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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2018, Vol. 39 ›› Issue (8): 322037-322037.doi: 10.7527/S1000-6893.2018.22037

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Algorithm for autofocusing of bistatic ISAR of space target based on sparse decomposition

HAN Ning1, LI Baochen2, WANG Libing3, TONG Jun3, GUO Baofeng4   

  1. 1. Ordnance Technique Research Institute, Shijiazhuang 050003, China;
    2. Scientific Research and Academic Department, Army Engineering University, Nanjing 210014, China;
    3. No. 63961 Unit, PLA, Beijing 100012, China;
    4. Shijiazhuang Campus of Army Engineering University, Shijiazhuang 050003, China
  • Received:2018-01-23 Revised:2018-05-02 Online:2018-08-15 Published:2018-05-02
  • Supported by:
    National Natural Science Foundation of China (61601496)

Abstract: In bistatic Inverse Synthetic Aperture Radar (ISAR) imaging of the space target, variation of the bistatic angle with time can cause defocusing of the two-dimensional image. To solve this problem, the principle for bistatic ISAR imaging of the stable space target is analyzed under the condition that the three synchronizations are realized ideally. The mechanism of influence of variation of the bistatic angle with time on defocusing of the two-dimensional image is researched, and an algorithm for autofocusing with high accuracy is proposed based on sparse decomposition. The cosine of half of the bistatic angel is approximated with Taylor expansion, and then the imaging phase is modelized as a polynomial according to the translation and rotation conditions of the space target. The second-order coefficient of the polynomial is obtained based on the sparse decomposition algorithm, and the compensation item is constructed to complete phase compensation with the obtained coefficient. Regular parameters are determined according to the L-curve criterion. High resolution factors of the redundant basis is designed based on prior information of the target size. Sparse representation coefficients are estimated with the extended generalization FOCal Underdetermined System Solver (FOCUSS) algorithm. The second-order phase item can be compensated accurately if the redundant dictionary resolution is chosen appropriately. The simulation experiment proves that performance of the algorithm proposed is prior to that of the common algorithm for non-parameter autofocusing.

Key words: space target, radar imaging, bistatic ISAR, sparse decomposition, autofocusing

CLC Number: