Super-Resolution Micro-Range Curve Extraction for Precession Cone-Shaped Targets Based on Multidimensional Information

Abstract

The micro-range curve extraction of scattering centers is significant for estimating the motion and structural parameters of space targets. The curves are often extracted from high-resolution range profile (HRRP) for its range dimension information. However, most of the existing curve extraction algorithms based on HRRPs are with the accuracy of curves limited by range resolution. Moreover, due to noise interference, it is difficult to achieve extraction under low signal-to-noise ratio (SNR). Therefore, a super-resolution micro-range extraction algorithm based on the parameter correlation between micro-range curves and micro-Doppler (m-D) curves is proposed in this article. First, a parametric curve model is constructed and a rough parameter search of model is conducted to obtain the initial range curve, which ensures the robustness and real-time performance. Second, time-frequency analysis is applied to the range bins of the curve, and the m-D curve is refined by local maxima search to further improve the accuracy. The accurate micro-range curve is then reconstructed with the absolute range acquired by a 1-D search. Finally, simulation and experiment are carried out to verify the effectiveness and superiority of the proposed algorithm, which can achieve a better accuracy when SNR is −10 dB, compared with the existing methods.