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Artykuły w czasopismach na temat „Single target tracking algorithms”

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Data publikacji: 6 września 2023

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1

Ling, Jiankun. "Target Tracking Using Kalman Filter Based Algorithms." Journal of Physics: Conference Series 2078, no. 1 (2021): 012020. http://dx.doi.org/10.1088/1742-6596/2078/1/012020.

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Abstract Kalman filter and its families have played an important role in information gathering, such as target tracking. Data association techniques have also been developed to allow the Kalman filter to track multiple targets simultaneously. This paper revisits the principle and applications of the Kalman filter for single target tracking and multiple hypothesis tracking (MHT) for multiple target tracking. We present the brief review of the Bayes filter family and introduce a brief derivation of the Kalman filter and MHT. We show examples for both single and multiple targets tracking in simul

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ZhongMing Liao and Azlan Ismail. "Performance of Correlational Filtering and Deep Learning Based Single Target Tracking Algorithms." Journal of Smart Science and Technology 3, no. 1 (2023): 63–79. http://dx.doi.org/10.24191/jsst.v3i1.42.

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Visual target tracking is an important research element in the field of computer vision. The applications are very wide. In terms of the computer vision field, deep learning has achieved remarkable results. It has broken through many complex problems that are difficult to be solved by traditional algorithms. Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. This paper closely follows the tracking framework of target tracking algorithms and discusses in detail the traditional visual target tracking methods, the mainstream

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3

Qu, Zhiyi, Xue Zhao, Huihui Xu, Hongying Tang, Jiang Wang, and Baoqing Li. "An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking." Sensors 22, no. 18 (2022): 6972. http://dx.doi.org/10.3390/s22186972.

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Target tracking is an essential issue in wireless sensor networks (WSNs). Compared with single-target tracking, how to guarantee the performance of multi-target tracking is more challenging because the system needs to balance the tracking resource for each target according to different target properties and network status. However, the balance of tracking task allocation is rarely considered in those prior sensor-scheduling algorithms, which may result in the degradation of tracking accuracy for some targets and additional system energy consumption. To address this issue, we propose in this pa

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4

Zhang, Haozheng, Xiong Li, and Yu Meng. "Performance Study of Two Bearings-only Target Tracking Algorithms." Journal of Physics: Conference Series 2419, no. 1 (2023): 012086. http://dx.doi.org/10.1088/1742-6596/2419/1/012086.

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Abstract For the bearings-only target tracking for single array, the tracking performance of extended kalman filter algorithm in cartesian coordinates and modified polar coordinates is studied. The result shows that the performance of extended kalman filter algorithm in polar coordinates is more general than that in cartesian coordinates. In addition, the tracking performance of these two algorithms decreases with an increase in azimuth measurement error.

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Yuan, Xianghui, Feng Lian, and Chongzhao Han. "Models and Algorithms for Tracking Target with Coordinated Turn Motion." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/649276.

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Tracking target with coordinated turn (CT) motion is highly dependent on the models and algorithms. First, the widely used models are compared in this paper—coordinated turn (CT) model with known turn rate, augmented coordinated turn (ACT) model with Cartesian velocity, ACT model with polar velocity, CT model using a kinematic constraint, and maneuver centered circular motion model. Then, in the single model tracking framework, the tracking algorithms for the last four models are compared and the suggestions on the choice of models for different practical target tracking problems are given. Fi

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6

Wei, Hao, Zong-ping Cai, Bin Tang, and Ze-xiang Yu. "Review of the algorithms for radar single target tracking." IOP Conference Series: Earth and Environmental Science 69 (June 2017): 012073. http://dx.doi.org/10.1088/1755-1315/69/1/012073.

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Zhang, Ming, Li Wang, Hai Hua Shi, and Wei Xiang. "The Target Tracking Algorithm Research of Independent Vision Robot Fish." Advanced Materials Research 753-755 (August 2013): 2015–19. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.2015.

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In the independent vision robot fish games, the interference of water wave often causes tracking inaccuracy and target tracking failure. In order to solve these problems, the Meanshift algorithm and the combination of Meanshift algorithm and Kalman filter respectively are studied to realize target tracking of independent vision robot fish in this paper. By comparing the two algorithms, the results show that: the former tracking algorithm is not ideal and easy to lose the target. The combined algorithm of Meanshift and Kalman filter can effectively improve the performance of single-target track

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8

Chang-Jian Wang, Chang-Jian Wang, Yong Ding Chang-Jian Wang, and Ye Ji Yong Ding. "An Improved Kernel Correlation Filter Tracking Combined with Mobilenet SSD." 電腦學刊 33, no. 2 (2022): 069–81. http://dx.doi.org/10.53106/199115992022043302006.

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<p>This article mainly solves the problems that exist when using the Kernel Correlation Filter (KCF) for tracking in complex scenarios. To make the algorithm suitable for target tracking under complex conditions such as scale changes, similar interference, and occlusion, a MobileNet SSD (Single Shot Detection) target detection combined with an improved KCF target tracking algorithm is proposed. Firstly, the MobileNet SSD is used to locate the target in the initial frame, and the location is sent to KCF for training. Secondly, aiming at the problem of scale changes, a Binary-Tree scale se

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9

Chang-Jian Wang, Chang-Jian Wang, Yong Ding Chang-Jian Wang, and Ye Ji Yong Ding. "An Improved Kernel Correlation Filter Tracking Combined with Mobilenet SSD." 電腦學刊 33, no. 2 (2022): 069–81. http://dx.doi.org/10.53106/199115992022043302006.

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<p>This article mainly solves the problems that exist when using the Kernel Correlation Filter (KCF) for tracking in complex scenarios. To make the algorithm suitable for target tracking under complex conditions such as scale changes, similar interference, and occlusion, a MobileNet SSD (Single Shot Detection) target detection combined with an improved KCF target tracking algorithm is proposed. Firstly, the MobileNet SSD is used to locate the target in the initial frame, and the location is sent to KCF for training. Secondly, aiming at the problem of scale changes, a Binary-Tree scale se

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10

Guo, Xifeng, Turdi Tohti, Mayire Ibrayim, and Askar Hamdulla. "Research on Anti-Occlusion Correlation Filtering Tracking Algorithm Based on Adaptive Scale." Information 13, no. 3 (2022): 131. http://dx.doi.org/10.3390/info13030131.

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Target tracking has always been an important research direction in the field of computer vision. The target tracking method based on correlation filtering has become a research hotspot in the field of target tracking due to its efficiency and robustness. In recent years, a series of new developments have been made in this research. However, traditional correlation filtering algorithms cannot achieve real-time tracking in complex scenes such as illumination changes, target occlusion, motion deformation, and motion blur due to their single characteristics and insufficient background information.

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11

Wang, Zi-Hao, Wen-Jie Chen, and Kai-Yu Qin. "Dynamic Target Tracking and Ingressing of a Small UAV Using Monocular Sensor Based on the Geometric Constraints." Electronics 10, no. 16 (2021): 1931. http://dx.doi.org/10.3390/electronics10161931.

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In many applications of airborne visual techniques for unmanned aerial vehicles (UAVs), lightweight sensors and efficient visual positioning and tracking algorithms are essential in a GNSS-denied environment. Meanwhile, many tasks require the ability of recognition, localization, avoiding, or flying pass through these dynamic obstacles. In this paper, for a small UAV equipped with a lightweight monocular sensor, a single-frame parallel-features positioning method (SPPM) is proposed and verified for a real-time dynamic target tracking and ingressing problem. The solution is featured with system

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12

Liu, Pu, Chun Ping Wang, and Qiang Fu. "An Anti- Occlusion Tracking Algorithm Based on MCD Correlation Matching." Advanced Materials Research 718-720 (July 2013): 2005–10. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.2005.

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In order to improve the stability of target tracking under occlusion conditions，on the basis of researching some target tracking algorithms, this paper presents an algorithm based on MCD correlation matching, which combines multi sub-templates matching and target movement prediction. Besides, for occlusion characteristics, corresponding template matching criterions and updating methods are put forward. Experimental results show that, comparing with the single template method which updating frame by frame, the proposed algorithm has a certain anti-occlusion ability with better stability and con

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13

Zhang, An Qing, Jing Shun Yao, and Hong Quan Chen. "A Parallel PDA Algorithm for Closely-Spaced Targets Tracking in Clutter." Applied Mechanics and Materials 380-384 (August 2013): 1035–38. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1035.

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To reduce the computational complexity of JPDA and resolve closely-spaced targets efficiently, decompose JPDA into parallel PDA algorithms without regarding the correlation of targets. For a target, measurements are all clutter except the ones originated from itself. The PDA algorithm to track every single target with fixed covariance of states. When targets got closed within thick clutter, try to avoid coalescence and reduce complexity of association, maintaining the independence of targets through neglecting the assignment association model of measurement-to-track which used to happen once t

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14

Mitra, Dipayan, Aranee Balachandran, and Ratnasingham Tharmarasa. "Ground Target Tracking Using an Airborne Angle-Only Sensor with Terrain Uncertainty and Sensor Biases." Sensors 22, no. 2 (2022): 509. http://dx.doi.org/10.3390/s22020509.

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Airborne angle-only sensors can be used to track stationary or mobile ground targets. In order to make the problem observable in 3-dimensions (3-D), the height of the target (i.e., the height of the terrain) from the sea-level is needed to be known. In most of the existing works, the terrain height is assumed to be known accurately. However, the terrain height is usually obtained from Digital Terrain Elevation Data (DTED), which has different resolution levels. Ignoring the terrain height uncertainty in a tracking algorithm will lead to a bias in the estimated states. In addition to the terrai

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15

Xue, Renzheng, Ming Liu, and Xiaokun Yu. "Visual Sequence Algorithm for Moving Object Tracking and Detection in Images." Contrast Media & Molecular Imaging 2021 (December 27, 2021): 1–7. http://dx.doi.org/10.1155/2021/3666622.

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Objective. The effects of different algorithms on detecting and tracking moving objects in images based on computer vision technology are studied, and the best algorithm scheme is confirmed. Methods. An automatic moving target detection and tracking algorithm based on the improved frame difference method and mean-shift was proposed to test whether the improved algorithm has improved the detection and tracking effect of moving targets. The algorithm improves the traditional three-frame difference method and introduces a single Gaussian background model to participate in target detection. The im

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16

Wang, Ai Xia, Peng Wu, Jing Jiao Li, and Ai Yun Yan. "A Real Time Tracking Algorithm Basing on Mixed Difference Algorithm." Advanced Materials Research 108-111 (May 2010): 291–96. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.291.

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This paper presented a high real time target tracking algorithm – mixed difference tracking algorithm MDT. In the proposed algorithm, frame difference and background difference algorithms are combined to get the location of the target. With background difference algorithm the shape of the target can be extracted. Due to the affection of the dynamic background, single background difference algorithm can not get the location of the moving target. To solve this issue the frame difference algorithm is used to estimate the location, and then combine the results of the background difference algorith

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17

Yao, Ji, and Deepa Singh. "Motion Tracking and Testing Based on Improved Surendra Algorithm." Open Electrical & Electronic Engineering Journal 8, no. 1 (2014): 620–24. http://dx.doi.org/10.2174/1874129001408010620.

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Recently, due to the gradual mature of the development of computer vision, video-based monitoring and control system has become a classic practice in the field of computer vision. Traffic detection and tracking technology in intelligent video surveillance system is one of the branches of computer vision, which has gradually become a hot and new research field. Through analysis and summary of the existing detection and tracking technology, this study draws a set of target detection and tracking program at the perspective of taking photos with a single fixed camera on the road. The target in the

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18

Li, Liping. "Migration Path Tracking Algorithm of Egret Birds Based on Intelligent Remote Sensing Monitoring." Wireless Communications and Mobile Computing 2022 (August 30, 2022): 1–10. http://dx.doi.org/10.1155/2022/4320297.

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There are billions of migratory birds migrating between breeding grounds and wintering grounds in the world every year. Egret is no exception. During the migration period, they need to travel for a long time and long distances. At present, the protection strategies of egrets and the dynamic mechanism of migration routes are concerned by experts in related fields. Researchers generally explore the above problems by tracking the migration paths of egrets. Most of the existing path tracking algorithms use some classical tracking algorithms, but the tracking accuracy of the classical algorithms is

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19

Sheng, Xueli, Yang Chen, Longxiang Guo, Jingwei Yin, and Xiao Han. "Multitarget Tracking Algorithm Using Multiple GMPHD Filter Data Fusion for Sonar Networks." Sensors 18, no. 10 (2018): 3193. http://dx.doi.org/10.3390/s18103193.

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Multitarget tracking algorithms based on sonar usually run into detection uncertainty, complex channel and more clutters, which cause lower detection probability, single sonar sensors failing to measure when the target is in an acoustic shadow zone, and computational bottlenecks. This paper proposes a novel tracking algorithm based on multisensor data fusion to solve the above problems. Firstly, under more clutters and lower detection probability condition, a Gaussian Mixture Probability Hypothesis Density (GMPHD) filter with computational advantages was used to get local estimations. Secondly

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20

Li, Yingchao, Lianji Ma, Shuai Yang, Qiang Fu, Hongyu Sun, and Chao Wang. "Infrared Image-Enhancement Algorithm for Weak Targets in Complex Backgrounds." Sensors 23, no. 13 (2023): 6215. http://dx.doi.org/10.3390/s23136215.

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Infrared small-target enhancement in complex contexts is one of the key technologies for infrared search and tracking systems. The effect of enhancement directly determines the reliability of the monitoring equipment. To address the problem of the low signal-to-noise ratio of small infrared moving targets in complex backgrounds and the poor effect of traditional enhancement algorithms, an accurate enhancement method for small infrared moving targets based on two-channel information is proposed. For a single frame, a modified curvature filter is used in the A channel to weaken the background wh

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21

Li, Changrui, and Qiuping Peng. "Multitarget Tracking Algorithm in Intelligent Analysis of Football Movement Training Stance." Security and Communication Networks 2022 (August 4, 2022): 1–8. http://dx.doi.org/10.1155/2022/6579066.

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In recent years, with the continuous development of computer technology, deep learning has been widely applied to computer vision tasks and has achieved great success in areas such as visual detection and tracking. On this basis, making deep learning techniques truly accessible to people becomes the next objective. Target detection and tracking in football gesture training is a quite challenging task with great practical and commercial value. In traditional football training methods, target trajectories are often extracted by means of a recording chip carried by the player. However, the cost o

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22

Tian, Weihong. "Research on Curriculum Design Method of Teaching Resource Library based on Deep Learning Technology." Highlights in Science, Engineering and Technology 35 (April 11, 2023): 157–61. http://dx.doi.org/10.54097/hset.v35i.7048.

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In order to improve the ideological understanding of computer majors and establish a correct world outlook, outlook on life and values, the ideological and political goals of computer majors are designed; (1) A new deep learning face recognition algorithm is proposed. Aiming at the limitations of many current methods of artificially designing image description features, this algorithm proposes an unsupervised big data-driven deep image feature learning and representation mechanism. (2) A new idea of single-target tracking algorithm DPL is proposed. Single target tracking is a hot research topi

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23

Liu, Caihong, Mayire Ibrayim, and Askar Hamdulla. "Multi-Feature Single Target Robust Tracking Fused with Particle Filter." Sensors 22, no. 5 (2022): 1879. http://dx.doi.org/10.3390/s22051879.

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Aiming at the problems of target model drift or loss of target tracking caused by serious deformation, occlusion, fast motion, and out of view of the target in long-term moving target tracking in complex scenes, this paper presents a robust multi-feature single-target tracking algorithm based on a particle filter. The algorithm is based on the correlation filtering framework. First, to extract more accurate target appearance features, in addition to the manual features histogram of oriented gradient features and color histogram features, the depth features from the conv3–4, conv4–4 and conv5–4

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Liu, Tingzhuang, Yi Zhu, Kefei Wu, and Fei Yuan. "Underwater Accompanying Robot Based on SSDLite Gesture Recognition." Applied Sciences 12, no. 18 (2022): 9131. http://dx.doi.org/10.3390/app12189131.

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Underwater robots are often used in marine exploration and development to assist divers in underwater tasks. However, the underwater robots on the market have some problems, such as only a single function of object detection or tracking, the use of traditional algorithms with low accuracy and robustness, and the lack of effective interaction with divers. To this end, we designed a type of gesture recognition based on interaction, using person tracking as an auxiliary means for an underwater accompanying robot (UAR). We train and test the SSDLite detection algorithm using the self-labeled under

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25

Fu, Yu, and Xiang Long. "Pedestrian Tracking Based on Improved Particle Filter under Complex Background." Advanced Materials Research 756-759 (September 2013): 4103–9. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.4103.

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When tracking a moving human target,the traditional particle filter algorithm based on color characteristic can't get accurate results in situations like complicated background or frequent brightness change.Due to the problem, this paper put forward a particle filter algorithm based on combination of color characteristics and shape features of the target.Firstly, fusing the above-mentioned two features into the particle filter frame to calculate the particle weights and achieve the human tracking goal through image sequences . The experimental results show that the algorithm can improve the tr

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26

Tan, Li, Xiaokai Huang, Xinyue Lv, Xujie Jiang, and He Liu. "Strong Interference UAV Motion Target Tracking Based on Target Consistency Algorithm." Electronics 12, no. 8 (2023): 1773. http://dx.doi.org/10.3390/electronics12081773.

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In recent years, unmanned aerial vehicle (UAV) image target tracking technology, which obtains motion parameters of moving targets and achieves a behavioral understanding of moving targets by identifying, detecting and tracking moving targets in UAV images, has been widely used in urban safety fields such as accident rescue, traffic monitoring and personnel detection. Due to the problems of complex backgrounds, small scale and a high density of targets, as well as mutual occlusion among targets in UAV images, this leads to inaccurate results of single object tracking (SOT). To solve the proble

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Huang, Yuan, Yifang Shi, and Taek Song. "An Efficient Multi-Path Multitarget Tracking Algorithm for Over-The-Horizon Radar." Sensors 19, no. 6 (2019): 1384. http://dx.doi.org/10.3390/s19061384.

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In target tracking environments using over-the-horizon radar (OTHR), one target may generate multiple detections through different signal propagation paths. Trackers need to jointly handle the uncertainties stemming from both measurement origin and measurement path. Traditional multitarget tracking algorithms suffer from high computational loads in such environments since they need to enumerate all possible joint measurement-to-track assignments considering the measurements paths unless they employ some approximations regarding the measurements and their corresponding paths. In this paper, we

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28

Wu, Wei Hua, Jing Jiang, Xun Feng, and Chong Yang Liu. "Tracking a Maneuvering Target in Clutter by Asynchronous and Heterogeneous Sensors on Single Airborne Platform." Applied Mechanics and Materials 701-702 (December 2014): 154–59. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.154.

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A new algorithm is proposed for tracking a maneuvering target in clutter using heterogeneous sensors, such as active and passive sensors, which are carried on single moving airborne platform and report their observations asynchronously. The algorithm combining interacting multiple model (IMM) with probabilistic data association filter (PDAF) is sequentially implemented to cope with asynchronous reports. In addition, in order to close to practice, the algorithm is based on Earth-centered Earth-fixed (ECEF) coordinate system while it considers the effect of the platform’s attitude. So the algori

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29

Meng, Fanming. "Tennis Video Target Tracking Based on Mobile Network Communication and Machine Learning Algorithm." International Transactions on Electrical Energy Systems 2022 (September 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/7447121.

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The application of information technology has realized the transformation of people’s production and lifestyle and also promoted the development of the sports industry. At present, the application of informatization in the field of sports is becoming more and more powerful. By using the advanced methods and technologies of its information display, this paper aimed to realize the research on the tracking of tennis sports video objects in the mobile network environment. It is helpful to analyze and solve the objectivity problems such as most of the loopholes in the single research and traditiona

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30

YU, YUANLONG, GEORGE K. I. MANN, and RAYMOND G. GOSINE. "A SINGLE-OBJECT TRACKING METHOD FOR ROBOTS USING OBJECT-BASED VISUAL ATTENTION." International Journal of Humanoid Robotics 09, no. 04 (2012): 1250030. http://dx.doi.org/10.1142/s0219843612500302.

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It is a quite challenging problem for robots to track the target in complex environment due to appearance changes of the target and background, large variation of motion, partial and full occlusion, motion of the camera and so on. However, humans are capable to cope with these difficulties by using their cognitive capability, mainly including the visual attention and learning mechanisms. This paper therefore presents a single-object tracking method for robots based on the object-based attention mechanism. This tracking method consists of four modules: pre-attentive segmentation, top-down atten

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31

Chang, Hsien-Tsung, Shu-Wei Liu, and Nilamadhab Mishra. "A tracking and summarization system for online Chinese news topics." Aslib Journal of Information Management 67, no. 6 (2015): 687–99. http://dx.doi.org/10.1108/ajim-10-2014-0147.

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Purpose – The purpose of this paper is to design and implement new tracking and summarization algorithms for Chinese news content. Based on the proposed methods and algorithms, the authors extract the important sentences that are contained in topic stories and list those sentences according to timestamp order to ensure ease of understanding and to visualize multiple news stories on a single screen. Design/methodology/approach – This paper encompasses an investigational approach that implements a new Dynamic Centroid Summarization algorithm in addition to a Term Frequency (TF)-Density algorithm

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Xu, Zheng, Haibo Luo, Bin Hui, and Zheng Chang. "Siamese Tracking from Single Point Initialization." Sensors 19, no. 3 (2019): 514. http://dx.doi.org/10.3390/s19030514.

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Recently, we have been concerned with locating and tracking vehicles in aerial videos. Vehicles in aerial videos usually have small sizes due to use of cameras from a remote distance. However, most of the current methods use a fixed bounding box region as the input of tracking. For the purpose of target locating and tracking in our system, detecting the contour of the target is utilized and can help with improving the accuracy of target tracking, because a shape-adaptive template segmented by object contour contains the most useful information and the least background for object tracking. In t

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Hu, Shuo, Yanan Ge, Jianglong Han, and Xuguang Zhang. "Object Tracking Algorithm Based on Dual Color Feature Fusion with Dimension Reduction." Sensors 19, no. 1 (2018): 73. http://dx.doi.org/10.3390/s19010073.

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Aiming at the problem of poor robustness and the low effectiveness of target tracking in complex scenes by using single color features, an object-tracking algorithm based on dual color feature fusion via dimension reduction is proposed, according to the Correlation Filter (CF)-based tracking framework. First, Color Name (CN) feature and Color Histogram (CH) feature extraction are respectively performed on the input image, and then the template and the candidate region are correlated by the CF-based methods, and the CH response and CN response of the target region are obtained, respectively. A

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Zhang, Lieping, Jinghua Nie, Shenglan Zhang, Yanlin Yu, Yong Liang, and Zuqiong Zhang. "Research on the Particle Filter Single-Station Target Tracking Algorithm Based on Particle Number Optimization." Journal of Electrical and Computer Engineering 2021 (September 4, 2021): 1–8. http://dx.doi.org/10.1155/2021/2838971.

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Given that the tracking accuracy and real-time performance of the particle filter (PF) target tracking algorithm are greatly affected by the number of sampled particles, a PF target tracking algorithm based on particle number optimization under the single-station environment was proposed in this study. First, a single-station target tracking model was established, and the corresponding PF algorithm was designed. Next, a tracking simulation experiment was carried out on the PF target tracking algorithm under different numbers of particles with the root mean square error (RMSE) and filtering tim

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Yao, Guang Yu, and Lu Song. "Design of the Target Tracking Process Based on DM648." Applied Mechanics and Materials 599-601 (August 2014): 904–7. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.904.

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Compared with the traditional vehicle detector, the vehicle detection and tracking based on video image processing and the technique of visual target has fast processing speed, and convenient installation and maintenance, and low cost, wide range of monitoring, can obtain more kinds of traffic parameters, and many other advantages, has become more and more widely used in intelligent transportation system (ITS) in recent years. This paper introduces a method for real-time detection, target tracking in traffic image sequences from a fixed single camera. The System adopts TMS320DM648 as the core

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Liu, Jiaqi, Zhen Wang, Di Cheng, Weidong Chen, and Chang Chen. "Marine Extended Target Tracking for Scanning Radar Data Using Correlation Filter and Bayes Filter Jointly." Remote Sensing 14, no. 23 (2022): 5937. http://dx.doi.org/10.3390/rs14235937.

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As the radar resolution improves, the extended structure of the targets in radar echoes can make a significant contribution to improving tracking performance, hence specific trackers need to be designed for these targets. However, traditional radar target tracking methods are mainly based on the accumulation of the target’s motion information, and the target’s appearance information is ignored. In this paper, a novel tracking algorithm that exploits both the appearance and motion information of a target is proposed to track a single extended target in maritime surveillance scenarios by incorpo

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Li, Jia Qi, Chu Guang Li, and Xiao Lin Tian. "Target Recognition and Tracking Algorithm without Training Samples: Sand-Table Algorithm." Advanced Materials Research 1061-1062 (December 2014): 1177–85. http://dx.doi.org/10.4028/www.scientific.net/amr.1061-1062.1177.

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In this paper, Working on the design of a algorithm :sand-table algorithm.The algorithm could work well in recognizing and tracking an single moving target shot by camera or in a video .The algorithm works simple with low operation cost.May used in tracking different object of many kinds.The algorithm imitate the the process of falling sands to Greatly enhance the tracking ability and tracking accuracy.

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Zhou, Fansen, Yidi Wang, Wei Zheng, Zhao Li, and Xin Wen. "Fast Distributed Multiple-Model Nonlinearity Estimation for Tracking the Non-Cooperative Highly Maneuvering Target." Remote Sensing 14, no. 17 (2022): 4239. http://dx.doi.org/10.3390/rs14174239.

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The newly developed near-space vehicle has the characteristics of high speed and strong maneuverability, being able to perform vertical skips and a wide range of lateral maneuvers. Tracking this kind of target with ground-based radars is difficult because of the limited detection range caused by the curvature of the Earth. Compared with ground-based radars, satellite tracking platforms equipped with Synthetic Aperture Radars (SARs) have a wide detection range, and can keep the targets in custody, making them a promising approach to tracking near-space vehicles continuously. However, this appro

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Elgamoudi, Abulasad, Hamza Benzerrouk, G. Arul Elango, and René Landry. "A Survey for Recent Techniques and Algorithms of Geolocation and Target Tracking in Wireless and Satellite Systems." Applied Sciences 11, no. 13 (2021): 6079. http://dx.doi.org/10.3390/app11136079.

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A single Radio-Frequency Interference (RFI) is a disturbance source of modern wireless systems depending on Global Navigation Satellite Systems (GNSS) and Satellite Communication (SatCom). In particular, significant applications such as aeronautics and satellite communication can be severely affected by intentional and unintentional interference, which are unmitigated. The matter requires finding a radical and effective solution to overcome this problem. The methods used for overcoming the RFI include interference detection, interference classification, interference geolocation, tracking and i

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Zhong, Lehai, Jiao Li, Feifan Zhou, et al. "Integration Between Cascade Region-Based Convolutional Neural Network and Bi-Directional Feature Pyramid Network for Live Object Tracking and Detection." Traitement du Signal 38, no. 4 (2021): 1253–57. http://dx.doi.org/10.18280/ts.380437.

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The current target tracking and detection algorithms often have mistakes and omissions when the target is occluded or small. To overcome the defects, this paper integrates bi-directional feature pyramid network (BiFPN) into cascade region-based convolutional neural network (R-CNN) for live object tracking and detection. Specifically, the BiFPN structure was utilized to connect between scales and fuse weighted features more efficiently, thereby enhancing the network’s feature extraction ability, and improving the detection effect on occluded and small targets. The proposed method, i.e., Cascade

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Wang, Jie Gui. "New Method of Moving Targets Passive Tracking by Single Moving Observer Based on Measurement Data Fusion." Applied Mechanics and Materials 239-240 (December 2012): 942–45. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.942.

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Moving targets passive tracking by single moving observer is a difficult problem. A new location method based on measurement data fusion is proposed in this paper. Firstly, the adaptive passive tracking initiation algorithm is introduced. Secondly, a new data association algorithm is proposed, based on the data fusion of multiple measurements, the decision of synthetic data association is made. Finally, with the help of computer simulations, the proposed algorithms are proven to be correct and effective.

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Xiong, Jiu Liang, Zhuang Zhi Han, and Hong Xu. "Study on Intermittent Target Tracking in Fire-Control Radar Network." Advanced Materials Research 219-220 (March 2011): 187–90. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.187.

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Intermittent target tracking (ITT) method is proposed based on radar network theory to keep the tracking precision while resisting anti-radiation missile effectively. ITT theory is analyzed first. Then, three relevant evaluation indexes and an improved adaptive sampling algorithm are proposed. Under the same condition, this paper simulated three different target tracking methods, i.e., single radar in ITT, single radar in fixed sampling period tracking and tracking method proposed in the paper. Simulation results show the validity of the method proposed in the paper.

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Zhang, Jianming, You Wu, Xiaokang Jin, Feng Li, and Jin Wang. "A Fast Object Tracker Based on Integrated Multiple Features and Dynamic Learning Rate." Mathematical Problems in Engineering 2018 (December 24, 2018): 1–14. http://dx.doi.org/10.1155/2018/5986062.

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Object tracking is a vital topic in computer vision. Although tracking algorithms have gained great development in recent years, its robustness and accuracy still need to be improved. In this paper, to overcome single feature with poor representation ability in a complex image sequence, we put forward a multifeature integration framework, including the gray features, Histogram of Gradient (HOG), color-naming (CN), and Illumination Invariant Features (IIF), which effectively improve the robustness of object tracking. In addition, we propose a model updating strategy and introduce a skewness to

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Li, Jia Qi. "Efficient Moving Target Tracking Algorithm: Design and Implementation of the Sand-Table Tracking Algorithm." Applied Mechanics and Materials 475-476 (December 2013): 1032–39. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.1032.

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Working on the design of a new algorithm :sand_table algorithm.The algorithm could work well in recognizing and tracking an single moving target shot by camera or in a video .The algorithm works simple with low operation cost.May used in tracking different object of many kinds.The algorithm imitate the the process of falling sands to Greatly enhance the tracking ability and tracking accuracy.

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Ban, Li Ying, Yue Hua Han, and Yan Hai Wu. "Target Tracking Based on Improved Camshift and Kalman Filter." Advanced Materials Research 989-994 (July 2014): 3587–90. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3587.

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A tracking algorithm based on improved Camshift and Kalman filter is proposed in this paper to deal with the problems in traditional Camshift algorithm, such as tracking failure under color interference or occlusion. Firstly, the proposed algorithm improves the single color target model and presents a novel target model, which fuses color and motion cues, to enhance the robustness and accuracy of target tracking. And in order to increase the tracking efficiency, the algorithm combines Kalman filter with the improved Camshift algorithm by using Kalman filter to predict the position of the track

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Hu, Ji, and Sai-wai Wong. "Design of efficient single target real-time beam tracking system." Journal of Physics: Conference Series 2245, no. 1 (2022): 012006. http://dx.doi.org/10.1088/1742-6596/2245/1/012006.

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Abstract This paper builds a system for real-time tracking of a single target Radio Frequency (RF) signal source, in which the transmitter uses a low-cost HackRF One software radio transceiver platform, and the receiving antenna array uses two monopole antennas to form a 1×2 receiving array. The receiver uses Xilinx 7-Series development board Zedboard and AD9361 RF transceiver to build a wireless receiving platform to process the received signal. In this RF beam tracking system, it needs to perform Direction of Arrival (DOA) estimation on the calibrated signal, the DOA algorithm plays a crucia

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Lv, Dong Yue, Dong Yan Liu, Zhi Pei Huang, Neng Hai Yu, and Jian Kang Wu. "Video Sequences Foreground Enhancement Using Hidden Markov Model." Advanced Materials Research 989-994 (July 2014): 3872–76. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3872.

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Foreground detection is an important part in video surveillance system. The detection results will significantly affect the performance of tracking, abnormal behavior analysis and other following procedures. Many algorithms have been proposed to improve the detection performance. However, these algorithms simply focus on one single frame, ignoring the relationship among the detection results of one target in successive frames. This paper presents a novel foreground enhancement algorithm using Hidden Markov Model (HMM). In a video sequence, one target in successive frames usually has similar sh

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Zhang, Yuanshi, Minghai Pan, and Qinghua Han. "Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning." Sensors 20, no. 5 (2020): 1371. http://dx.doi.org/10.3390/s20051371.

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The unmanned aerial vehicle (UAV) cluster is gradually attracting more attention, which takes advantage over a traditional single manned platform. Because the size of the UAV platform limits the transmitting power of its own radar, how to reduce the transmitting power while meeting the detection accuracy is necessary. Aim at multiple-target tracking (MTT), a joint radar node selection and power allocation algorithm for radar networks is proposed. The algorithm first uses fuzzy logic reasoning (FLR) to obtain the priority of targets to radars, and designs a radar clustering algorithm based on t

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Xiao, Song, Xian Si Tan, and Hong Wang. "Interacting Multiple Mode Tracking Algorithm Based on Modified Coordinate Turn Model." Applied Mechanics and Materials 610 (August 2014): 534–39. http://dx.doi.org/10.4028/www.scientific.net/amm.610.534.

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The continuing success of near space hypersonic aircraft flight test has become a real threat to China's space attack-defense system, In view of the problem that the single model cannot track such target effectively, an interacting multiple model (IMM) tracking algorithm based on modified cornering model (MCT) was proposed. First the characteristics of near space hypersonic target were analyzed, and then the target real-time angular velocity according to the target motion equation was estimated, finally the near space hypersonic target tracking through the IMM was carried out. The Monte Carlo

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Truong, Xuan Tung. "DEEP LEARNING TECHNIQUE - BASED DRONE DETECTION AND TRACKING." Journal of Military Science and Technology, no. 73 (June 15, 2021): 10–19. http://dx.doi.org/10.54939/1859-1043.j.mst.73.2021.10-19.

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The usage of small drones/UAVs is becoming increasingly important in recent years. Consequently, there is a rising potential of small drones being misused for illegal activities such as terrorism, smuggling of drugs, etc. posing high-security risks. Hence, tracking and surveillance of drones are essential to prevent security breaches. This paper resolves the problem of detecting small drones in surveillance videos using deep learning algorithms. Single Shot Detector (SSD) object detection algorithm and MobileNet-v2 architecture as the backbone were used for our experiments. The pre-trained mod

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