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IET International radar Conference 2023, IRC 2023

作者： Guo, Huancheng Wang, Zhibin Lou, JiaHan Liu, Lei Tang, Fanyi Li, Xuemao Zhang, Qi Li, Zhenfang Zhang, Qingjun National Key Laboratory of Radar Signal Processing Xidian University Xi'an China Country Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China

ISBN: (纸本)9781839539954

Multi-static ATI SAR has significant potential for measuring sea surface velocity vectors. The system comprises one signal-transmitting satellite and two ATI signal-receiving satellites, with a substantial baseline between the receiving satellites and the transmitting satellite. This paper analyzes the accuracy of measuring sea surface velocity vectors using a multi-static spaceborne ATI SAR system, encompassing both velocity and direction measurements. To begin, we revisit the principles of sea surface velocity measurement based on the interferometric SAR's observation geometry to identify potential sources of error in the inversion of the sea surface current field. Subsequently, we derive formulas to quantify the impact of two types of errors: random errors and systematic errors, on the accuracy of vector inversion. Finally, we elucidate the satellite system requirements for multi-static ATI systems by utilizing a set of system parameters. © The Institution of Engineering & technology 2023.

关键词： Systematic errors

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Target Estimation with Angle-Only Observations of Distributed Passive radar Networks 2

Target Estimation with Angle-Only Observations of Distribute...

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2nd IEEE International Conference on signal, Information and Data processing, ICSIDP 2024

作者： Dou, Fabing Wang, Linhai Zhou, Shenghua Zhang, Mengchen Chen, Yidi Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Academy of Space Information Systems Xi'an710199 China China Academy of Launch Vehicle Technology Beijing100076 China

ISBN: (纸本)9798331515669

Passive radars that rely on angle-only measurements cannot obtain the distance between radars and targets. To obtain position estimates of targets, passive radars can be connected to a central processor through communication links. Therefore, fusion algorithms are required to combine observations from distributed passive radars. For the scenario where all radars and targets are moving, most existed fusion algorithms use filtering methods to estimate the velocity and position of moving targets. In fact, most filtering algorithms have some limitations which will limit the algorithm's effectiveness to a large extent. In this paper, two fusion algorithms are proposed for the central processor. The first algorithm, known as the gross least squares (GLS), employs all observations from passive radars to implement moving target estimation, and thus needs significant computation at the central processor. The second algorithm, termed as the recursive least squares (RLS), iteratively optimizes the velocity and position of moving target. Exploiting the continuity of target motion, current target position and velocity estimates are used as initial values in the next moment. With good initial values, the number of iterations decreases and thus the computational cost is reduced at the central processor. Numerical results show that both algorithms benefit from more observations. The GLS algorithm provides more accurate position and velocity estimates of the target but requires substantial computation cost. The RLS algorithm may suffer a slight performance loss but offers a lower computation cost. The results demonstrate the trade-off between accuracy and computational cost, providing useful insights for practical applications. © 2024 IEEE.

关键词： Iterative methods

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Synthetic Aperture Positioning: A Review

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Journal of Beijing Institute of technology 2024年第2期33卷 89-102页

作者： Guangcai Sun Wenlong Dong Yuqi Wang Mengdao Xing National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China School of Communication and Information Engineering Xi’an University of Science and TechnologyXi’an 710054China National Key Laboratory of Radar Signal Processing and the Academy of Advanced Interdisciplinary Research DepartmentXidian UniversityXi’an 710071China

Obtaining precise position of interested emitters passively has wide applications in both civilian and military *** from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been *** method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted *** SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise *** paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope ***,the possible future outlook of SAP is considered.

关键词： passive localization synthetic aperture positioning coherent processing

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Performance Analysis of the Space-time Adaptive processing for Distributed Space-borne Multiple-input Multiple-output radar 4

Performance Analysis of the Space-time Adaptive Processing f...

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4th International Conference on signal processing and Computer science, SPCS 2023

作者： Yang, Zhiwei Wu, Xiangyu Li, Xianghai Jiang, Di Wu, Taisheng National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China

ISBN: (纸本)9781510672505

Space-time adaptive processing (STAP) has been extended to the distributed space-borne multiple-input multiple-output (MIMO) radar system to improve the detection performance. Nevertheless, the transmitting waveforms are not completely orthogonal to each other, resulting in the STAP performance deterioration. In this paper, we established a novel STAP performance analysis model to reveal the influence mechanism of waveform properties. Firstly, the signal model of distributed space-borne radar with hybrid baseline and yaw angle was presented. Then, we derived the characteristic of the clutter covariance matrix for post-Doppler STAP, considering the effect of waveform periodic auto-correlation and cross-correlation sidelobe. Finally, the numerical simulation results, based on indicators of clutter eigenvalue spectrum and output signal-to-noise ratio loss, demonstrated the accuracy of the proposed analysis model. The aforementioned results provide important basis for the design of distributed space-borne MIMO radar system. © 2023 SPIE.

关键词： Space time adaptive processing

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Weak Change Detection of Wide field Foggy Video Image 24

Weak Change Detection of Wide field Foggy Video Image

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4th International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Li, Wen Jia, Zhenhong Song, Sensen Huang, Xiaohui Wang, Jiajia Zhou, Gang Shi, Fei School of Computer Science and Technology Xinjiang University Urumqi Xinjiang China Key Laboratory of Signal Detection and Processing Xinjiang University Urumqi Xinjiang China

ISBN: (纸本)9798400710247

Hawk-eye devices are often used in surveillance and security, and the video images collected by them have a wide field of view. Under foggy conditions, the video images captured by eagle-eye surveillance have low contrast and details are easily lost. In order to solve these problems, this paper proposes a change detection algorithm for foggy wide field video images based on the Discrete Wavelet Transform (DWT) image fusion and FCM clustering algorithm. Firstly, the improved neighborhood ratio operator and the most value mean pixel ratio operator are used to generate the disparity map, and then the DWT is used to fuse the disparity map, and after obtaining the fused disparity map, the soft threshold function and the FCM clustering algorithm are used to carry out the coarse classification and fine classification respectively, and obtain the final change detection result map. © 2024 Copyright held by the owner/author(s).

关键词： Discrete wavelet transforms

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Dark area recognition algorithm for SAR images based on superpixel statistical features

Dark area recognition algorithm for SAR images based on supe...

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2024 Advanced Fiber Laser Conference, AFL 2024

作者： Liu, Peng Liu, Yanyang Li, Xuemao Dong, Xuezhi Xiao, Qian Li, Zhenfang National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Shanghai Institute of Satellite Engineering Shanghai200090 China Aerospace Stellar Technology Co. Ltd. Beijing100095 China

ISBN: (数字)9781510688889

ISBN: (纸本)9781510688872

The dark areas in SAR images are primarily low backscatter regions dominated by noise signals, characterized by significant texture, low echo energy, and large phase interference errors in the echo signals. Accurately identifying these dark regions is crucial for high-precision SAR image target detection and classification, SAR cross-radiometric calibration of satellite constellations, SAR image filtering, and the generation of digital surface models based on SAR technology. This paper proposes a dark region recognition algorithm for SAR images based on superpixel statistical features(SSF). The algorithm constructs a bimodal distribution curve using the statistical features of superpixels and searches for the region with the minimum amplitude proportion within the bimodal distribution, which serves as a constraint to ensure that the OTSU thresholding method converges to the global optimal solution. This approach addresses the issue of inaccurate threshold detection in traditional algorithms, significantly improving the accuracy of dark region detection in SAR images. The detection results can further be used to identify low backscatter areas, such as shadows, water bodies, and asphalt roads. © 2025 SPIE.

关键词： Superpixels

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CHANNEL-WISE INFLUENCE: ESTIMATING DATA INFLUENCE FOR MULTIVARIATE TIME SERIES

arXiv

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arXiv 2024年

作者： Wang, Muyao Xie, Zeke Chen, Bo National Laboratory of Radar Signal Processing Xidian University China The Hong Kong University of Science and Technology Guangzhou China

The influence function, a technique from robust statistics, measures the impact on model parameters or related functions when training data is removed or modified. This effective and valuable post-hoc method allows for studying the interpretability of machine learning models without requiring costly model retraining. It would provide extensions like increasing model performance, improving model generalization, and offering interpretability. Recently, Multivariate Time Series (MTS) analysis has become an important yet challenging task, attracting significant attention. However, there is no preceding research on the influence functions of MTS to shed light on the effects of modifying the channel of training MTS. Given that each channel in an MTS plays a crucial role in its analysis, it is essential to characterize the influence of different channels. To fill this gap, we propose a channel-wise influence function, which is the first method that can estimate the influence of different channels in MTS, utilizing a first-order gradient approximation that leverages the more informative average gradient of the data set. Additionally, we demonstrate how this influence function can be used to estimate the impact of a channel in MTS. Finally, we validated the accuracy and effectiveness of our influence estimation function in critical MTS analysis tasks, such as MTS anomaly detection and MTS forecasting. According to abundant experiments on real-world dataset, the original influence function performs worse than our method and even fail for the channel pruning problem, which demonstrate the superiority and necessity of channel-wise influence function in MTS analysis tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Time series analysis

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A Novel Reduced-Dimension Clutter Suppression Method Based on Tensor Decomposition 4

A Novel Reduced-Dimension Clutter Suppression Method Based o...

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4th International Conference on signal processing and Computer science, SPCS 2023

作者： Yang, Zhiwei Xu, Yufeng Li, Jingya Mao, Yongfei Kuang, Hui National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing100094 China

ISBN: (纸本)9781510672505

Reduced-dimension (RD) space-time adaptive processing (STAP) technique has achieved good clutter suppression performance in real data processing. However, the traditional F$A method suffers from performance degradation in presence of clutter fluctuation. Extended F$A method (E-F$A) is an effective approach to improve the performance in such a clutter environment, but it requires high computational complexity and sample support. In this paper, a novel reduced-dimension method for E-F$A clutter suppression is proposed. Firstly, we extract characteristics of clutter by tensor Tucker decomposition, which can preserve the structural characteristics of the clutter in the spatial and Doppler domains. Then, we select eigenvectors to construct the RD matrix based on principle components (PC) analysis. Finally, RD data is obtained by multiplying the RD matrix with the original data, and the weight vector for clutter suppression can be calculated. The experimental results based on real measured data validate the effectiveness of the proposed method. © 2023 SPIE.

关键词： Space time adaptive processing

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Adaptive Target Birth Intensity Based on Scene Optimization 5

Adaptive Target Birth Intensity Based on Scene Optimization

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5th International Conference on Intelligent Control, Measurement and signal processing, ICMSP 2023

作者： Zhao, Jiuchao Zhan, Ronghui Cao, Jingmin Peng, Huafeng College of Electronic Science and Engineering National University of Defense Technology Changsha China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9798350336030

The effective multi-target detection and tracking has always been a research hotspot in the field of radar, and there are many factors that affect the performance of the algorithm for multi-target tracking. Aiming at the target birth issue, this paper proposes an adaptive target birth intensity method based on scene optimization. This method is mainly applied to the radar long-term continuous monitoring scenario, and the monitoring area is divided into the target-birth consideration area and non-target-birth consideration area by some prior information of the monitoring area and the target status. And then the target birth process in the target-birth consideration area is strengthened, while the clutter interference from the non-target-birth consideration area is eliminated, so as to improve the target tracking performance and processing efficiency. Finally, the effectiveness and robustness of the proposed algorithm are verified by simulation experiments and analysis. © 2023 IEEE.

关键词： Target tracking

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A Novel Parameter Estimation and Integration Framework for Range Ambiguous Space High-Speed Maneuvering Target 4

A Novel Parameter Estimation and Integration Framework for R...

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4th International Conference on signal processing and Computer science, SPCS 2023

作者： Xu, Xingyuan Yang, Zhiwei Li, Xianghai Yu, Haoran Mao, Yongfei Jiang, Di National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing100094 China

ISBN: (纸本)9781510672505

For the long-range and high-speed maneuvering space target detection, its performance is constrained by two challenges, the coherent integration loss due to Range migration and Doppler frequency spread, the contradiction between Range Ambiguity, and Doppler bandwidth ambiguity. This paper proposed a novel parameter estimation and integration method to solve the above two issues. Firstly, the waveform diversity technique is used to solve the range ambiguity problem. Then a matched filter bank for high-speed targets that can calculate the range ambiguity number is designed. Next, coherent integration is successfully achieved by estimating the target motion parameters and compensating for the echo signal. Finally, a two-step search strategy is proposed to improve the parameter estimation process, numerical experiments have validated that the complexity of the algorithm is reduced while ensuring the accuracy of the parameter estimation. © 2023 SPIE.

关键词： Parameter estimation

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