基于FRFT与Keystone变换的运动目标参数估计算法

摘要

目标运动参数估计精度是衡量雷达探测系统性能的重要指标。该文为解决目标运动参数的估计问题，建立了运动目标回波模型，在利用分数阶傅里叶变换(FRFT)估计加速度的过程中采用数据融合提高估计精度，在估计出加速度的基础上通过Keystone变换和速度模糊通道解决距离走动(RCM)和多普勒模糊问题。仿真实验表明算法在估计精度和计算量上具有优势，并且对白噪声具有较好的鲁棒性。%An important standard to measure the effectiveness of radar acquisition systems is the accuracy of target parameter estimation. To solve the estimation problem, the echo model of moving targets is established and the FRactional Fourier Transform (FRFT) is subsequently used to estimate the acceleration; further, data fusion is used to raise estimation accuracy. Finally, Range Cell Migration (RCM) and Doppler ambiguity are solved by using the Keystone transform and the ambiguity channels based on the estimated acceleration. The simulation results show high accuracy, complexity, and noise robustness.