基于稀疏分解的微弱信号检测方法

微弱信号的检测在通信、雷达、声纳等领域有着重要的意义,一直是信号处理的难点。本文将信号稀疏分解思想应用于信号检测,提出一种算法。算法中信号稀疏分解采用Matching Pursuit(MP)算法实现,原子采用正弦波模型,通过对正弦波模型伸缩和平移形成过完备原子库。由MP分解结果,可检测出淹没在强噪声环境中的微弱正弦信号的幅度、频率和初相位参数,从而恢复出待检测的微弱正弦信号。所提出方法在-40 dB极低信噪比环境下可以同时检测多个正弦信号。计算机仿真结果证实了算法的有效性。

A Weak Signal Detection Method Based on Sparse Decomposition

To detect weak signals is difficult in signal processing and is very important in many areas such as communication,Radar and Sonar.In this paper,a new algorithm is proposed by introducing the idea of sparse decomposition into signal detection.The sparse decomposition is implemented by matching pursuit(MP) in this algorithm.The model of atoms is the sinusoidal function,and the redundancy dictionary is built up by stretching,compression and time shift of sinusoidal functions.The amplitude,frequency and initial phase parameters of sinusoidal signals blurred by strong noise can be estimated according to the parameters of the MP decomposed atoms,and the expected weak sinusoidal signal can be then reconstructed.The new method can detect more than one sinusoidal signal simultaneously at very low SNR of-40dB.Computer simulations confirm its validity.