Bistatic inverse synthetic aperture radar imaging method for the high-speed motion target

Chuangzhan Zeng; Weigang Zhu; Xin Jia

doi:10.1117/1.JRS.12.045012

20 November 2018 Bistatic inverse synthetic aperture radar imaging method for the high-speed motion target

Chuangzhan Zeng, Weigang Zhu, Xin Jia

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 045012 (November 2018). https://doi.org/10.1117/1.JRS.12.045012

Abstract

Bistatic inverse synthetic aperture radar (ISAR) can help image the high-speed target for its advantage in tracking and more observation angle to provide more information than monostatic ISAR. However, the complex image geometry makes it difficult to achieve a clear image of the target with geometry distortion correction and calibration. Furthermore, high-speed motion will make the image blurred or defocussed. To address these problems, a bistatic ISAR (B-ISAR) imaging method for high-speed motion target with geometric distortion correction and calibration is proposed. According to the motion decomposition idea, we established the B-ISAR echo model of the high-speed motion target. Then, based on the range Doppler algorithm, we deduce the analytic formula of the geometric distortion factor and calibration factor, and transform the imaging problem into a parameter estimation problem. With the sparsity of the scattering points, the required parameters are solved using the expectation maximization algorithm based on the maximum a posteriori probability criterion. With the estimated parameters, a clear B-ISAR image of a high-speed motion target with geometric correction and calibration is obtained. The simulations show that the proposed method has better resolution and simultaneously attains geometric distortion correction and calibration of the image.

Citation Download Citation

Chuangzhan Zeng, Weigang Zhu, and Xin Jia "Bistatic inverse synthetic aperture radar imaging method for the high-speed motion target," Journal of Applied Remote Sensing 12(4), 045012 (20 November 2018). https://doi.org/10.1117/1.JRS.12.045012

Received: 19 June 2018; Accepted: 25 October 2018; Published: 20 November 2018

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