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Synthetic aperture radar tomography sampling criteria and three-dimensional range migration algorithm with elevation digital spotlighting

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Science in China(Series F) 2009年第1期52卷 100-114页

作者： TAN WeiXian1,2,3., HONG Wen1,2, WANG YanPing1,2, LIN Yun1,2,3.& WU YiRong1,2 1 State key laboratory of microwave {3. {3., beijing 100190, China 2 Institute of Electronics, Chinese Academy of Sciences, beijing 100190, China 3.Graduate School, Chinese Academy of Sciences, beijing 100190, China State key laboratory of microwave {3. {3. Beijing 100190 China Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate School Chinese Academy of Sciences Beijing 100190 China

Based on the general geometric model of multi-baseline Synthetic Aperture Radar Tomography （TomoSAR）, the three-dimensional （3.D） sampling criteria, the analytic expression of the 3.D Point Spread Function （PSF） and the 3.D resolution are derived in the 3.D wavenumber domain in this paper. Considering the relationship between the observation geometry and the size of illuminated scenario, a 3.D Range Migration Algorithm with Elevation Digital Spotlighting （RMA-EDS） is proposed. With this algorithm 3.D images of the area of interest can be directly and accurately reconstructed in the 3.D space avoiding the complex operations of 3.D geometric correction. Finally, theoretical analyses and simulation results are presented to demonstrate the shift-varying property of the 3.D PSF and the spatialvarying property of the 3.D resolution and to demonstrate the validity of the 3.D RMA-EDS.

关键词： synthetic aperture radar tomography (TomoSAR) three-dimensional (3.D) SAR imaging 3.D sampling criteria 3.D resolution,3.D range migration algorithm with elevation digital spotlighting (RMA-EDS)

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A universal adaptive vector quantization algorithm for space-borne SAR raw data

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Science China(Information Sciences) 2012年第6期55卷 1280-1289页

作者： QI HaiMing 1,2,HUA Bin 1,2,LI Xin 1,2,YU WeiDong 1 & HONG Wen 1,2 1 Institute of Electronics,Chinese Academy of Sciences,beijing 100190,China 2 national {3. {3. of microwave imaging technology,beijing 100190,China 1. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China2. National Key Laboratory of Microwave Imaging Technology Beijing 100190 China

Codebook of conventional VQ cannot be generally used and needs real time onboard updating,which is hard to implement in spaceborne SAR *** order to solve this problem,this paper analyses the characteristic of space-borne SAR raw data firstly,and then utilizes the distortion function of multidimensional space as criterion,and finally the adaptive code book design algorithm is proposed according to the joint probability density function of the input ***,the feasibility of the new algorithm in cascade with entropy coding and the robustness of the algorithm when error occurs during transmission are analysed based on the encoding and decoding *** results of real data show that codebook deriving from the new algorithm can be generally used and designed off-line,which makes VQ a practical algorithm for space-borne SAR raw data compression.

关键词： synthetic aperture radar (SAR) compression raw data block adaptive quantization (BAQ) vector quantization (VQ)

Multi-channel SAR imaging based on distributed compressive sensing

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Science China(Information Sciences) 2012年第2期55卷 245-259页

作者： LIN YueGuan1,2,3.ZHANG BingChen1,2,JIANG Hai1,2,3.HONG Wen1,2 & WU YiRong1,2 1national key {3. of Science and technology on {3. imaging,beijing 100190,China 2Institute of Electronics,Chinese Academy of Sciences,beijing 100190,China 3.raduate University of Chinese Academy of Sciences,beijing 100049,China 1. national key laboratory of Science and {3. on {3. imaging Beijing 100190 China2. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China3. Graduate University of Chinese Academy of Sciences Beijing 100049 China

The rapid development of compressive sensing(CS)shows that it is possible to recover a sparse signal from very limited *** aperture radar(SAR)imaging based on CS can reconstruct the target scene with a reduced number of collected samples by solving an optimization *** multi-channel SAR imaging based on CS,each channel requires sufficient samples for separate imaging and the total number of samples could still be *** propose an imaging algorithm based on distributed compressive sensing(DCS)that reconstructs scenes jointly under multiple ***-channel SAR imaging based on DCS not only exploits the sparsity of the target scene,but also exploits the correlation among *** requires significantly fewer samples than multi-channel SAR imaging based on *** multiple channels offer different sampling rates,DCS joint processing can reconstruct target scenes with a much more flexible allocation of the number of measurements offered by each channel than that used in separate CS processing.

关键词： synthetic aperture radar multi-channel synthetic aperture radar compressive sensing distributed compressive sensing

A study of spaceborne SAR raw data compression error based on a statistical model of quantization interval transfer probability

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Science China(Information Sciences) 2010年第11期53卷 2352-2362页

作者： LI Xin1,2,3., QI HaiMing1,2*, HUA Bin1,2,3. LEI Hong1 & YU WeiDong1 1Institute of Electronics, Chinese Academy of Sciences, beijing 100190, China 2.he national key laboratory of microwave imaging technology, beijing 100190, China 3.raduate University, Chinese Academy of Sciences, {3. 10003., China 1. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China2. The National Key Laboratory of Microwave Imaging Technology Beijing 100190 China3. Chinese Academy of Sciences Graduate University Beijing 100039 China

SAR raw data signal to noise ratio (SNR) after compression is of great importance since the choice of compression ratio is dependent on it during SAR system design and application analysis. The signal to quantization noise ratio (SQNR) generally used may not precisely indicate the relationship between signal and noise. Considering the thermal noise, a statistical model of quantization interval transfer probability is proposed in this paper. SNR mapping between SAR raw data before analog to digital converter (ADC) and after block adaptive quantization (BAQ) over the whole set of saturation degree is obtained using this model. When the power of echo is small with low SNR, after 1, 2, 3.or 4 bits BAQ compression, SNR has tiny difference among the four compression levels. When the power of the echo is medium with higher SNR, the SNR degradation after BAQ is about 5 dB with each bit decreasing from 4 bits. If voltage of the echo is higher than the clipping point of ADC, SNR after ADC and BAQ degrades stepwise. The higher the saturation degree of SAR raw data, the worse the SNR is. Simulated Gaussian data and real SAR raw data are used to verify the theoretical results, which are useful in the choice of BAQ compression ratio and further application analysis.

关键词： SAR raw data compression SNR saturation

Influence factors of sparse microwave imaging radar system performance:approaches to waveform design and platform motion analysis

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Science China(Information Sciences) 2012年第10期55卷 2301-2317页

作者： ZHANG Zhe 1,2,3.ZHANG BingChen 1,2,JIANG ChengLong 1,2,3.XIANG Yin 1,2,HONG Wen 1,2 & WU YiRong 1,2 1 Science and {3. on microwave imaging {3.,beijing 100190,China 2 Institute of Electronics,Chinese Academy of Sciences,beijing 100190,China 3.Graduate University,Chinese Academy of Sciences,beijing 100190,China 1. Science and technology on microwave imaging {3. Beijing 100190 China 2. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China 3. Graduate University Chinese Academy of Sciences Beijing 100190 China

Sparse microwave imaging radar is a newly developed concept of microwave imaging system,which tries to combine the traditional radar imaging system with sparse signal processing theories,achieving the aim of reducing the complexity of microwave imaging systems and enhancing the system *** this paper,we introduce some basic concepts of sparse signal processing theory,and then apply it to the traditional radar imaging system to get the mathematical model of sparse microwave imaging *** analyze the factors that determine the performance of sparse microwave imaging radar,including scene,waveform and *** to the radar model,we analyze how these factors influence the radar system and how to optimize *** results of the sparse microwave imaging radar system are also provided.

关键词： sparse microwave imaging radar synthetic aperture radar compressive sensing Lq regularization waveform design

Sparse microwave imaging:Principles and applications

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Science China(Information Sciences) 2012年第8期55卷 1722-1754页

作者： ZHANG BingChen1,2,HONG Wen1,2 & WU YiRong1,2 1Science and technology on microwave {3. {3.,beijing 100190,China 2Institute of Electronics,Chinese Academy of Sciences,beijing 100190,China 1. Science and technology on microwave imaging {3. Beijing 100190 China2. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

This paper provides principles and applications of the sparse microwave imaging theory and *** aperture radar(SAR) is an important method of modern remote *** decades microwave imaging technology has achieved remarkable progress in the system performance of microwave imaging technology,and at the same time encountered increasing complexity in system *** sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theory,new system and new methodology of microwave *** on classical SAR imaging model and fundamental theories of sparse signal processing,we can derive the model of sparse microwave imaging,which is a sparse measurement and recovery problem and can be solved with various *** exist several fundamental points that must be considered in the efforts of applying sparse signal processing to radar imaging,including sparse representation,measurement matrix construction,unambiguity reconstruction and performance *** on these considerations,the sparse signal processing could be successfully applied to radar imaging,and achieve benefits in several aspects,including improvement of image quality,reduction of data amount for sparse scene and enhancement of system *** sparse signal processing has also been applied in several specific radar imaging applications.

关键词： sparse microwave imaging sparse signal processing compressive sensing synthetic aperture radar radar imaging

On the placement of actuators and sensors for flexible structures with closely spaced modes

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Science China(Technological Sciences) 2010年第7期53卷 1973-1982页

作者： LIU XiaoXiang1,2 & HU Jun1,2 1 beijing Institute of Control Engineering, beijing 100190, China 2 State key {3. of Science and {3. on Space Intelligent Control, beijing 100190, China 1. beijing Institute of Control Engineering Beijing 100190 China2. State Key Laboratory of Science and Technology on Space Intelligent Control Beijing 100190 China

This paper analyzed the fundamental limitations of previous work and developed a new method to optimally locate actuators and sensors for structures with close modes. Optimization criteria were defined based on the distinguishing modal controllability and observability measures of close modes. An appropriate genetic algorism was adopted as the optimization algorism. Solving the high order Lyapunov functions was avoided by means of the closed-form expressions for controllability and observability Grammians. Since structure with widely separated natural frequencies is approximately balanced, computational efficiency was improved by grouping close modes together and dealing with the resulting subsystems independently. Finally, the effectiveness and optimality of the novel placement scheme were verified on a model structure with close modes.

关键词： close modes controllability/observability sensor/actuator optimization criterion optimization algorithm

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Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase

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Science China(Information Sciences) 2011年第3期54卷 448-459页

作者： LUO Xiong 1,2 & LI Jiang 1 1 Department of Computer Science and technology, key laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and technology {3., {3. 100083. China 2 national laboratory of Space Intelligent Control, beijing 100190, China 1. Department of Computer Science and technology Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing 100083 China2. National Laboratory of Space Intelligent Control Beijing 100190 China

The intelligent autonomous control of hypersonic vehicles has aroused great interest from the field of spacecraft. To solve the problem of longitudinal attitude control of hypersonic vehicle in gliding phase, a new intelligent controller is proposed in this paper. This new controller is based on the fuzzy dynamic characteristic modeling method. The fuzzy logic is introduced into the characteristic modeling by dividing the whole restriction range into several subspaces. Simulations show that this modification greatly improves the performance of the original method. With the same whole restriction range the fuzzy dynamic characteristic modeling decreases the time of convergence, and at the same time makes the attitude angle tracing more precise and robust. Since the sub-model is a characteristic model that has stronger adaptiveness than a fixed local model, the number of fuzzy rules is greatly reduced. Our model sharply reduces the complexity in constructing a fuzzy dynamic model. Finally, simulation results are given to show the effectiveness of the proposed approach in dealing with the attitude control problem of hypersonic vehicle in gliding phase.

关键词： hypersonic vehicle gliding attitude control fuzzy dynamic characteristic modeling

Experimental results and analysis of sparse microwave imaging from spaceborne radar raw data

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Science China(Information Sciences) 2012年第8期55卷 1801-1815页

作者： JIANG ChengLong1,2,3.ZHANG BingChen1,2,ZHANG Zhe1,2,3.HONG Wen1,2&WU YiRong1,2 1S cience and {3. on microwave imaging {3.,beijing 100190,China 2I nstitute of Electronics,Chinese Academy of Sciences,beijing 100190,China 3. raduate University of Chinese Academy of Sciences,beijing 100190,China 1. Science and technology on microwave imaging {3. Beijing 100190 China2. Institute of Electronics Chinese Academy of Sciences Beijing 100190 China3. Graduate University of Chinese Academy of Sciences Beijing 100190 China

Sparse microwave imaging is a novel radar framework aiming to bring revolutions to the microwave imaging according to the theory of sparse signal *** compressive sensing(CS)is introduced to synthetic aperture radar(SAR)imaging in recent years,the current SAR sparse imaging methods have shown their advantages over the traditional matched filtering ***,the requirement for these methods to process the compressed range data results in the increase of the hardware *** the SAR sparse imaging method that directly uses the raw data is *** paper describes the method of SAR sparse imaging with raw data directly,presents the analysis of the signal-to-noise ratio(SNR)in the echo signal by combining the traditional radar equation with the compressive sensing theory,and provides the tests on 2-D simulated SAR *** simulation results demonstrate the validity of the SNR analysis,and the good performance of the proposed method while a large percentage of the raw data is *** experiment with RadarSat-1 raw data is also carried out to show the feasibility of processing the real SAR data via the method proposed in this *** method is helpful for designing new SAR systems.

关键词： sparse microwave imaging synthetic aperture radar(SAR)imaging compressive sensing signalto-noise ratio raw data