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

作者： Du, Xiaohe Zhou, Shenghua Bai, Jian Qin, Jingshu Li, Aihua Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (纸本)9798331515669

Traditional radar systems typically use wideband signals but have limited anti-jamming capabilities. Sparse frequency waveforms offer a solution to narrowband interference issues. However, existing sparse frequency waveform design methods often handle the entire signal uniformly, resulting in fixed frequency notch positions and limited waveform flexibility. In this paper, we propose a new method for optimizing sparse frequency waveforms. While maintaining constant waveform pulse width and range resolution, we increase the degree of freedom by extending the length of phase coded signals. Pulse compression is applied to each frequency band component with the objective of minimizing sidelobes, using the minimax algorithm based on sequential quadratic programming (SQP) to obtain optimal phase coded waveforms. Simulation results demonstrate the method's capability to flexibly design sparse frequency waveforms and reduce pulse compression sidelobe levels. © 2024 IEEE.

关键词： Quadratic programming

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Few-Shot Object Detection in SAR images via Gaussian Flow Class-Balanced Differential Aggregation 2

Few-Shot Object Detection in SAR images via Gaussian Flow Cl...

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

作者： Zhao, Po Chen, Jie Zhang, Chaochen Ma, Ke Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electronics and Information Engineering Hefei230601 China

ISBN: (纸本)9798331515669

Currently, few-shot object detection (FSOD) methods for synthetic aperture radar (SAR) images are severely understudied. The high confidentiality and scarcity of SAR data, coupled with the susceptibility of targets in SAR images to significant changes in orientation, make existing models sensitive to variations in novel class examples. This sensitivity leads to challenges in extracting class prototypes and accurately estimating class centers for novel classes. To solve the above issues, we propose a few-shot object detection algorithm for SAR images via Gaussian Flow Class-Balanced Differential Aggregation. Specifically, we first design a class-balanced difference feature aggregation module to solve the problems of difficult class distribution estimation and inaccurate class center estimation of novel classes in SAR images. Second, the contextual information perception module is designed to extract the most representative support features into fine-grained prototypes and aggregate them with the query features using the matching paradigm to solve the imbalance between foreground targets and background in SAR images. Finally, experimental results on MSAR-AIR dataset indicate that our model realizes the best detection properties on SAR images compared to existing models. © 2024 IEEE.

关键词： few-shot learning object detection synthetic aperture radar variational feature learning

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Real-time transmission audio and video data stream gateway platform for monitoring and management 2

Real-time transmission audio and video data stream gateway p...

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2nd International Conference on Electronic information Engineering and Computer Communication, EIECC 2022

作者： Zhao, Hongbo Li, Tong Beijing institute of Graphic Communication Beijing Key Laboratory of Signal and Information Processing China

ISBN: (纸本)9781510663121

Nowadays, with the rapid development of Internet technology and the emergence of converged media, the rapid transmission of news and information and the ways of transmission are increasingly diversified, and the transmission of video information is gradually developing forward and entering the mainstream of society. Video communication has become an integral part of the new era. This paper proposes a conference mode, which is convenient for the video conference terminal to connect to the video conference software, and also convenient for later operation and maintenance. Our video conference terminal uses Polycom's hardware equipment, our software client uses Huawei cloud conference, and our management platform is managed by the intelligent edge platform of the Internet of Things. The conference system, which supports HD real-time video transmission, has lower delay when resharing the screen than the conference system developed by Tencent Conference. This system maintains stable transmission even in the case of serious renetwork packet loss. © 2023 SPIE.

关键词： Image communication systems

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Mainlobe Deceptive Jammer Suppression using Beampattern Synthesis in EPC-MIMO radar 2

Mainlobe Deceptive Jammer Suppression using Beampattern Synt...

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

作者： Zhang, Xiang Lan, Lan Zhu, Shengqi Cui, Lei Chen, Guozhong Liao, Guisheng Dong, Xiaoyang Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Shanghai Institute of Satellite Engineering Shanghai200090 China

ISBN: (纸本)9798331515669

This paper presents a beampattern synthesis method aimed at suppressing mainlobe deceptive jamming signals in Element Pulse Coding-Multiple-Input-Multiple-Output (EPC-MIMO) radar. By applying phase coding in both the spatial and pulse dimensions, EPC-MIMO radar can suppress mainlobe deceptive jammers through data-independent beamforming. However, the performance degeneration occurs due to the existence of Direction of Arrive (DOA) mismatch. Therefore, an Iterative Weight Control (IWC) algorithm is devised by optimizing the weight vector to achieve ideal responses, where constant quadratic constraint and a dynamical power constraint are utilized to broaden the presumed null regions. At the analysis stage, the performance of IWC method in mitigating mainlobe deceptive jamming signals is compared with the state-of-the-arts beampattern synthesis techniques, highlighting the superiorities of the IWC approach. © 2024 IEEE.

关键词： Direction of arrival

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Simultaneous Detection and Estimation with Distributed FDA-MIMO and EPC-MIMO radars 2

Simultaneous Detection and Estimation with Distributed FDA-M...

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

作者： Zhu, Jiayun Zhang, Xiang Lan, Lan Ma, Runlong Cui, Lei Chen, Guozhong Xu, Jingwei Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xian710071 China Shanghai Institute of Satellite Engineering Shanghai200090 China

ISBN: (纸本)9798331515669

This paper deals with simultaneous parameter estimation and target detection in a distributed radar system consisting of Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) and Element-Pulse Coding MIMO (EPC-MIMO) radars. For each local radar station, a binary hypothesis detection problem is formulated with unknown target parameters, and detectors are developed leveraging Generalized Likelihood Ratio Test (GLRT) criterion. Under the hypothesis of target presence, the Coordinate Descent (CD) algorithm is leveraged to estimate the range and angle information of the target. Subsequently, the multiple sets of the local test statistics are fused at the Fusion Center (FC) for the ultimate decision, where the global test statistic can be constructed by taking the logarithm sum of local test statistics. At the analysis stage, the effectiveness of the devised method is evaluated in terms of Root Mean Square Error (RMSE) and Probability of Detection (Pd), where comparisons among different radar frameworks, including the distributed radar composed of traditional phased arrays, monostatic EPC-MIMO, and FDA-MIMO radars are carried out. Numerical results verify the superiorities of the proposed approach for simultaneous target detection and parameter estimation. © 2024 IEEE.

关键词： Mean square error

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Rapidly Generated Mainlobe Deceptive Jammer Suppression via Matrix Decomposition in FDA-MIMO radar 2

Rapidly Generated Mainlobe Deceptive Jammer Suppression via ...

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

作者： Zhang, Yitao Lan, Lan Xu, Jingwei Cui, Lei Chen, Guozhong Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Shanghai Institute of Satellite Engineering Shanghai200090 China

ISBN: (纸本)9798331515669

The main purpose of this paper is rapidly generated mainlobe deceptive jammer suppression in the framework of a frequency diverse array-multiple-input multiple-output (FDA-MIMO) radar. Particularly, an innovative solution based on the two-low-rank matrix decomposition (2-LRMD) model is proposed. At the stage of signal model formulation, the echo is conformed to the aforementioned model, and it can be separated into two low-rank matrices corresponding to the true target and rapidly generated mainlobe deceptive jammers, also called false targets, respectively. Then, we establish an optimization problem so as to solve the 2-LRMD problem via alternating direction method of multipliers (ADMM) algorithm. Moreover, the procedure of residual jammer matrix extraction via truncated singular value decomposition (SVD) is implemented to better recover the signal matrices of true and false targets. Numerical simulation results are presented to attest the effectiveness of our method in mitigating the rapidly generated mainlobe deceptive jammers. © 2024 IEEE.

关键词： Singular value decomposition

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Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

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Tsinghua Science and Technology 2024年第4期29卷 1069-1081页

作者： Shanwen Guan Xinhua Lu Ji Li Rushi Lan Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic TechnologyGuilin 541004China Guilin Huigu Institute of AI Industrial Technology Guilin 541004China School of Information Engineering Nanyang Institute of TechnologyNanyang 473000China

When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

关键词： wideband direction of arrival(DOA)estimation sparse Bayesian learning(SBL) unitary approximate message passing(UAMP)algorithm Dirichlet process(DP)

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An Efficient Transposition Method for Spaceborne SAR Data Based on HBM 2

An Efficient Transposition Method for Spaceborne SAR Data Ba...

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

作者： Li, Yongrui Lv, HuShan Xu, Ming Chen, Liang Yang, Zhu Xie, Yizhuang Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Technology Research Institute Beijing China

ISBN: (纸本)9798331515669

The onboard real-time processing of Spaceborne synthetic aperture radar (SAR) is of great significance for the rapid acquisition of surface information. As a key step of SAR imaging processing, the efficiency of data transposition directly affects the imaging quality and processing speed. In order to solve the problem of traditional double data rate synchronous dynamic random-access memory (DDR SDRAM) limiting the transposition speed, this paper proposes a SAR data transposition method based on high bandwidth memory (HBM). The method makes full use of the high bandwidth and multichannel characteristics of HBM, and significantly improves the transposition speed by optimising the data read/write process, providing a new solution for real-time imaging processing of satellite-borne SAR. © 2024 IEEE.

关键词： Dynamic random access storage

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Multi-target High-resolution DOA Estimation based on Sparse Reconstruction for Frequency Agility radar

Multi-target High-resolution DOA Estimation based on Sparse ...

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IET International radar Conference 2023, IRC 2023

作者： Liu, Ruofan Xu, Danlei Jiu, Bo Fan, Youlin Zhang, Yu Liu, Hongwei National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Information Sensing Xidian University Xi'an710071 China

ISBN: (纸本)9781839539954

Frequency agility (FA) radar can avoid the frequency band of mainlobe jamming through frequency hopping and has excellent anti-jamming performance. However, frequency hopping also leads to the target signal having an irregular steering vector after pulse integration, which will affect the performance of DOA estimation. To solve this problem, this paper proposes a method of multi-target high-resolution DOA estimation in FA radar based on sparse reconstruction. Firstly, sparse reconstruction method is adopted for high resolution range-doppler reconstruction, realizing the distance and velocity estimation. Afterward, for the received array signal, phase compensation is performed based on the distance and velocity of the multi-target. Finally, using the frequency encoding of different pulses in FA signal to construct an angle estimation dictionary, the high resolution DOA information of multi-target can be recovered. Theoretical analysis and simulation experiments have verified the effectiveness of this method. © The Institution of Engineering & Technology 2023.

关键词： Frequency hopping

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A Satellite Data-Driven Coherent Parameters Estimation Method via Hierarchical HGRFT for Distributed Coherent Aperture radar

IEEE Transactions on Radar Systems

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IEEE Transactions on radar Systems 2024年 2卷 791-804页

作者： Li, Pucheng Ding, Zegang Li, Linghao Lv, Linhan Li, Zhe Zhu, Rui Wang, Guanxing Beijing Institute of Technology Radar Research Laboratory School of Information and Electronics Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401331 China

The distributed coherent aperture radar (DCAR) utilizes full coherent processing (FCP). Compared to single radar unit observations, N radar units can achieve an N3 times increase in signal-to-noise ratio (SNR), providing an advantage in observing distant targets. However, its stringent requirements for time and phase of multiple radar units make coherent parameters (CPs) estimation the crucial aspect of FCP. This article introduces a satellite data-driven CPs estimation method via hierarchical and hybrid generalized Radon-Fourier transform (HHGRFT). First, the FCP procedure is outlined, and the signal model with CPs is established. Second, the principles for selecting satellites and observation time in the experimental setup are induced, along with an analysis of the SNR variations during processing. Furthermore, through a hierarchical processing approach using the generalized Radon-Fourier transform (GRFT), interpulse coherence (IPC) processing, interunit-radar coherence (IURC) processing, and inter-subaperture coherent or noncoherent processing are sequentially conducted. The utilization of generalized sharpness (GS) and gradient descent method facilitated CPs estimation, subsequently enhancing the SNR post-coherence processing. Finally, the proposed method has been validated through simulation and successfully applied to a real DCAR system. © 2023 IEEE.

关键词： signal to noise ratio

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