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signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Rui Ma Shenghua Zhou Hui Ma Jingshu Qing Jizhuan Li Aihua Li National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Science and Technology on Millimeter-Wave Laboratory Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Electronic attack (EA) equipment can interfere radar systems by emitting interference signals with the assistant of the electronic support measurement (ESM) equipment. In this case, masking signalss can be designed to deceive ESM equipment and prevent EA equipment from emitting interference. This paper proposes an active anti-interference signal design method for Multiple-input Multiple-output (MIMO) radar. Designed masking signals cover a radar signal in the time domain, but the frequency band of the masking signals in the frequency domain does not completely overlap with the radar signal, making it difficult for an enemy ESM equipment to determine whether the obtained signal is a radar signal or interference masking signals. To reduce the cross correlation sidelobes between radar signals and masking signals, the masking signals are designed with upper and lower frequency bands with an identical center frequency, and then the spectrum of the masking signals can be efficient shifted to achieve the spectrum overlap, therefore, low cross correlation sidelobes can be ensured. Simulation results indicate that the propsoed algorithm can reduce the cross-correlation sidelobe level to the level of −100 dB, and it is also shown that the proposed algorithm is robust to the radar transmission delay.

关键词： Time-frequency analysis Correlation Radar measurements Simulation MIMO radar Noise Radar detection Radar equipment Time-domain analysis signal design

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Target Range Angle And Velocity Estimation Method For FDA-MIMO Radar

Target Range Angle And Velocity Estimation Method For FDA-MI...

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IEEE International Conference on Radar

作者： keyi Wang Guisheng Liao Jingwei Xu Yanhong Xu Qingyun Kan Kaiwei Wang National Key Laboratory of Radar Signal Processing Xidian University Xi’an China The School of Communication and Information Engineering Xi’an University of Science and Technology Xi’an China

ISBN: (数字)9798350362381

ISBN: (纸本)9798350362398

The frequency diverse array multiple-input and multiple-output (FDA-MIMO) radar has been widely applied in parameter estimation due to its additional range information introduced by FDA and increased transmit degrees-of-freedom (DOFs) brought by MIMO. However, the effect of frequency diversity on target Doppler has not been thoroughly investigated and exploited. In this paper, a three-stage search-based method is proposed for target range, angle and velocity estimation. In particular, the velocity ambiguity problem can be solved by exploiting the coupling relationship between the transmit carrier frequency and the target velocity. Furthermore, the multiple parameters estimation performance with respect to the signal-to-noise ratio (SNR) is evaluated. Numerical simulation results have demonstrated the effectiveness of the proposed method.

关键词： Couplings Simulation Estimation Search problems Numerical simulation Frequency diversity Frequency estimation Doppler radar Doppler effect signal to noise ratio

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A Multi-Angle MIMO-SAR Fusion Imaging Method Based on Improved Range Migration Algorithm and Improved Geographic Information Scale Invariant Feature Transform Algorithm

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 13938-13949页

作者： Zhou, Fang Jiao, Zhikuan Shen, Guoqing Xing, Mengdao Gashinova, Marina Hefei University of Technology School of Computer Science and Information Engineering Hefei230009 China University of Birmingham School of Engineering United Kingdom Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China

In order to resolve the conflict between high pulse repetition frequency (PRF) and wide-swath imaging in multi-angle synthetic aperture radar (SAR), a multi-angle imaging model combined with multiple-input multiple-output synthetic aperture radar (MIMO-SAR) is proposed. The model utilizes more freedom in azimuth degrees provided by MIMO-SAR to remove azimuth ambiguity caused by low PRF, and successfully solves that contradiction. At the same time, considering the problem of low utilization of spectrum in multi-angle imaging SAR, an improved range migration algorithm (ImRMA) is proposed, which can effectively increase the utilization of the spectrum for data processing. Finally, an improved method of geographic information-scale invariant feature transform (ImGI-SIFT) is used to achieve the efficiency fusion of multi-angle imaging results. Simulation and real data experiments show that the effectiveness and superiority of the proposed imaging method, and the precision of the proposed fusion method. © 2008-2012 IEEE.

关键词： Data reduction

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Hybrid signal fusion for target detection in distributed PA-MIMO radar systems on moving platforms

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Zhou, Dingsen Yang, Minglei Lian, Hao Greco, Maria Sabrina Gini, Fulvio Xidian University National Key Laboratory of Radar Signal Processing Shaanxi Xi'an710071 China Science and Technology on Underwater Test and Control Laboratory Dalian116013 China University of Pisa Department of Information Engineering Pisa56122 Italy

Distributed phased multiple-input multiple-output (PA-MIMO) radar systems on moving platforms combine the spatial diversity of MIMO radars with the coherent gain of phased-array radars, making them ideal for dynamic environments. However, challenges such as motion-induced channel variability, Doppler shifts, and complex parameter estimation often hinder target detection. Traditional methods like non-coherent fusion (NCF) and coherent fusion (CF) struggle to adapt to such variability, leading to suboptimal performance. In this paper, we propose a hybrid signal fusion (HSF) scheme that integrates joint space-time-phase compensation (JSTPC) with a compressed fusion network. The JSTPC module mitigates motion-induced phase errors and ensures precise alignment of received signals, while the compressed fusion network combines CF and NCF stages, leveraging their respective strengths to adaptively manage channel correlation variability. We also develop a joint parameter estimation algorithm to accurately extract direction of departure, direction of arrival, and Doppler frequency, thereby ensuring precise signal reconstruction and enhancing the detection process by estimating key parameters in real time. Theoretical analyses of detection thresholds and probabilities, derived using moment-matching techniques, further validate the reliability of the proposed scheme. Monte Carlo simulations and theoretical analyses for diverse radar configurations and channel correlation scenarios show that the proposed HSF scheme achieves 2 dB detection gain improvement over NCF. © 2025 IEEE.

关键词： Frequency estimation

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Integrating Conjugate Gradients Into Evolutionary Algorithms for Large-Scale Continuous Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1801-1817页

作者： Ye Tian Haowen Chen Haiping Ma Xingyi Zhang Kay Chen Tan Yaochu Jin the Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China the Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230601China IEEE the Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial IntelligenceAnhui UniversityHefei 230601China the Department of Computing The Hong Kong Polytechnic UniversityHong Kong SARChina the Faculty of Technology Bielefeld UniversityBielefeld 33619Germany

Large-scale multi-objective optimization problems(LSMOPs)pose challenges to existing optimizers since a set of well-converged and diverse solutions should be found in huge search *** evolutionary algorithms are good at solving small-scale multi-objective optimization problems,they are criticized for low efficiency in converging to the optimums of *** contrast,mathematical programming methods offer fast convergence speed on large-scale single-objective optimization problems,but they have difficulties in finding diverse solutions for ***,how to integrate evolutionary algorithms with mathematical programming methods to solve LSMOPs remains *** this paper,a hybrid algorithm is tailored for LSMOPs by coupling differential evolution and a conjugate gradient *** the one hand,conjugate gradients and differential evolution are used to update different decision variables of a set of solutions,where the former drives the solutions to quickly converge towards the Pareto front and the latter promotes the diversity of the solutions to cover the whole Pareto *** the other hand,objective decomposition strategy of evolutionary multi-objective optimization is used to differentiate the conjugate gradients of solutions,and the line search strategy of mathematical programming is used to ensure the higher quality of each offspring than its *** comparison with state-of-the-art evolutionary algorithms,mathematical programming methods,and hybrid algorithms,the proposed algorithm exhibits better convergence and diversity performance on a variety of benchmark and real-world LSMOPs.

关键词： Conjugate gradient differential evolution evolutionary computation large-scale multi-objective optimization mathematical programming

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Research on Spatial Angle Super-Resolution Algorithm Based on Adaptive Layered Sparse

Research on Spatial Angle Super-Resolution Algorithm Based o...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Min Xue Yuexin Gao Zhixin Wu National Key Laboratory of Radar Signal Processing Xidian University Xi'an China School of Aerospace Science and Technology Xidian University Xi'an China

Compressed Sensing (CS) theory is based on the sparsity of signals and involves compressively sampling high-dimensional data to obtain a small number of linear observations that contain the complete information of the signals. By solving an optimization problem, the original signals can be recovered from these compressed linear observations. This paper combines CS theory with the sparse characteristics of targets in the spatial domain and proposes an adaptive layered sparse spatial angle super-resolution algorithm. This algorithm converts the target spatial angle super-resolution into the problem of using orthogonal basis to reconstruct sparse signals. Then, the target spatial angle super-resolution is carried out by using single snapshot data through optimization solution, and the target spatial angle domain is continuously reduced through layered orthogonal matching pursuit (LOMP) solution to complete the target spatial angle reconstruction. The effectiveness and robustness of the algorithm are verified by using the proposed algorithm to process the measured data.

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Suppression of Mainlobe Deceptive Jammers using Multi-Domain Coding

Suppression of Mainlobe Deceptive Jammers using Multi-Domain...

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IET International Radar Conference 2023, IRC 2023

作者： Zhang, Xiang Lan, Lan Liao, Guisheng Zhu, Shengqi Yu, Xianxiang Cui, Guolong National Key Laboratory of Radar Signal Processing Xidian University No.2 South Taibai Road Xi'an710071 China School of Electronic Engineering University of Electronic Science and Technology of China No. 2006 Xi Yuan Da Dao Gao Xin Xi Qu Chengdu611731 China

ISBN: (纸本)9781839539954

This paper deals with the problem of suppressing mainlobe deceptive jammers by using the Multi-Domain Coding (MDC). At the design stage, by coding in the spatial, slow-time and fast-time domains, the MDC radar is capable of separating the transmitted signals from various transmit elements and discriminating the true target from the mainlobe jammers in the joint transmit-receive spatial frequency domain. Furthermore, the mainlobe jammers can be eliminated by nulling at the equivalent transmit beampattern via an appropriate coding coefficient. Simulation results corroborate the effectiveness of the proposed MDC scheme for the mainlobe deceptive jammer suppression. © The Institution of Engineering & technology 2023.

关键词： Frequency domain analysis

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A Symbol Rate Estimation Scheme for Non-Cooperative Communication 7

A Symbol Rate Estimation Scheme for Non-Cooperative Communic...

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7th International Conference on Computer and Communications, ICCC 2021

作者： Lu, Jian Xu, Wenbo Wang, Siye Qi, Huiying Li, Yabin Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Beijing China National Key Laboratory of Science and Technology On Blind Signal Processing Shanghai China

ISBN: (纸本)9781665409506

In non-cooperative communication, symbol rate estimation is a prerequisite for signal demodulation. However, it is particularly difficult to estimate the symbol rate in the scenario with unknown modulation type and root cosine roll-off shaping. In this paper, an estimator without the requirement of communication parameters is proposed. First, the signal is recognized as constant envelope or non-constant envelope signal by square spectrum. Then, for the former, the symbol rate estimation is based on wavelet transform;for the latter, an envelope velocity strategy is adopted. In the proposed scheme, we elaborate some design details, including resampling factor, extraction of discrete spectral lines in the squared spectrum, selection of wavelet transform scale, and compensation of frequency deviation. We further propose a low-complexity implementation to meet the requirements for real-time capability and accuracy. Simulation results show that our proposed scheme is effective and accurate. © 2021 IEEE.

关键词： Wavelet transforms

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On the Structure Property of PCR’s Adjacency Graph with a Prime Order and Its Application of Constructing M-Sequences 16th

On the Structure Property of PCR’s Adjacency Graph with a P...

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16th International Conference on Information Security and Cryptology, Inscrypt 2020

作者： Zhou, Congwei Guan, Jie Hu, Bin He, Kuan PLA SSF Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9783030718510

In this paper we find a deterministic structure respecting the adjacency graph of a pure circulating shift register (PCR) with a prime order, and give a theoretical method for constructing all floor weight class of M-sequences. As a special case of this method, we calculate a lower bound of the number of floor weight class of M-sequences and give their corresponding feedback functions. © 2021, Springer Nature Switzerland AG.

关键词： Shift registers

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Multi-objective Deployment of WSNs in Underground Sheltered Space 19th

Multi-objective Deployment of WSNs in Underground Sheltere...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wan, Liangtian Wang, Caiyun Sun, Lu Chen, Boyu Zheng, Jibin Wang, Xianpeng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China National Laboratory of Radar Signal Processing Xidian University Xi’an710071 China State Key Laboratory of Marine Resource Utilization in South China Sea and School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9783031651250

Given the increasing population, the underground spaces are widely used. The existing research on wireless sensor networks (WSNs) development has mainly focused on overground space;also, the existing work was based on an ideal deployment environment and simple sensor behaviour. As a consequence, they do not satisfy requirements for practical 3D environment. The 3D wireless sensor networks (WSNs) deployment has new difficulties in the underground space. The signal transmission is impacted by obstacles in the underground space. Thus, we propose a geometry-based 3D signal propagation model to calculate the signal path loss caused by obstacles. Then, taking both coverage and connectivity into account, we transform the WSNs deployment problem into a multi-objective optimization problem (MOP). Finally, we compare some state-of-the-art multi-objective evolutionary algorithms (MOEAs) for the WSNs deployment problem in underground sheltered space. By the experimental results, we optimize the multiobjective deployment problem of the WSNs in the underground sheltered space. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Wireless sensor networks

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