of CFAR detectors, CATM CFAR, which en

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Qin, Tian-Ci, Zhong-Xun Wang, Yong Huang, Hao-Xuan Wei, and Yan Liu. "VIHCEMOS-CFAR Detector Based on Improved VI-CFAR." Journal of Physics: Conference Series 2613, no. 1 (2023): 012007. http://dx.doi.org/10.1088/1742-6596/2613/1/012007.

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Abstract A variability index heterogeneous clutter estimate modified ordered statistics constant false alarm rate (VIHCEMOS-CFAR) detector based on improved VI-CFAR is proposed. First calculate the VI and MR values and then judge the clutter background: If the background is uniform, cell averaging (CA) target detection strategy is adopted; HCE detection strategy is adopted if it is clutter edge background; If it is a complex background composed of multiple targets or strong clutter, the OS detection strategy is adopted. The method of judging the interfering targets and strong clutter in the re

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Li, Juan, Yunlong Dong, Ningbo Liu, Yong Huang, Xingyu Jiang, and Jinping Sun. "A Novel Copula-Based Multi-Feature CFAR Framework for Radar Target Detection." Remote Sensing 17, no. 13 (2025): 2299. https://doi.org/10.3390/rs17132299.

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Multi-feature radar target detection enhances the discrimination between targets and clutter, thereby improving detection accuracy. However, the complex nonlinear dependencies among features present significant challenges for precise control of the false alarm rate (FAR). In this paper, a novel constant false alarm rate (CFAR) framework for multi-feature detection is proposed. First, a Copula-CFAR theorem is established, which models the feature dependence structure and enables the derivation of closed-form expressions for probability of false alarm (PFA) and detection probability across vario

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SK, Jainuddin, Satyanarayana P, and Aruna V.B.K.L. "Multiple targets detection in the marine environment using matlab." International Journal of Engineering & Technology 7, no. 4 (2018): 2397. http://dx.doi.org/10.14419/ijet.v7i4.14088.

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This paper implements multiple targets detection against sea clutter by mathematically modeling target as a single point target and sea-clutter as k-distribution model and observing the deterioration in the effective operation of radar using signal processing by matlab. A Variability Index (VI) algorithm is suggested for detection on the basis of constant false-alarm rate (CFAR) property even in heteroge-neous conditions. Comparative analysis of VI-CFAR against various CFAR methods (CA, GO, SO, OS) for multiple targets detection in heterogeneous environment is done in this paper. Comparison an

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Putri, Farra Anindya, Dayat Kurniawan, Rahmawati Hasanah, et al. "Development of FMCW Radar Signal Processing for High-Speed Railway Collision Avoidance." Jurnal Elektronika dan Telekomunikasi 22, no. 1 (2022): 40. http://dx.doi.org/10.55981/jet.482.

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Collision is the main issue in safe transportation, including in the railway system. Sensor systems have been developed to detect obstacles to prevent a collision, such as using cameras. One disadvantage of the camera systems is that performance detection decreases in a not clean environment, like the target position behind the fogs. This paper discusses the development of frequency modulated continuous wave (FMCW) radar signal processing for high-speed railway collision avoidance. The development of radar signal processing combines a two-dimensional constant false alarm rate (2D-CFAR) and rob

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Sun Binbin, 孙宾宾, 沈涛 Shen Tao, 李洪鹏 Li Hongpeng, 崔晓荣 Cui Xiaorong, and 陈雨魁 Chen Yukui. "Improved CA-CFAR Algorithm Based on LFMCW Radar Multi-Target Detection." Laser & Optoelectronics Progress 58, no. 8 (2021): 0815005. http://dx.doi.org/10.3788/lop202158.0815005.

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Endo, Koji, Kohei Yamamoto, and Tomoaki Ohtsuki. "A Denoising Method Using Deep Image Prior to Human-Target Detection Using MIMO FMCW Radar." Sensors 22, no. 23 (2022): 9401. http://dx.doi.org/10.3390/s22239401.

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A Multiple-Input Multiple-Output (MIMO) Frequency-Modulated Continuous Wave (FMCW) radar can provide a range-angle map that expresses the signal power against each range and angle. It is possible to estimate object locations by detecting the signal power that exceeds a threshold using an algorithm, such as Constant False Alarm Rate (CFAR). However, noise and multipath components often exist over the range-angle map, which could produce false alarms for an undesired location depending on the threshold setting. In other words, the threshold setting is sensitive in noisy range-angle maps. Therefo

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10

Monakov, A. A. "CFAR Target Detector in Synthetic Aperture Radar." Journal of the Russian Universities. Radioelectronics 27, no. 3 (2024): 52–67. http://dx.doi.org/10.32603/1993-8985-2024-27-3-52-67.

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Introduction. Constant false alarm rate (CFAR) detectors have found application in synthetic aperture radar (SAR) systems. The operating principle of a classic cell averaging detector (CA-CFAR detector) is based on comparing the decision statistics in the test resolution element with an adaptive threshold, which is calculated from signals in the reference cells. The decision statistic is an estimate of the signal power. Therefore, target signal detection is based on the brightness contrast of the test and reference resolution cells. Such a detector is optimal provided that the noise background

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Huang, Jiayun, Liwei Yang, Jiqin Zhang, and Hao Hu. "Granular Fertilizer Mass Flow Measurement and Vehicle Experiments Based on Microwave Doppler Method." Applied Engineering in Agriculture 37, no. 1 (2021): 135–47. http://dx.doi.org/10.13031/aea.14013.

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HighlightsA microwave Doppler-based fertilizer mass flow measurement system was developed.The measurement system was applied in vehicle experiments.Power spectra of mass flow signal and vibration signal were obtained and analyzed.Interference suppression algorithm based on CA-CFAR reduced vibration interference.Fertilizer mass flow measurement accuracy was improved by interference suppression.Abstract. The fertilizer mass flow measurement system is typically installed on the fertilizer applicator. However, vehicle vibrations are inevitable during field operation of fertilizing equipment, and c

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Shen, Wenjie, Jie Zhi, Yanping Wang, et al. "Two-Step CFAR-Based 3D Point Cloud Extraction Method for Circular Scanning Ground-Based Synthetic Aperture Radar." Applied Sciences 13, no. 12 (2023): 7164. http://dx.doi.org/10.3390/app13127164.

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Ground-Based Synthetic Aperture Radar (GBSAR) has non-contact, all-weather, high resolution imaging and microdeformation sensing capabilities, which offers advantages in applications such as building structure monitoring and mine slope deformation retrieval. The Circular Scanning Ground-Based Synthetic Aperture Radar (CS-GBSAR) is one of its newest developed working mode, in which the radar rotates around an axis in a vertical plane. Such nonlinear observation geometry brings the unique advantage of three-dimensional (3D) imaging compared with traditional GBSAR modes. However, such nonlinear o

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Liang, Zhihuan, Yanghao Jin, Degui Yang, Buge Liang, and Jinjun Mo. "Two-Step Accuracy Improvement for Multitarget Detection in Complex Environment Using UWB Radar." Remote Sensing 16, no. 5 (2024): 877. http://dx.doi.org/10.3390/rs16050877.

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Detecting multiple human targets in indoor scenarios using ultra-wideband (UWB) radar usually involves false detection results caused by the secondary reflections, which might reduce the target detection accuracy and cause a more severe deterioration when the number of targets increases. This article proposed a two-step accuracy improvement method for multitarget detection in environments with multiple human targets of more than three and strong secondary reflections by the surroundings, especially the walls. Based on the rough detection results acquired by the modified CA-CFAR (MCA-CFAR) proc

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Zhang, Yongshun, Xin Jia, and Ge Song. "Joint Interference Detection Method for DSSS Communications Based on the OMP Algorithm and CA-CFAR." MATEC Web of Conferences 56 (2016): 05011. http://dx.doi.org/10.1051/matecconf/20165605011.

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15

Wang, Yanping, Dandan Qu, Chao Zhao, and Dan Yang. "Study on CA-CFAR Algorithm Based on Normalization Processing of Background Noise for HI of Optical Fiber." Photonic Sensors 8, no. 4 (2018): 341–50. http://dx.doi.org/10.1007/s13320-018-0498-5.

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Tseng, Tzu-Jung, and Jian-Jiun Ding. "Adaptive Trajectories’ Constant False Alarm Rate Mirror Filters and Elevation Angle Evaluation for Multiple-Input Multiple-Output Radar-Based Hand Gesture Recognition." Electronics 13, no. 4 (2024): 682. http://dx.doi.org/10.3390/electronics13040682.

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Gesture recognition technology has been quickly developed in the field of human–computer interaction. The multiple-input multiple-output (MIMO) radar is popular in gesture recognition because of its notable spatial resolution. This work proposes a MIMO radar-based hand gesture recognition algorithm with low complexity. We leverage low-complexity adaptive signal processing to extract trajectory information and minimize noise to create a system that can be applied in real-world applications with small training datasets. First, a spectrum analysis is utilized on range-Doppler maps (RDMs), and a c

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17

Chen, Xiaolong, Jian Guan, Xiaoqian Mu, Zhigao Wang, Ningbo Liu, and Guoqing Wang. "Multi-Dimensional Automatic Detection of Scanning Radar Images of Marine Targets Based on Radar PPInet." Remote Sensing 13, no. 19 (2021): 3856. http://dx.doi.org/10.3390/rs13193856.

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Traditional radar target detection algorithms are mostly based on statistical theory. They have weak generalization capabilities for complex sea clutter environments and diverse target characteristics, and their detection performance would be significantly reduced. In this paper, the range-azimuth-frame information obtained by scanning radar is converted into plain position indicator (PPI) images, and a novel Radar-PPInet is proposed and used for marine target detection. The model includes CSPDarknet53, SPP, PANet, power non-maximum suppression (P-NMS), and multi-frame fusion section. The pred

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18

Lanz, Peter, Armando Marino, Thomas Brinkhoff, Frank Köster, and Matthias Möller. "The InflateSAR Campaign: Testing SAR Vessel Detection Systems for Refugee Rubber Inflatables." Remote Sensing 13, no. 8 (2021): 1487. http://dx.doi.org/10.3390/rs13081487.

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Countless numbers of people lost their lives at Europe’s southern borders in recent years in the attempt to cross to Europe in small rubber inflatables. This work examines satellite-based approaches to build up future systems that can automatically detect those boats. We compare the performance of several automatic vessel detectors using real synthetic aperture radar (SAR) data from X-band and C-band sensors on TerraSAR-X and Sentinel-1. The data was collected in an experimental campaign where an empty boat lies on a lake’s surface to analyse the influence of main sensor parameters (incidence

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19

Park, Jae-Shin, Jeong-Pyo Kim, and Doo-Yeong Yang. "Implementation of Wide Angle FoV Radar Module for ADAS Systems." Journal of Electromagnetic Engineering and Science 24, no. 5 (2024): 477–84. http://dx.doi.org/10.26866/jees.2024.5.r.249.

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In this study, we propose the wide field of view (FoV) radar module for autonomous vehicles. The proposed wide FoV radar (WFR) module was constructed using of an RF module comprising wide beamwidth microstrip patch antennas, an AWR1642 radar sensor chip, and a control module. To achieve a wide FoV of 150° using the fabricated radar module, the 3-dB beamwidth characteristic of the applied microstrip patch antenna had to wider than 150°. The patch antenna was designed using a comb-line structure along 10-by-1 array structure, each radiator characterized by a shorted patch structure, such as a pl

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20

Hu, Yili, Yongbo Zhao, and Sheng Chen. "Incoherent Integration Detection Method of Airborne Phased Array Radar in a Multipath Environment." International Journal of Antennas and Propagation 2021 (December 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/8699512.

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Airborne phased array radar (PAR) suffers from multipath problems when flying over a calm sea surface. The existence of a multipath phenomenon will cause the electromagnetic echo of the same target to be reflected back to the airborne PAR from two paths, namely, direct path (DP) and multipath. Compared with the ground-based radar, the target echo received by airborne PAR in the multipath environment has two important characteristics: one is that the DP signal and the multipath signal exist in different range bins, and the other is that the radar cross section (RCS) in the DP direction may be s

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21

Tang, Gang, Yichao Zhuge, Christophe Claramunt, and Shaoyang Men. "N-YOLO: A SAR Ship Detection Using Noise-Classifying and Complete-Target Extraction." Remote Sensing 13, no. 5 (2021): 871. http://dx.doi.org/10.3390/rs13050871.

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High-resolution images provided by synthetic aperture radar (SAR) play an increasingly important role in the field of ship detection. Numerous algorithms have been so far proposed and relative competitive results have been achieved in detecting different targets. However, ship detection using SAR images is still challenging because these images are still affected by different degrees of noise while inshore ships are affected by shore image contrasts. To solve these problems, this paper introduces a ship detection method called N-YOLO, which based on You Only Look Once (YOLO). The N-YOLO includ

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Wu, Kun, Zhijian Zhang, Zeyu Chen, and Guohua Liu. "Object-Enhanced YOLO Networks for Synthetic Aperture Radar Ship Detection." Remote Sensing 16, no. 6 (2024): 1001. http://dx.doi.org/10.3390/rs16061001.

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Synthetic aperture radar (SAR) enables precise object localization and imaging, which has propelled the rapid development of algorithms for maritime ship identification and detection. However, most current deep learning-based algorithms tend to increase network depth to improve detection accuracy, which may result in the loss of effective features of the target. In response to this challenge, this paper innovatively proposes an object-enhanced network, OE-YOLO, designed specifically for SAR ship detection. Firstly, we input the original image into an improved CFAR detector, which enhances the

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Zhang, Li, Hai Lin, Ke Wang, and Feng Zhang. "A Low‐Complexity Target Detection Technique Using the Prefix Sum Algorithm." Electronics Letters 61, no. 1 (2025). https://doi.org/10.1049/ell2.70202.

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ABSTRACTA conventional target detection technique for FMCW millimeter‐wave radar applies a two‐dimensional (2D) cell‐averaging constant false alarm rate (CA‐CFAR) detector to all range‐doppler cells in order to suppress noise and clutter. However, this 2D CA‐CFAR method has significant drawbacks, particularly its high computational cost due to the large number of additions required, resulting in a time complexity of O(n4). To decrease the computational complexity while ensuring the detection accuracy, a novelty CA‐CFAR technique based on the prefix sum algorithm with a complexity O(n2) is prop

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H., Krouma, Barkat M., Kemih K., Benslama M., and Yacine Y. "Performance Analysis of an Adaptive Threshold Hybrid Double-Dwell System with Antenna Diversity for Acquisition in DS-CDMA Systems." December 21, 2008. https://doi.org/10.5281/zenodo.1081822.

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In this paper, we consider the analysis of the acquisition process for a hybrid double-dwell system with antenna diversity for DS-CDMA (direct sequence-code division multiple access) using an adaptive threshold. Acquisition systems with a fixed threshold value are unable to adapt to fast varying mobile communications environments and may result in a high false alarm rate, and/or low detection probability. Therefore, we propose an adaptively varying threshold scheme through the use of a cellaveraging constant false alarm rate (CA-CFAR) algorithm, which is well known in the field of radar detect

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