基于SVD的通信信号背景下脉冲波形和初相估计

雷达侦察接收机往往侦察到的是通信和雷达脉冲的混合信号，如何从通信信号背景中有效提取出雷达脉冲波形，是现代雷达信号处理领域中的重要内容。针对这一问题，提出了一种基于奇异值分解的通信与雷达混合信号中脉冲波形估计算法。该算法通过对信号观测矩阵的奇异值分析和协方差矩阵的特征值分析，证明了观测矩阵的奇异值分解具有稳定性，并且奇异值分解能够最佳近似观测信号的线性特征，给出了一种利用左右奇异向量估计脉冲波形及其相对初相的方法。本文的算法适用于任意脉冲波形，并且能够在较低信噪比环境下估计脉冲信号波形和相对相位，仿真结果证明了算法的有效性。

Waveform and primary phase estimation of pulse in background of communication signals based on SVD

The problem of waveform estimation of radar pulses which are badly contaminated by communication signals is addressed in this paper. A new method based on singular value decomposition (SVD) for waveform estimation of radar pulse is given, even when the pulse in the background of communication signals. Through the characteristic analysis of SVD and eigenanalysis, the stability of SVD is proved, and the SVD has the best approximation to the linear characteristic of the signal observation matrix. Through the SVD of the signal observation matrix, the algorithm gives a waveform estimation method by singular vector (eigenvectors), and the method can also estimate the primary phase of pulse. The algorithm adapts to waveform of pulse with any shapes, and it also can estimate the waveform from low signal-to-noise ratio environment. Some simulations are accomplished, and proved the efficiency of the algorithm.