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4th International Conference on Computer science and Application Engineering, CSAE 2020

作者： Hu, Hongbo Sun, Zhengbo Yang, Yuxiang Deng, Bing Information Engineering University Science and Technology on Blind Signal Processing Laboratory Zhengzhou China Science and Technology on Blind Signal Processing Laboratory Chengdu China

ISBN: (纸本)9781450377720

To solve the problem of insufficient number of check equation in the reconstruction of high order interfered scrambling code sequence, a reconstruction algorithm is proposed. Firstly, the check relationships based on the scrambling code generator polynomial are used to construct the factor graph, and the factor graph iteration method is used to estimate the scrambling code sequences. Secondly, the check relationship inspection method is used to evaluate the compatibility between the iterative estimation sequences and the generator polynomial, and select the best continuous codeword to restore the scrambler initial state. Finally, the optimal reconstruction sequence is selected from the scrambling code for initial state recovery according to the principle of minimum Hamming distance. Simulation results show that the algorithm can effectively solve the problem of reconstruction by using a limited number of check equations. © 2020 ACM.

关键词： Iterative methods

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Blind source separation with unknown and dynamically changing number of source signals

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science in China(Series F) 2006年第5期49卷 627-638页

作者： YE Jimin ZHANG Xianda ZHU Xiaolong Key Laboratory for Radar Signal Processing Xidian University Xi'an 710071 China Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China

The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual information is still the contrast function for BSS if the mixing matrix is of full column rank. The mutual information reaches its minimum at the separation points, where the random outputs of the BSS system are the scaled and permuted source signals, while the others are zero outputs. Using the property that the transpose of the mixing matrix and a matrix composed by m observed signals have the indentical null space with probability one, a practical method, which can detect the unknown number of source signals n, ulteriorly traces the dynamical change of the sources number with a few of data, is proposed. The effectiveness of the proposed theorey and the developed novel algorithm is verified by adaptive BSS simulations with unknown and dynamically changing number of source signals.

关键词： blind source separation independent component analysis natural gradient mutual information contrast function neural networks.

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A Modified Information Embedding Scheme for the Integrated System of radar and Communication

A Modified Information Embedding Scheme for the Integrated S...

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2019 IEEE International Conference on signal, Information and Data processing, ICSIDP 2019

作者： Wu, Wenhua Cao, Yunhe Liu, Yutao National Laboratory of Radar Signal Processing Xidian University Xi'an China Science and Technology on Communication Networks Laboratory Shi jia zhuang China

ISBN: (纸本)9781728123455

This paper has proposed a modified information embedding scheme for the integrated system of radar and communication without influence on the mainlobe. Exploiting the waveform diversity of multiple-input multiple-output (MIMO) radar, the beamforming weight vectors are designed for constellation mapping to increase the data rate. Simulation results are presented to demonstrate the theoretical analysis. © 2019 IEEE.

关键词： Beamforming

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Target Spatial-Frequency Scattering Response Sparse Approximation using Multi-static radar Observations

Target Spatial-Frequency Scattering Response Sparse Approxim...

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2021 CIE International Conference on radar, radar 2021

作者： Zhou, Shenghua Cai, Jiewen Huo, Chaoying Ma, Hui Peng, Xiaojun Xidian University National Laboratory of Radar Signal Processing Xi'an710071 China Science and Technology on Electromagnetic Scattering Laboratory Beijing100854 China

ISBN: (纸本)9781665498142

Inverse synthetic aperture radar (ISAR) can form an image of the target with a sequence of wideband coherent observations, but it is generally difficult to generalize ISAR images from other directions. In this paper, with observations of a noncoherent multistatic radar system to the same target, we study how to approximate the target spatial-frequency joint response by the scattering centers target model. We optimize the scattering intensities of the scatterers such that the target response at selected frequency ticks and spatial directions, under sparse constraints to select proper number of scattering centers. Numerical results with a 3D plane model indicates that the target response can be approximated by a few scattering centers in a good accuracy, even for spatial directions in which the target is not probed before. © 2021 IEEE.

关键词： frequency scattering diversity MIMO radar radar cross section radar target 3D imaging scattering centers target model spatial scattering diversity

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Grading learning for blind source separation

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science in China(Series F) 2003年第1期46卷 31-44页

作者：张贤达朱孝龙保铮 Key Laboratory for Radar Signal Processing Xidian University Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China

By generalizing the learning rate parameter to a learning rate matrix, this paper proposes a grading learning algorithm for blind source separation. The whole learning process is divided into three stages: initial stage, capturing stage and tracking stage. In different stages, different learning rates are used for each output component, which is determined by its dependency on other output components. It is shown that the grading learning algorithm is equivariant and can keep the separating matrix from becoming singular. Simulations show that the proposed algorithm can achieve faster convergence, better steady-state performance and higher numerical robustness, as compared with the existing algorithms using fixed, time-descending and adaptive learning rates.

关键词： blind source separation independent component analysis neural computation adaptive learning.

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An advanced STAP implementation for surveillance radar systems

An advanced STAP implementation for surveillance radar syste...

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11th IEEE Workshop on Statistical signal processing (SSP 2001)

作者： Fabrizio, GA Turley, MD Radar Signal Processing Group Surveillance Systems Division Defence Science and Technology Org. Canberra ACT Australia

ISBN: (纸本)0780370112

Space-time adaptive processing (STAP) has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe and dynamic interference which generally includes clutter as well as jamming. While the theory of optimum STAP is well known, practical issues such as interference heterogeneity, finite sample support, mismatched signal models and computational load need to be overcome when it comes to implementing STAP in operational radar systems. This paper proposes an advanced STAP formulation which addresses important issues facing practical implementation and then tailors this general formulation for the case of interference rejection in over-the-horizon (OTH) radar to experimentally evaluate its target detection and localisation performance.

关键词： Surveillance radar

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A Modified BGM-PHD Filter with Unknown Detection Probability 6

A Modified BGM-PHD Filter with Unknown Detection Probability

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6th International Conference on Information Communication and signal processing, ICICSP 2023

作者： Wei, Jingxin Luo, Feng Qi, Jiawei Ruan, Luyao Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Hangzhou Institute of Technology Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Hangzhou Institute of Technology Xidian University Hangzhou China

ISBN: (纸本)9798350339994

The standard Probability Hypothesis Density (PHD) filter requires manually presetting the detection probability before tracking. In addition, incorrect settings would lead to deterioration in filter performance. Beta GM-PHD filter introduces the unknown detection probability modeled by Beta distribution into the Bayes recursion to enhance the robustness under the lack of detection model parameters. However, the limitation that biases the target number and detection probability estimations significantly affects the application of the Beta GM-PHD filter. In this paper, the mechanism of the estimation biases is analyzed and a simple but effective modification is presented. Simulation results demonstrate that the modified filter provides more accurate detection probability and target state estimates in unknown and space-varying detection probability scenarios. © 2023 IEEE.

关键词： multi-target tracking parameter estimation PHD filter unknown detection probability

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An Electromagnetic Parameter Estimation Method for Microwave Photonic signal Based on PSO

An Electromagnetic Parameter Estimation Method for Microwave...

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2021 CIE International Conference on radar, radar 2021

作者： Xie, Yiyuan Gao, Yuexin Xing, Mengdao Xidian University National Laboratory of Radar Signal Processing Xi'an China School of Aerospace Science and Technology Xidian University Xi'an China

ISBN: (纸本)9781665498142

Microwave photonics radar generates cross-band signals, which provides a basis for precise electromagnetic characteristics description and accurate identification of targets. As a result, a corresponding electromagnetic model parameter extraction method is urgently required under the cross-band and wide-angle condition. This paper proposes a parameter estimation method based on an improved Particle Swarm Optimization (PSO). The representation dictionary without range-azimuth coupling of scattering behavior for the data processed by PFA is firstly formed based on the attributed scattering center (ASC) model. Based on the proposed scattering behavior dictionary, the improved PSO algorithm and the CLEAN algorithm are implemented to estimate the electromagnetic parameters of each scattering center. Further, the simulated annealing (SA) algorithm is introduced to improve the method's capacity to find the global optimum. Finally, the structure of each scattering center can be identified according to the parameter estimation results. The processing results of simulation data verify the effectiveness of the algorithm. Compared with traditional algorithms, the proposed algorithm is insensitive to the initialization value and does not require image segmentation, which reduces the complexity of computation. © 2021 IEEE.

关键词： Attributed scattering center Cross-band radar imaging Parameter estimation Particle Swarm Algorithm Polar Format Algorithm

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Research on Sliding Spotlight and TOPS SAR Variable PRF Imaging technology

Research on Sliding Spotlight and TOPS SAR Variable PRF Imag...

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2021 CIE International Conference on radar, radar 2021

作者： Gong, Songtao Wang, Zhi Sun, Guang-Cai Jun, Yang Xing, Mengdao Xidian University National Laboratory of Radar Signal Processing Xi'an China College of Geomatics Xi'An University of Science and Technology Xi'an China

ISBN: (纸本)9781665498142

Because the traditional single-based spaceborne synthetic aperture radar (SAR) cannot receive signals while transmitting signals, there is a defect that high azimuth resolution and wide swath imaging cannot be achieved at the same time. In response to this problem, researchers have proposed the use of variable pulse repetition frequency (PRF) technology to achieve high-resolution wide swath imaging. However, the echo data of the variable PRF SAR will have the problem of sampling at different intervals in the azimuth direction. Using traditional frequency domain algorithms to process the data will cause serious deterioration of the imaging quality, or even imaging;the time domain algorithm can directly focus on the data of the variable PRF, but the amount of calculation is huge. In this paper, we deduced the change rule of PRF and proposed a variable PRF imaging algorithm based on time-frequency scale scaling. A new interpolation method is used to perform uniform sampling of the unambiguous signal in the time domain. Then use the Omega-K algorithm to achieve range cell migration correction (RCMC), and finally focuses the signal in the azimuth frequency domain. The proposed SAR working system with variable PRF is verified by simulation experiments. © 2021 IEEE.

关键词： Interpolation Sliding Spotlight TOPS SAR Variable PRF

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The observability analysis of aerial moving target location based on dual-satellite geolocation system

The observability analysis of aerial moving target location ...

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2012 International Conference on Computer science and Information processing, CSIP 2012

作者： Deng, Bing Xiong, Jinyu Xia, Changxiong Science and Technology on Blind Signal Processing Laboratory Chengdu China

ISBN: (纸本)9781467314114

Dual-satellite geolocation system is an effective passive location technique. This method can locate a stationary emitter on Earth by using time and frequency differences of arrival (TDOA/FDOA).In this paper, the rank of the observation matrix was proposed as standards of location observability, established location models, analysed the observability of aerial moving target location with the representative motion, such as uniform linear model and maneuvering turn model. Finally, simulation results presented a conclusion that Dual-satellite geolocation system could implement location for aerial moving target under some restrictions. In this paper, the rank of the observation matrix was proposed as standards of location observability, established location models, analysed the observability of aerial moving target location with the representative motion, such as uniform linear model and maneuvering turn model. Finally, simulation results presented a conclusion that Dual-satellite geolocation system could implement location for aerial moving target under some restrictions. © 2012 IEEE.

关键词： Observability

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