scholarly journals New Compressed Sensing ISAR Imaging Algorithm Based on Log–Sum Minimization

2016 ◽  
Vol 67 (6) ◽  
pp. 439-443
Author(s):  
Cheng Ping ◽  
Zhao Jiaqun
Keyword(s):  
Compressed Sensing ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Signal Spectrum ◽  
Imaging Algorithm ◽  
Imaging Result ◽  
Isar Imaging ◽  
Recovery Error ◽  
New Interpretation ◽  
Conventional Algorithm

Abstract To improve the performance of inverse synthetic aperture radar (ISAR) imaging based on compressed sensing (CS), a new algorithm based on log-sum minimization is proposed. A new interpretation of the algorithm is also provided. Compared with the conventional algorithm, the new algorithm can recover signals based on fewer measurements, in looser sparsity condition, with smaller recovery error, and it has obtained better sinusoidal signal spectrum and imaging result for real ISAR data. Therefore, the proposed algorithm is a promising imaging algorithm in CS ISAR.

scholarly journals Fast off grid compressed sensing ISAR imaging algorithm

2018 ◽  
Vol 69 (4) ◽  
pp. 326-328
Author(s):  
Cheng Ping ◽  
Zhao Jiaqun
Keyword(s):  
Compressed Sensing ◽  
Optimization Problem ◽  
Synthetic Aperture ◽  
Joint Optimization ◽  
Least Squares Problems ◽  
Imaging Algorithm ◽  
First Order ◽  
Taylor Approximation ◽  
Isar Imaging ◽  
Conventional Algorithm

Abstract To solve the off grid problem in compressed sensing (CS) based inverse synthetic aperture radar (ISAR) imaging, a fast and accurate algorithm has been proposed in the paper. By jointly estimating the off grid error and the sparse solution, off grid ISAR imaging is transformed into a joint optimization problem. Interestingly, it can be solved efficiently through two least squares problems based on first order Taylor approximation. When applied to complex sinusoids and quasi real ISAR data, the proposed algorithm has got better results than the conventional algorithm. Therefore, it is a promising off grid CS based ISAR imaging algorithm.

scholarly journals An Improved Space Debris ISAR Imaging Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 321-326
Author(s):  
Bao Ping Wang ◽  
Jun Jie Guo ◽  
Chao Sun
Keyword(s):  
Fourier Transform ◽  
Synthetic Aperture Radar ◽  
Space Debris ◽  
Position Error ◽  
Synthetic Aperture ◽  
Inverse Synthetic Aperture Radar ◽  
Imaging Algorithm ◽  
Scattering Centers ◽  
Isar Imaging ◽  
Aperture Radar

According to the Characteristics of space debris, single-range matching filtering (SRMF) can be used for space debris inverse synthetic aperture radar (ISAR) imaging. Combined SRMF and Coherent CLEAN algorithm can effectively solve high sidelobes problem brought by Fourier transform. However, when the SNR is low, the position error of scattering centers extracted by SRMF-CLEAN is big, and even some weak scatterings can’t be extracted. This paper uses Sequence CLEAN instead of Coherent CLEAN to availably solve the above problems. The experiment results confirm the validness of the proposed algorithm.

Analysis of Forward-Looking Synthetic Aperture Radar Imaging Characteristics of Rotating Target

2014 ◽  
Vol 1044-1045 ◽  
pp. 1057-1060
Author(s):  
Lei Chen ◽  
Dian Ren Chen ◽  
Ying Liu ◽  
Ze Chuan Lv
Keyword(s):  
Synthetic Aperture Radar ◽  
Doppler Frequency ◽  
Synthetic Aperture ◽  
Stationary Target ◽  
Imaging Result ◽  
Imaging Characteristics ◽  
Imaging Results ◽  
Rotating Target ◽  
Aperture Radar ◽  
Forward Looking

In this paper,it is established the geometric and radar echo model of the rotating target with the Forward-looking synthetic aperture radar firstly,then the Doppler frequency History Formula is Deduced and Pointed out that the Formula has a sinusoidal characteristics. It is simulated the imaging of the stationary target and the rotating target with different rotation speed, the imaging result can be expressed as the forms of curve and the curve circle nomadic type, when these features appear in the imaging results, it can initially determine that the rotating target is presence.

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