基于RCCF‒PCT的机动目标运动参数估计

Maneuvering target motion parameters estimation based on robust cross-correlation and polynomial chirplet transform

摘要:

针对高速机动目标的运动参数估计问题，基于鲁棒互相关和多项式调频小波变换(RCCF-PCT)，提出了一种高速机动目标运动参数估计方法。该方法首先采用幂率变换增强信号，利用距离像互相关和鲁棒多项式回归完成距离徙动校正；再采用多项式调频小波变换对多普勒徙动初步补偿后的信号进行参数化时频分析，利用提取的时频脊特征完成目标运动参数的精确估计。通过数值实验验证了算法的有效性。

Abstract:

Considering the motion parameter estimation problem for a high?speed maneuvering target with complex motions, a novel motion parameter estimation algorithm based on the Robust Cross-Correlation Function(RCCF) and Polynomial Chirplet Transform(PCT), i.e., RCCF-PCT, is proposed. Firstly, after range profile image enhancement using the power-law transformation, the cross-correlation and robust polynomial regression operations are adopted to measure the target's motion parameters, which are used for the preliminary correction of the Range Migration(RM). Then, it employs the PCT to obtain the parameterized Time?Frequency Representation(TFR) of the Doppler Frequency Migration(DFM) coarsely compensated signal, and estimates the residual motion parameters with the time?frequency ridge feature extracted from the TFR. Finally, several numerical experiments are presented to demonstrate the effectiveness.