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High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

Journal of Beijing Institute of technology 2024年第2期33卷 111-118页

作者： Yongjia Dou Guangcai Sun 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

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to *** this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present *** concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA ***,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA *** results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

关键词： synthetic aperture direction-of-arrival(DOA)estimation coherent accumulation

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Practical frequency-hopping MIMO joint radar communications:Design and experiment

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Digital Communications and Networks 2024年第6期10卷 1904-1914页

作者： Jiangtao Liu Kai Wu Tao Su J.Andrew Zhang National Key Laboratory of Radar Signal Processing Xidian UniversityXi'anShanxi 710071China Global Big Data Technologies Centre University of Technology SydneyNSW 2007Australia

Joint radar and Communications(JRC)can implement two Radio Frequency(RF)functions using a single of resources,providing significant hardware,power and spectrum savings for wireless systems requiring both ***-Hopping(FH)MIMO radar is a popular candidate for JRC because the achieved communication symbol rate can greatly exceed the radar pulse repetition ***,practical transceiver imperfections can cause many existing theoretical designs to *** this work,we reveal for the first time the non-trivial impact of hardware imperfections on FH-MIMO JRC and model the impact *** also design new waveforms and correspondingly develop a low-complexity algorithm to jointly estimate the hardware imperfections of unsynchronized *** addition,using low-cost software-defined radios and Commercial Off-The-Shelf(COTS)products,we build the first FH-MIMO JRC experimental platform with simultaneous over-the-air radar and communication *** by simulation and experimental results,the proposed designs achieve high performance for both radar and communications.

关键词： Joint radar and communications Frequency-hopping MIMO radar Sampling timing offset Carrier frequency offset Front-end errors Software-defined radio Commercial off-the-shelf

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Joint optimization algorithm based on array optimization and pattern synthesis 4

Joint optimization algorithm based on array optimization and...

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4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Liao, Haiyun Tao, Haihong Zhong, Tiantian Cao, Han Song, Dawei Xidian Universitriy National Laboratory of Radar Signal Processing Xi'an China China Academy of Space Technology National Key Laboratory of Science and Technology on Space Microwave Xi'an China

ISBN: (纸本)9798350394375

By optimizing the weights of each element in the array to control the array pattern, the performance of radar can be improved. In this paper, we study the relationship between the position of the array antenna and the weighted value of the array antenna. Based on the given desired pattern, the position of the array antenna and the weighted value of the array are optimized to realize the pattern synthesis. Since the proposed optimization problem is a non-deterministic polynomial problem, a cyclic algorithm is proposed under non-convex constraints to optimize the coordinates and weights with the least number of array antennas in an approximate given desired pattern. Our numerical experiments shows that the proposed algorithm is universal and can control the level of the mainlobe and sidelobe of the pattern, for example, it is used in the design optimization of the phased array emission pattern of unmanned aerial vehicles. © 2024 IEEE.

关键词： Antenna phased arrays

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Improved SOCP Relaxation for SRI-Unknown Emitter Localization Using a Moving Receiver

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IEEE signal processing Letters 2025年 32卷 2199-2203页

作者： Liu, Sining Yue, Yaxing Zhao, Jiayi Shi, Zhiguo Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China

Employing a single moving receiver for emitter localization offers numerous advantages, including low cost, ease of implementation, and elimination of clock synchronization. A novel localization method is proposed for a stationary emitter with an unknown signal Repetition Interval (SRI). We first construct a localization model based on time-of-arrival, taking into account potential missed detections, and then derive the Cramér-Rao Lower Bound. Given that the established model is non-convex, we reformulate the problem into a convex form and convert it to Second-order Cone Programming (SOCP) format. However, the SOCP formulation encounters convex hull issues, which may hinder far-field localization. To address this challenge, we introduce a penalty term to alleviate the convex hull problem for the first time. Simulation results demonstrate the effectiveness of the proposed approach in comparison to existing methods, and the validity of the penalty term is also confirmed. © 1994-2012 IEEE.

关键词： Location awareness Receivers signal processing algorithms Convex hulls Maximum likelihood estimation Vectors Synchronization Lower bound Iterative methods Costs

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An interference suppression algorithm for cognitive bistatic airborne radars

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Journal of Systems Engineering and Electronics 2022年第3期33卷 585-593页

作者： XIA Deping ZHANG Liang WU Tao HU Wenjun National Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China Nanjing Research Institute of Electronics Technology Nanjing 210039China

Interference suppression is a challenge for radar researchers, especially when mainlobe and sidelobe interference coexist. We present a comprehensive anti-interference approach based on a cognitive bistatic airborne radar. The risk of interception is reduced by lowering the launch energy of the radar transmitting terminal in the direction of interference;main lobe and sidelobe interferences are suppressed via cooperation between the two radars. The interference received by a single radar is extracted from the overall radar signal using multiple signal classification(MUSIC), and the interference is cross-located using two different azimuthal angles. Neural networks allowing good, non-linear nonparametric approximations are used to predict the location of interference, and this information is then used to preset the transmitting notch antenna to reduce the likelihood of interception. To simultaneously suppress mainlobe and sidelobe interferences, a blocking matrix is used to mask mainlobe interference based on azimuthal information, and an adaptive process is used to suppress sidelobe interference. Mainlobe interference is eliminated using the data received by the two radars. Simulation verifies the performance of the model.

关键词： interference suppression cognitive bistatic airborne radar neural network blocking matrix

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Recognition of Micromotion Space Targets at Low SNR Based on Complex-Valued Time Convolutional Attention Denoising Recognition Network

IEEE Transactions on Radar Systems

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IEEE Transactions on radar Systems 2025年 3卷 193-202页

作者： Bai, Xueru Mao, Xuchen Tian, Xudong Zhou, Feng Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Beijing Institute of Astronautical Systems Engineering Beijing100076 China Xidian University School of Aerospace Science and Technology Xi'an710071 China

For a micromotion space target, its narrowband radar cross section (RCS) series reflects the characteristics of target shape and motion. In practical scenarios, however, the RCS series of distant targets with weak scattering coefficients suffers from low signal-to-noise ratio (SNR), and performing separate noise suppression and recognition purely on the amplitude results in degraded recognition performance. To tackle this issue, an end-to-end complex-valued (CV) time convolutional attention denoising recognition network, dubbed as CV-TCANet, is proposed. Specifically, the denoising module captures temporal correlation by the CV attention mechanism and calculates the noise mask for denoising;and the recognition module utilizes the CV temporal convolutional network (CV-TCN) for feature extraction and recognition. In addition, a hybrid loss is designed to realize the integration of denoising and recognition, thus preserving target information while denoising and improving the recognition accuracy. Experimental results have proved that the proposed method could achieve satisfying recognition performance at low SNR. © 2025 IEEE.

关键词： signal to noise ratio

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Masking radar signals with Two Masks Overlapping in Frequency Domain 2

Masking Radar Signals with Two Masks Overlapping in Frequenc...

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

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

ISBN: (纸本)9798331515669

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. © 2024 IEEE.

关键词： radar interference

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Simultaneous Target Detection and Parameters Estimation with FDA-MIMO radar Exploiting Centro-Hermitian Array Manifold

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IEEE signal processing Letters 2025年 32卷 2204-2208页

作者： Lan, Lan Zhu, Jiayun Rosamilia, Massimo Xu, Jingwei Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing China Università degli studi di Napoli Federico II Department of Electrical Engineering and Information Technology Italy

This paper deals with the simultaneous adaptive target detection and parameter estimation utilizing a Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) radar. At the design stage, a linearized model of the received signal is derived, leveraging the centro-Hermitian (persymmetric) structure of the array manifold and considering potential steering vector mismatches related to the actual target parameters. Exploiting this model, the detection problem is formulated and tackled leveraging adaptive detection approaches, resorting to the Persymmetric Generalized Likelihood Ratio (PGLR) and Persymmetric Adaptive Matched Filter (PAMF), respectively. However, they demand the Maximum Likelihood (ML) estimates of target incremental range (i.e., the deviation of the target actual position from the center of the range bin) and angle. Two iterative methods are devised to solve the ML estimation problem. The former is based on Dinkelbach's algorithm, which is capable of achieving the global optimum, whereas the latter is a fast-converging alternative approach relying on the Coordinate Descent (CD) framework. Numerical results highlight the effectiveness of the proposed simultaneous detection and estimation strategies, also in comparison with suitable benchmarks and counterparts. © 1994-2012 IEEE.

关键词： Gradient methods

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A multi-frame track-before-detect algorithm based on root label clustering for multiple targets

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Chinese Journal of Aeronautics 2022年第5期35卷 87-96页

作者： Jiaqi ZHANG Haihong TAO Xiushe ZHANG Chunlei HAN State Key laboratory of Radar Signal Processing Xidian UniversityXi’an 710068China Xi’an Research Institute of Navigation Technology Xi’an 710071China

In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise density increase.A criterion of track extrapolation is used to construct state transition set,root label is marked by state transition set to obtain the distribution information of multiple targets in measurement space,then measurement plots of multi-frame are divided into several clusters,and finally multi-frame track-before-detect algorithm is implemented in each *** computational complexity can be reduced by employing the proposed *** results show that the proposed algorithm can accurately detect multiple targets in close proximity and reduce the number of false tracks.

关键词： Multi-frame track-before-detect Multiple targets detection Root label clustering State transition set Track extrapolation

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Efficient Position Determination Using Low-Rank Matrix Completion 2

Efficient Position Determination Using Low-Rank Matrix Compl...

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

作者： Zhang, Zehui Pu, Wenqiang Zhou, Rui You, Mingyi Wang, Wei Yan, Junkun Shenzhen Research Institute of Big Data Shenzhen China National Key Laboratory of Electromagnetic Space Security Jiaxing China National Key Laboratory of Radar Signal Processing Hangzhou Institute of Technology Xidian University Xi'an China National Key Laboratory of Radar Signal Processing Hangzhou Institute of Technology Xidian University Hangzhou China

ISBN: (纸本)9798331515669

In increasingly complex electromagnetic environments, distributed systems are crucial for passive target localization. These systems, consisting of spatially dispersed sensing nodes, collaboratively enhance the localization of target signals. Particularly in blind localization tasks within low signal-to-noise ratio (SNR) settings, distributed passive localization offers improved positioning performance. Traditional passive localization methods typically follow a two-step process: initially extracting parameters, such as the direction of arrivals (DOA), from raw data, followed by localizing the target. This approach often requires a high SNR. In contrast, Direct Position Determination (DPD) methods directly leverage all the received raw data, thus overcoming the constraints of the two-step process. However, DPD methods involve a time-consuming grid search within the area of interest. To address this challenge, we propose a radiation source localization method that utilizes random sampling. This method capitalizes on the low-rank properties of the grid search matrix used in DPD methods. By integrating random sampling with low-rank matrix completion algorithms, our approach efficiently localizes the radiation source. Simulation results demonstrate that this random sampling-based method significantly reduces computational demands while preserving high localization accuracy. © 2024 IEEE.

关键词： Direction of arrival

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