J4 ›› 2012, Vol. 39 ›› Issue (3): 63-71.doi: 10.3969/j.issn.1001-2400.2012.03.010

• Original Articles • Previous Articles     Next Articles

Translational motion compensation for ISAR imaging based on joint autofocusing under the low SNR

YANG Lei;XIONG Tao;ZHANG Lei;XING Mengdao   

  1. (National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2011-02-24 Online:2012-06-20 Published:2012-07-03
  • Contact: YANG Lei E-mail:xdthomasyl@gmail.com

Abstract:

In conventional inverse synthetic aperture radar (ISAR), since range alignment can not be accurately performed in low signal-to-noise (SNR) environment, the subsequent phase adjustment will be limited in precision. To address this problem, a novel autofocusing method is proposed, which is capable of correcting both range shift and phase disturbance. It can compensate the translational motion in a complex form for ISAR data contaminated with strong noise. The method utilizes the entropy of the ISAR image as the optimization function, and the Damped Newton algorithm is applied to solve the problem efficiently. According to the fact that the translational motion can be usually fitted by limited-order polynomial, the normalized polynomial fitting technique is applied to enhance both the efficiency and precision of the proposal. Finally, real data of Yak-42 are used to validate the effectiveness and reliability of the proposed method under the low SNR.

Key words: inverse synthetic aperture radar (ISAR), minimum entropy (ME), damped newton algorithm, joint autofocus