Ground slowly moving target detection and velocity estimation via high-speed platform dual-beam synthetic aperture radar

Xinxin Tang; Xiaoling Zhang; Jun Shi; Shunjun Wei; Ling Pu

doi:10.1117/1.JRS.13.026516

20 June 2019 Ground slowly moving target detection and velocity estimation via high-speed platform dual-beam synthetic aperture radar

Xinxin Tang, Xiaoling Zhang, Jun Shi, Shunjun Wei, Ling Pu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 13, Issue 2, 026516 (June 2019). https://doi.org/10.1117/1.JRS.13.026516

Abstract

Due to the spectrum of a moving target being almost submerged in ground clutter, it is difficult for high-speed platform synthetic aperture radar to indicate a slowly moving target by traditional methods. To solve this problem, a detection and azimuth velocity estimation method is proposed based on along-track dual-beam synthetic aperture radar mode. Back projection is adopted to focus the forward- and backward-looking-beam images due to abilities such as automatic coregistration and geometric correction. The positions of the moving target in the two images are deduced, and we show that there is an azimuth location offset for the moving target in the forward-and-backward-looking images proportional to its azimuth velocity, which can be used to detect the moving target and estimate its azimuth velocity. Furthermore, a refocusing method is proposed to obtain a more accurate estimation. Simulation results show that the proposed method can detect slowly moving targets, especially those only with an azimuth velocity, which is difficult for many existing methods. In addition, the accuracy of azimuth velocity estimation can reach 0.01 m / s when the signal-to-clutter ratio is greater than 5 dB under simulation conditions.

Citation Download Citation

Xinxin Tang, Xiaoling Zhang, Jun Shi, Shunjun Wei, and Ling Pu "Ground slowly moving target detection and velocity estimation via high-speed platform dual-beam synthetic aperture radar," Journal of Applied Remote Sensing 13(2), 026516 (20 June 2019). https://doi.org/10.1117/1.JRS.13.026516

Received: 16 December 2018; Accepted: 23 May 2019; Published: 20 June 2019

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