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2025 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Zhang, Jiongge Dong, Hang Tian, Long He, Xiongpeng Sun, Huimin Liu, Yuan Pilot School of Software Engineering Xidian University Xi'an China Key Lab. of Radar Signal Processing Xidian University Xi'an China Electronic Engineering Research Institute Xi'an China Nanyang Technological University Singapore

ISBN: (纸本)9798350368741

Micro-Doppler Analysis (MDA) of rigid-body targets is crucial for various practical downstream tasks such as target imaging and recognition. radar echoes from micro-moving targets typically represent non-stationary signals and are often described using the parameterized Time-Varying Auto Regressive (TVAR) model. Sparse Bayesian Learning (SBL) is commonly employed to estimate time-invariant coefficients, thereby achieving high-resolution micro-Doppler time-frequency distributions. Despite its effectiveness, SBL-based optimization methods often face inefficiency due to the computational burden of inverse operation. To address this challenge and enhance the efficiency of MDA based on TVAR model, we propose a Sparse Bayesian Network (SBN) that unfolds a fast Mean Field SBL (MF) using a deep variational autoencoding framework. This method retains the optimization effectiveness of SBL while incorporating the inference efficiency of Deep Neural Networks (DNNs). Our proposed method demonstrates strong generalization capabilities, performing well on both simulated and measured radar echoes. © 2025 IEEE.

关键词： Micro-Doppler Analysis (MDA) Rigid-body Target Sparse Bayesian Network (SBN)

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radar Jamming Recognition via Cross-Modality Contrast Learning

Radar Jamming Recognition via Cross-Modality Contrast Learni...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Ganggang Dong Zixuan Wang National Key Lab of Radar Signal Processing Xidian University Xi’an China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The discernment of radar jamming signal played an important role for the downstream tasks. Great performance was achieved by the deep learning methods. Yet large amounts of lab.led signals were needed. To solve the problem, a new cross-modality contrast learning method was proposed in this paper. The signal-wise hierarchy, and the image-wise hierarchy were developed to extract the features from IQ data (In-phase & quadrature) and TF-image (Time-frequency). The cross-domain features were then combined. The fused features were delivered to the learning phase. It was composed of the pre-training and the fine-tuning. The unlab.led signals were first employed to optimize the similarity loss to make the positive sample mores similar to the signal than the negative samples. The pre-trained model was then fine-tuned to the recognition task. The proposed method was demonstrated to provide impressive performance by multiple comparative studies.

关键词： Time-frequency analysis radar Speech recognition signal processing radar imaging Feature extraction Multitasking Jamming Speech processing Standards

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Sparse Bayesian Network for Fast Micro-Doppler Analysis

Sparse Bayesian Network for Fast Micro-Doppler Analysis

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Jiongge Zhang Hang Dong Long Tian Xiongpeng He Huimin Sun Yuan Liu Pilot School of Software Engineering Xidian University Key Lab. of Radar Signal Processing Xidian University Pilot School of Software Engineering Xidian University Xi’an China Electronic Engineering Research Institute Xi’an China Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

关键词： Time-frequency analysis Target recognition radar measurements Computational modeling Optimization methods radar radar imaging signal processing Bayes methods Speech processing

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A coordinate-transform based FFBP algorithm for high-resolution spotlight SAR imaging

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Science China(Information Sciences) 2015年第2期58卷 31-41页

作者： YANG ZeMin XING MengDao ZHANG Lei BAO Zheng National Key Lab of Radar Signal Processing Xidian University

This paper proposes a coordinate-transform(CT) implementation for the fast factorized backprojection(FFBP) algorithm(CT-FFBP) to process high-resolution spotlight synthetic aperture radar(SAR)data. Unlike the FFBP utilizing two-dimensional image-domain interpolation for sub-aperture fusion, CT-FFBP finishes the image-projection using CT with the accommodation of chirp-z transform and circular shifting. Without interpolation, CT-FFBP yields enhanced efficiency over the interpolation based FFBP, besides maintaining high precision simultaneously. Both simulation and real-data experiments verifies the efficiency and precision superiorities of the CT-FFBP.

关键词： spotlight synthetic aperture radar(SAR) fast factorized back-projection(FFBP) coordinate-transform(CT)

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HNet: A Loss Rate Robust ISAR Imaging Framework Based on Hypernetwork

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Li, Xiaoyong Liu, Lei Huang, Jiale Li, Lei Bai, Xueru Zhou, Feng Xidian University Hangzhou Institute of Technology Hangzhou311231 China Xidian University Key Laboratory of Electronic Information Countermeasure and Simulation Technology of Ministry of Education Xi'an710071 China Xidian University National Key Lab of Radar Signal Processing Xi'an710071 China Xidian University School of Aerospace Science and Technology Xi'an710071 China

Deep learning has significantly advanced the field of sparse inverse synthetic aperture radar (ISAR) imaging. Nonetheless, current methodologies often face constraints due to their reliance on fixed loss rates and types, which can limit practical applicability and result in elevated computational demands both spatially and temporally, as well as diminished generalizability. In tackle to these challenges, this paper introduces a resilient ISAR imaging architecture grounded in hypernetwork technology capable of accommodating diverse loss rates. Initially, we devise a sparse signal reconstruction technique that functions irrespective of the loss rate or matrix dimensions. Subsequently, a methodology for producing arbitrary loss rates is outlined. Building upon this foundation, we present a hypernetwork framework that harnesses hypernetworks to derive defocus characteristics from range-Doppler (RD) imagery across varying loss rates, subsequently transforming these insights into ideal parameters for the sparse signal reconstruction process. By executing the iterative algorithm with these optimized parameters, we achieve loss rate robust ISAR imaging. Comprehensive evaluations conducted on point simulated data, electromagnetic simulated data and measured data confirm the superiority of our proposed approach in terms of reconstruction accuracy and generalization capabilities. This advancement facilitates reliable ISAR imaging across a spectrum of loss rates. 1965-2011 IEEE.

关键词： radar imaging

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Linear feature detection based on ridgelet

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Science China(Technological Sciences) 2003年第2期46卷 141-152页

作者：侯彪刘芳焦李成 Key Lab for Radar Signal Processing Xidian University

Linear feature detection is very important in image processing. The detection efficiency will directly affect the performance of pattern recognition and pattern classification. Based on the idea of ridgelet, this paper presents a new discrete localized ridgelet transform and a new method for detecting linear feature in anisotropic images. Experimental results prove the efficiency of the proposed method.

关键词： linear feature detection, ridgelet transform, wavelet transform, Radon transform.

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Design of digital synthesis filters for hybrid filter bank A/D converters using semidefinite programming

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Journal of Networks 2014年第5期9卷 1325-1332页

作者： Wang, Wei Zhang, Zi-Jing Key Lab. of Radar Signal Processing Xidian Univ Xi'an 710071 China

Hybrid filter bank (HFB) analog-to-digital systems permit wideband, high frequency conversion. This paper presents mixed norm optimal design of digital synthesis filters of a HFB. The mixed norm is a convex combination of the 2-norm and the Chebyshev norm with a weighting parameter. Robust HFB design method based on worst-case ellipsoidal uncertainty in analog filters errors is also proposed. Both the problems can be solved using semidefinite programming. The proposed mixed norm method allows designers to select the best suitable filters among a family of synthesis filters for specific applications, and the robust design method is more insensitive to analog filters errors than the nominal minimax design. © 2014 ACADEMY PUBLISHER.

关键词： Design

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Space-borne antenna adaptive anti-jamming method based on gradient-genetic algorithm

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Journal of Systems Engineering and Electronics 2007年第3期18卷 469-475页

作者： Tao Haihong Liao Guisheng Yu Jiang National Key Lab. of Radar Signal Processing Xidian Univ. Xi'an 710071 P. R. China

A novel space-borne antenna adaptive anti-jamming method based on the genetic algorithm （GA）, which is combined with gradient-like reproduction operators is presented, to search for the best weight for pattern synthesis in radio frequency （RF）. Combined, the GA＇s the capability of the whole searching is, but not limited by selection of the initial parameter, with the gradient algorithm＇s advantage of fast searching. The proposed method requires a smaller sized initial population and lower computational complexity. Therefore, it is flexible to implement this method in the real-time systems. By using the proposed algorithm, the designer can efficiently control both main-lobe shaping and side-lobe level. Simulation results based on the spot survey data show that the algorithm proposed is efficient and feasible.

关键词： space-borne antenna genetic algorithm (GA) gradient-like anti-jamming pattern synthesis.

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A Novel Induction Algorithm for DM

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Journal of Systems Engineering and Electronics 2001年第4期12卷 91-97页

作者：郑建国刘芳焦李成 Key Lab. of Radar Signal Processing Xidian University Xi'an 710071 P. R. China

DM usually means an efficient knowledge discovery from database, and the immune algorithm is a biological theory-based and global searching algorithm. A novel induction algorithm is proposed here which integrates a power of individual immunity and an evolutionary mechanism of population. This algorithm does not take great care of discovering some classifying information, but unknown knowledge or a predication on higher level rules. Theoretical analysis and simulations both show that this algorithm is prone to the stabilization of a population and the improvement of entire capability, and also keeping a high degree of preciseness during the rule induction.

关键词： Algorithms Computer simulation Data handling Database systems

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Micro-Doppler effect analysis and extraction of the tracked vehicle

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Journal of Computational Information Systems 2014年第3期10卷 1029-1035页

作者： Chen, Guangfeng Zhang, Linrang National Key Lab. of Radar Signal Processing Xidian Univ. Xi'an 710071 China

Micro-Doppler signature produced by micro-motion contains movement and structure information which is useful for radar classification and recognition. In order to recognize the tracked vehicle in ground battle, the motion dynamics and echo models of the scattering point on tracked vehicle are set up. And the micro-Doppler modulation of the scattering point on tracked vehicle is quantitatively analyzed. Furthermore, the smoothed pseudo Winger-Ville distribution method is proposed for extracting micro-Doppler modulation. Finally, simulation results demonstrate the correctness of the theoretic analysis and the validity of the extraction method. © 2014 Binary Information Press.

关键词： Tracked vehicles

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