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Pulsed Active Sonar Using Generalized Sinusoidal Frequency Modulation for High-Speed Underwater target detection and tracking

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IEEE ACCESS 2023年 11卷 143081-143091页

作者： Park, Jinuk Kim, Geunhwan Seok, Jongwon Hong, Jungpyo Changwon Natl Univ Ind Technol Inst Chang Won 51524 South Korea Sejong Univ Dept Ocean Syst Engn Seoul 05006 South Korea Changwon Natl Univ Informat & Commun Engn Chang Won 51524 South Korea

For decades, the soft-kill strategy which detects high-speed underwater targets with passive sonar and attract the targets using decoys has been used. However, recently, the paradigm to respond to the high-speed underwater targets is shifting to a hard-kill method that directly intercepts the targets. Therefore, an active sonar detection and tracking technique is required to estimate the exact location of the target. Existing detection and tracking techniques using active sonar divide pulses either temporally or along the frequency axis, transmitting pulses in various directions within a pulse repetition interval. This division, however, leads to a reduction in the time-bandwidth product, consequently diminishing detection performance. Therefore, this paper proposes a generalized sinusoidal frequency modulation (GSFM)-based pulsed active sonar (PAS). The proposed PAS-GSFM employs short pulses for a quick update of target estimates, but the orthogonality between pulses of GSFM allows pulses to maximize bandwidth, thus high detection performance can be expected. Two types of simulations were performed to verify the performance of the proposed PAS-GSFM. First, the performance comparison with PAS-linear frequency modulation (LFM), and second, the comparison between the proposed method and continuous active sonar (CAS)-GSFM. Through the evaluation, the superiority of the proposed method over PAS-LFM and competitiveness compared to CAS-GSFM were proved.

关键词： High-speed networks High-speed underwater target GSFM pulsed active sonar target detection and tracking

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Low-SNR Infrared Point target detection and tracking via Saliency-Guided Double-Stage Particle Filter

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SENSORS 2022年第7期22卷 2791页

作者： Jia, Liangjie Rao, Peng Zhang, Yuke Su, Yueqi Chen, Xin Chinese Acad Sci Shanghai Inst Tech Phys Shanghai 200083 Peoples R China Chinese Acad Sci Key Lab Intelligent Infrared Percept Shanghai 200083 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Low signal-to-noise ratio (SNR) infrared point target detection and tracking is crucial to study regarding infrared remote sensing. In the low-SNR images, the intensive noise will submerge targets. In this letter, a saliency-guided double-stage particle filter (SGDS-PF) formed by the searching particle filter (PF) and tracking PF is proposed to detect and track targets. Before the searching PF, to suppress noise and enhance targets, the single-frame and multi-frame target accumulation methods are introduced. Besides, the likelihood estimation filter and image block segmentation are proposed to extract the likelihood saliency and obtain proper proposal density. Guided by this proposal density, the searching PF detects potential targets efficiently. Then, with the result of the searching PF, the tracking PF is adopted to track and confirm the potential targets. Finally, the path of the real targets will be output. Compared with the existing methods, the SGDS-PF optimizes the proposal density for low-SNR images. Using a few accurate particles, the searching PF detects potential targets quickly and accurately. In addition, initialized by the searching PF, the tracking PF can keep tracking targets using very few particles even under intensive noise. Furthermore, the parameters have been selected appropriately through experiments. Extensive experimental results show that the SGDS-PF has an outstanding performance in tracking precision, tracking reliability, and time consumption. The SGDS-PF outperforms the other advanced methods.

关键词： infrared point target target detection and tracking particle filter infrared remote sensing

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An array of two periodic leaky-wave antennas with sum and difference beam scanning for application in target detection and tracking

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Frontiers of Information Technology & Electronic Engineering 2023年第4期24卷 567-581页

作者： Mianfeng HUANG Juhua LIU School of Electronics and Information Technology Sun Yat-sen UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen UniversityGuangzhou 510006Chin

An array of two substrate-integrated waveguide(SIW) periodic leaky-wave antennas(LWAs) with sum and difference beam scanning is proposed for application in target detection and tracking. The array is composed of two periodic LWAs with different periods, in which each LWA generates a narrow beam through the n=-1 space harmonic. Due to the two different periods for the two LWAs, two beams with two different directions can be realized, which can be combined into a sum beam when the array is fed in phase or into a difference beam when the array is fed 180?out of phase. The array integrated with 180?hybrid is designed, fabricated, and *** results show that the sum beam can reach a gain up to 15.9 dBi and scan from-33.4?to 20.8?. In the scanning range, the direction of the null in the difference beam is consistent with the direction of the sum beam,with the lowest null depth of-40.8 dB. With the excellent performance, the antenna provides an alternative solution with low complexity and low cost for target detection and tracking.

关键词： Antenna Leaky-wave antenna(LWA) Substrate-integrated waveguide(SIW) Sum and difference beam target detection and tracking

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Robust target detection and tracking Algorithm Based on Roadside Radar and Camera

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SENSORS 2021年第4期21卷 1116-1116页

作者： Bai, Jie Li, Sen Zhang, Han Huang, Libo Wang, Ping Tongji Univ Inst Intelligent Vehicles Sch Automot Studies Shanghai 201804 Peoples R China Tongji Univ Coll Elect Sci & Technol Shanghai 201804 Peoples R China

Intelligent transportation systems (ITSs) play an increasingly important role in traffic management and traffic safety. Smart cameras are the most widely used sensors in ITSs. However, cameras suffer from a reduction in detection and positioning accuracy due to target occlusion and external environmental interference, which has become a bottleneck restricting ITS development. This work designs a stable perception system based on a millimeter-wave radar and camera to address these problems. Radar has better ranging accuracy and weather robustness, which is a better complement to camera perception. Based on an improved Gaussian mixture probability hypothesis density (GM-PHD) filter, we also propose an optimal attribute fusion algorithm for target detection and tracking. The algorithm selects the sensors' optimal measurement attributes to improve the localization accuracy while introducing an adaptive attenuation function and loss tags to ensure the continuity of the target trajectory. The verification experiments of the algorithm and the perception system demonstrate that our scheme can steadily output the classification and high-precision localization information of the target. The proposed framework could guide the design of safer and more efficient ITSs with low costs.

关键词： target detection and tracking sensor fusion roadside radar and camera intelligent transportation system

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Sports Video Motion target detection and tracking Based on Hidden Markov Model 11

Sports Video Motion Target Detection and Tracking Based on H...

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11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Zhou, Li Jiangxi Sci & Technol Normal Univ Nanchang 330013 Jiangxi Peoples R China

ISBN: (纸本)9781728121659

Sports video moving object detection and tracking is a hot topic in computer vision research. The hidden Markov model is applied to the detection and tracking of moving objects in sports video. The acquired student motion is used as input to interact with the virtual scene. Firstly, the virtual and real difference measurement selection algorithm based on statistics is used to select the sports students with strong ability. Then, the classifier confidence method is used to select the students with high confidence level from the sports students who have not been marked, and classify them into the marked sports students to promote the generalization ability of the model. Raise. The experimental results show that this method can effectively assist physical education teaching activities and provide objective and effective data analysis for sports video target detection and tracking.

关键词： Sports Video Motion target detection and tracking Adaptive Learning Hidden Markov Model

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target detection and tracking Analysis of Moving Object Based on PCLFM Simulated Model for Airborne Satellite Communication 6

Target Detection and Tracking Analysis of Moving Object Base...

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IEEE 6th International Conference on Electronics Information and Emergency Communication (ICEIEC)

作者： Anjum, M. R. Yin, Pilei Wang, Haofei Dida, Mussa A. Islamia Univ Bahawalpur UCET Dept Elect Engn Bahawalpur Pakistan Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

ISBN: (纸本)9781509019977

Pulse Compression Linear Frequency Modulation (PCLFM) waveform is widely used in wideband radars such as Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR). But the LFM waveform suffers from range migration, if the target to be detected and it has a high velocity that the pulses cannot be coherently integrated. A novel method based on wideband matched filter is proposed to eliminate the effect of speed. Both theory analysis and simulations shows that the new method can integrate the energy of the echo reflected from the target effectively.

关键词： LFM radar PRT target detection and tracking

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target detection and tracking of moving objects for characterizing landslide displacements from time-lapse terrestrial optical images

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ENGINEERING GEOLOGY 2014年第0期172卷 26-40页

作者： Gance, J. Malet, J. -P. Dewez, T. Travelletti, J. Bur Rech Geol & Minieres F-45060 Orleans France Univ Strasbourg CNRS UM7516 Inst Phys Globe StrasbourgEOST F-67084 Strasbourg France Bur Etud Geol SA BEG CH-1994 Aproz Switzerland

Terrestrial Optical Photogrammetry (TOP) is a low-cost monitoring technique that is commonly used in change detection studies. For landslide monitoring, image correlation techniques are frequently used to generate Digital Surface Models (DSMs) from stereo-pairs or to measure the 2D surface displacement field from single-view time-lapse sequences. Image correlation allows for detecting spatially continuous displacement fields at a sub-pixel precision. The technique, however, has several limitations for assessing displacement because 1) of its sensitiveness to changes in texture, shape and radiometry in the image pile, 2) of the need of spatially regular sampling grids, and 3) of possible high computation time that can impede the processing of large image datasets. To address these limitations, an alternative and complementary approach based on a target detection and tracking (TOT) algorithm is proposed for a rapid calculation of the displacement of targets in image time series. The TDT code, developed as a MATLAB-based tool, is able to track natural or man-made targets. The precision of the TDT code is assessed using several image time series acquired at the Super-Sauze landslide (Southern French Alps) and compared to ground based measurements. The computed relative accuracy is between 10(-3) and 10(-4) (5 cm at a distance of 115 m). Although the TOT approach does not provide spatially continuous information, it provides 1) a quantification of the object displacements at the same order of precision as image correlation (sub-pixel accuracy) and 2) information in regions where image correlation fails because of too large ground displacements. A sensitivity analysis reveals that the major sources of uncertainty are camera movement and/or lens distortion and not the TOT method itself. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Displacement monitoring Time series images Terrestrial optical images Landslide target detection and tracking

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target detection and tracking Based on Spatially Multiplexed and Superposition Imaging

Target Detection and Tracking Based on Spatially Multiplexed...

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6th International Congress on Image and Signal Processing (CISP)

作者： Li, Shaoyi Dong, Minzhou Zhang, Kai Yan, Jie Northwestern Polytech Univ Sch Astronaut Xian 710072 Peoples R China

ISBN: (纸本)9781479927630

Addressing continuous target detection and tracking over a large field of view in surveillance application, a novel method to detect and track target is presented in a wide field of view based on spatially multiplexed and superposition imaging technique. This system architecture is proposed by using the spherical lens array and confocal plane with the character of wide field and compressive sampling. And the method of moving target detection with superposition imaging is studied emphatically. This method models each pixel as a Gaussian mixture model, while the Gaussian distributions are evaluated to determine which are most likely to result from a background process. Accordingly the background and foreground are separated. Also, the method of moving target decoding and tracking is researched, which means that target location is decoded based on a set resulting from classifying target copies according to position and velocity criteria in the superposition space. Finally, the target detection and decoding algorithm are simulated and the results show that this method can perform target detection and tracking over a wide field of view.

关键词： large field of view superposition imaging mixture of Gaussians model target detection and tracking

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target detection and tracking Based on Spatially Multiplexed and Superposition Imaging

Target Detection and Tracking Based on Spatially Multiplexed...

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International Congress on Image and Signal Processing

作者： Shaoyi Li Minzhou Dong Kai Zhang Jie Yan School of Astronautics Northwestern Polytechnical University

ISBN: (纸本)9781479927654

关键词： Large field of view Superposition imaging Mixture of Gaussians model target detection and tracking

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Underwater Formation System Design and Implement for Small Spherical Robots

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IEEE SYSTEMS JOURNAL 2023年第1期17卷 1259-1269页

作者： Shi, Liwei Bao, Pengxiao Guo, Shuxiang Chen, Zhan Zhang, Zhongyin Beijing Inst Technol Key Lab Convergence Med Engn Syst & Healthcare Te Beijing 100081 Peoples R China Beijing Inst Technol Minist Ind & Informat Technol Beijing 100081 Peoples R China Kagawa Univ Fac Engn Takamatsu Kagawa 7600016 Japan

Aiming at the difficulty of communication and positioning of the existing underwater robot system, this article combines the vision system with a closed leader-follower formation structure to realize the underwater formation of three underwater robots. On account of the long-standing tracking requirements during vision-based formation process, an antiloss and redetecting strategy is fused in the proposed detecting and tracking algorithm and the binocular vision system can achieve real-time positioning underwater and calculate the 3-D coordinate so as to complete the follower's follow-up to the leader. An artificial submarine detection experiment and an antiloss redetection experiment are applied to demonstrate the robustness of the algorithm. And the underwater formation experiment is implemented so that the effectiveness of the proposed vision-based formation strategy is proved, which also provides a new solution for expanded formation system and multilevel cooperation.

关键词： Robots target tracking Underwater vehicles Cameras Robot vision systems Robot kinematics Multi-robot systems Antiloss and redetection binocular vision target detection and tracking underwater formation

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