基于频域超分辨的高速目标参数估计算法

针对宽带噪声雷达高速目标探测中参数估计性能与运算复杂度无法兼顾的问题，该文提出一种基于频域超分辨的参数估计算法。该算法通过设置不同固定时延得到多组含有不同相位信息的组合噪声调频信号，并对每组信号进行不含尺度变换的匹配滤波运算，以此来构造多普勒相位差组。根据多普勒相位差组与阵列信号处理的相似性，利用现代谱估计算法得到目标的速度信息，构造多普勒补偿函数进行包含尺度变换的匹配滤波运算估计出目标的距离信息。该算法可以在无需考虑多普勒色散的情况下估计出目标速度，整个运算过程仅需1次时域重构运算；当多普勒相位差组的固定时延及分组数选择合适时，其运算复杂度及参数估计性能皆优于曲面拟合的宽带互模糊函数算法。仿真结果验证了该算法的有效性。

Parameters Estimation of High Speed Targets Based on Frequency Domain Super-resolution

To solve the contradiction between estimation performance and computation burden, when detecting high speed target in wideband noise radar, a novel method based on Frequency Domain Supper-Resolution (FDSR) is proposed for parameter estimation. Firstly, a group of component noise frequency modulation signals with different phase information are obtained by setting different fixed delay, and the Doppler phase difference group is constructed through matched filtering without scaling transform. Then according to the similarity of Doppler phase difference group and array signal processing, the velocity is acquired through modern spectrum estimation algorithm, and the range is calculated by scaled matched filtering after Doppler compensation. In this method, the velocity is obtained without considering Doppler dispersion and the time-domain reconstruction is used only once in the whole algorithm. The computation burden and estimation performance both superior to wideband cross ambiguity function algorithm based on curve fitting, when the fixed delay and group number of Doppler phase difference group are appropriately selected. The effectiveness of this algorithm is validated by simulation results.