Science and Technology on Microwave Imaging Laboratory

Beijing, China

Science and Technology on Microwave Imaging Laboratory

Beijing, China
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Li L.,Science and Technology on Microwave Imaging Laboratory | Li L.,CAS Institute of Electronics | Li D.,Science and Technology on Microwave Imaging Laboratory | Li D.,CAS Institute of Electronics | And 2 more authors.
Science China Information Sciences | Year: 2017

A novel interferometric synthetic aperture radar (InSAR) signal processing method based on compressed sensing (CS) theory is investigated in this paper. InSAR image formation provides the scene reflectivity estimation along azimuth and range coordinates with the height information. While surveying the height information of the illuminated scene, the data volume enlarges. CS theory allows sparse sampling during the data acquisition, which can reduce the data volume and release the pressure on the record devices. InSAR system which configures two antennas to cancel the common backscatter random phase in each resolution element implies the sparse nature of the complex-valued InSAR image. The complex-valued image after conjugate multiplication that only a phase term proportional to the differential path delay is left becomes sparse in the transform domain. Sparse sampling such as M-sequence can be implemented during the data acquisition. CS theory can be introduced to the processing due to the sparsity and a link between raw data and interferometric complex-valued image can be built. By solving the CS inverse problem, the magnitude image and interferometric phase are generated at the same time. Results on both the simulated data and real data are presented. In comparison with the conventional SAR interferometry processing results, CS-based method shows the ability to keep the imaging quality with less data acquisition. © 2017, Science China Press and Springer-Verlag GmbH Germany.


Hui Z.,University of Chinese Academy of Sciences | Hui Z.,CAS Institute of Electronics | Hui Z.,Key Laboratory of Technology in Geo Spatial Information Processing and Application System Technology | Jun H.,CAS Institute of Electronics | Jun H.,Science and Technology on Microwave Imaging Laboratory
IET Conference Publications | Year: 2013

Along-Track Interferometric Synthetic Aperture Radar (ATISAR) has the potential of measuring the radial velocity of the slowly moving target. The accuracy of the radial velocity is mainly determined by the accuracy of the interferometric parameters. Sensitivity equations are good ways of analysing the impacts of system parameters for interferometric SAR. Former sensitivity analysis for ATI-SAR has been mainly focused on the case of no squint angle. In this paper, we explain the necessity of analysing the sensitivity equations in the presence of squint angle. Then the expression of the radial velocity in the presence of squint is derived and the sensitivity equations are obtained. Finally, the sensitivity of some interferometric parameters and the impact of squint angles are analysed and simulated for a particular accuracy requirement.


Li L.,CAS Institute of Electronics | Li L.,science and Technology on Microwave Imaging Laboratory | Li L.,University of Chinese Academy of Sciences | Hong J.,CAS Institute of Electronics | And 3 more authors.
IEEE National Radar Conference - Proceedings | Year: 2014

The Medium-Earth-Orbit Synthetic Aperture Radar (MEOSAR) is one of the most potential next-generation spaceborne SARs for its excellent performance. However, ionospheric effect is one of the most factors for the development of MEOSAR. Many researchers have studied the ionospheric effects on Low-Earth-Orbit SAR (LEOSAR), but there are few papers about ionospheric effects on MEOSAR. So it is very necessary to study ionospheric effects for the development of MEOSAR. In this paper, we established an analysis model for background ionospheric effects on MEOSAR based on the system characteristics of MEOSAR and the spatio-temporal variability of ionosphere firstly. Then we analyzed the effects induced by background ionosphere and its spatio-temporal variability on MEOSAR image quality. According to the results of our analysis, we conclude that the worsening of azimuth resolution, displacement in azimuth and distortion in range image will be serious for MEOSAR. Furthermore, ionospheric effects will become more and more serious with the increase of SAR altitude and the improvement of resolution designed. © 2014 IEEE.


Li L.-C.,Science and Technology on Microwave Imaging Laboratory | Li L.-C.,CAS Institute of Electronics | Li L.-C.,University of Chinese Academy of Sciences | Li D.-J.,Science and Technology on Microwave Imaging Laboratory | And 4 more authors.
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | Year: 2013

Side-looking three-Dimensional (3D) imaging of three-aperture sparse array Synthetic Aperture Radar (SAR) based on Compressed Sensing (CS) is investigated in this paper. Using the sparse array structure in crosstrack direction formed by three aperture antennas, the elevation resolution can be obtained and 3D imaging is achieved. However, the conventional Fourier transform based 3D imaging approach has a low resolution in elevation direction and brings the image quality problem because of the low number of acquisitions and irregular space sampling. CS theory is introduced to improve the resolution in the elevation direction. Experiment results on simulation and real data validate the effectiveness of the proposed method compared with the conventional imaging technique.


Zhang B.C.,Science and Technology on Microwave Imaging Laboratory | Zhang B.C.,CAS Institute of Electronics | Hong W.,Science and Technology on Microwave Imaging Laboratory | Hong W.,CAS Institute of Electronics | And 2 more authors.
Science China Information Sciences | Year: 2012

This paper provides principles and applications of the sparse microwave imaging theory and technology. Synthetic aperture radar (SAR) is an important method of modern remote sensing. During 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 implementation. The sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theory, new system and new methodology of microwave imaging. Based 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 algorithms. There 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 evaluation. Based 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 performance. The sparse signal processing has also been applied in several specific radar imaging applications. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.


Jiang C.L.,Science and Technology on Microwave Imaging Laboratory | Jiang C.L.,CAS Institute of Electronics | Jiang C.L.,University of Chinese Academy of Sciences | Zhang B.C.,Science and Technology on Microwave Imaging Laboratory | And 8 more authors.
Science China Information Sciences | Year: 2012

Sparse microwave imaging is a novel radar framework aiming to bring revolutions to the microwave imaging according to the theory of sparse signal processing. As 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 methods. However, the requirement for these methods to process the compressed range data results in the increase of the hardware complexity. So the SAR sparse imaging method that directly uses the raw data is needed. This 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 data. The 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 dropped. An 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 paper. Our method is helpful for designing new SAR systems. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.


Liu B.,Science and Technology on Microwave Imaging Laboratory | Liu B.,CAS Institute of Electronics | Liu B.,University of Chinese Academy of Sciences | Pan Z.-H.,Science and Technology on Microwave Imaging Laboratory | And 7 more authors.
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | Year: 2012

An inverse synthetic aperture radar (ISAR) imaging method based on motion compensation of a moving target was presented. The concept of radar imaging was applied to the process of moving target detection with low signal to noise ratio (SNR). The lateral and radial velocity of the target can be acquired by means of imaging processing. The location of the moving target and estimation of its cross-sectional area could be fulfilled using the multi-baseline image interferometric method. The geometric model for imaging moving target was established. A method for the compensation of signals from channels of multi-antenna time division multiplexing (TDM) receiver was proposed. The unambiguous angle orientation based on multi-baseline phase unwrapping was presented. The influence of the image SNR on interferometric orientation accuracy was analyzed. The validity of the proposed method was testified by both simulation and an example of its application.


Wang J.,Science and Technology on Microwave Imaging Laboratory | Wang J.,CAS Institute of Electronics | Wang J.,University of Chinese Academy of Sciences | Liang X.D.,Science and Technology on Microwave Imaging Laboratory | And 9 more authors.
Science China Information Sciences | Year: 2014

Special attention has been devoted to multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems in recent years. The applications of MIMO SAR systems which involve 3D imaging, highresolution wide-swath remote sensing, and multi-baseline interferometry are seriously limited to the orthogonal waveforms. Although orthogonal frequency division multiplexing (OFDM) chirp waveforms can be used for MIMO SAR systems to avoid intra-pulse interferences, there is a small frequency shift between the transmitted OFDM pulses. This vulnerable shift, which can not only affect the waveform orthogonality, but also introduce residual phase error, renders the OFDM waveforms impractical. In this paper, an improved OFDM chirp waveform which works without the mentioned shift is presented, along with the novel modulation and efficient demodulation procedures. Comparison between the improved and the conventional OFDM chirp waveforms is detailed. The influence of random noise, quantization error, and Doppler shift on the orthogonality of OFDM waveform is also investigated in this paper. Theoretical analysis and simulation results illustrate the feasibility of this waveform scheme. © 2014 Science China Press and Springer-Verlag Berlin Heidelberg.


Li L.,CAS Institute of Electronics | Li L.,science and Technology on Microwave Imaging Laboratory | Li L.,University of Chinese Academy of Sciences | Hong J.,CAS Institute of Electronics | And 5 more authors.
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | Year: 2014

The Medium-Earth-Orbit SAR (MEOSAR) is one of the potential next-generation spaceborne SARs. Ionospheric effects analysis is one of the critical techniques for the development of MEOSAR. An analysis model for background ionospheric effect on MEOSAR is established based on the system characteristics of MEOSAR and the spatio-temporal variability of ionosphere. The degradation of image quality, including resolution and displacement distortion, induced by background ionosphere and its spatio-temporal variability is analyzed. The analysis result shows that ionosphere and its time-space variability affect critically the quality of obtained images. In condition of the same ionosphere, the degradation of resolution in both azimuth and range, the distortion on range image and the displacements in azimuth image are all more serious with the increasing of SAR orbit height when the resolution is same.


Li L.,Science and Technology on Microwave Imaging Laboratory | Li D.,Science and Technology on Microwave Imaging Laboratory | Pan Z.,Science and Technology on Microwave Imaging Laboratory
Proceedings of 10th European Conference on Synthetic Aperture Radar, EUSAR 2014 | Year: 2014

A novel Interferometric SAR (InSAR) sparse sampling and signal processing method based on compressed sensing (CS) is investigated in this paper. The method uses the interferometric technique to cancel the random phase of each scattering cell, which makes the SAR images become sparse in the frequency domain. Exploiting this sparsity, the signal random sparse sampling can be achieved during the data acquisition and the CS theory can be introduced into the signal processing and implements scene reconstruction. Results on simulated data and real data show the good performance of the proposed method. © VDE VERLAG GMBH · Berlin · Offenbach, Germany.

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