基于序列线性规划的雷达低峰均比估计波形设计

在信号相关杂波背景下,现有方法大部分均基于频域进行雷达估计波形设计,这将引起相位信息的缺失从而导致波形变换到时域后性能降低。针对上述问题,同时兼顾放大器的非线性特性,提出了一种基于时域的低峰均比(peak to average power ratio, PAR)估计波形设计方法。首先,根据最大互信息准则在时域上构建了优化问题模型;然后，基于序列线性规划思想,将非凸的优化问题松弛为凸问题,并求得波形矩阵的近似解;最后,对该波形矩阵解进行逼近,使得新的波形矩阵满足Toeplitz结构,进而提取出波形向量解。仿真结果表明,与现有方法相比,本文方法在不增加运算量的前提下具有更好的估计性能。

Radar estimation waveform design under low-PAR constraints based on sequence linear programming#br#

The existing radar estimation waveform design methods mostly concentrate on the frequency domain in presence of signal dependent clutter, which leads to the missing of waveform phase information. Then the estimation performance will decline when the waveform is transformed into time domain. To solve this problem, while considering the non linear characteristics of the amplifier, we propose a low peak-to-average power ratio (PAR) estimation waveform design method. Firstly, an optimization model is established based on the maximum mutual information criterion. Secondly, an approximate waveform matrix is obtained by relaxing the non convex problem into a convex problem based on the sequence linear programming method. Finally, the proposed waveform matrix which satisfies the Toeplitz matrix structure is obtained by approximating the former waveform matrix, then the optimal vector solution of waveform can be extracted. Compared with the existing method, the proposed method has better estimation performance without adding additional computation.