基于特征子空间的最小二乘恒模算法

The Eigenvalue- Based Least Squar Constant Modulus Algorithm

最小二乘恒模算法(lscma)是阵列信号处理中广泛使用的一种能全局收敛且稳定性强的算法,但是当低信噪比的情况下它的收敛性和输出信干噪比会明显下降。本文在信号子空间特征值分解的基础上进行权值迭代,提出一种基于特征子空间的最小二乘恒模算法(eb-lscm)。经过实验仿真该算法的收敛性要强于lscma算法。

The lscma is a constringent and steady algorithm in array signal processing.But the astringency and SINR would be decline obvious when the SNR were low.In this article ,we set out the formula of weight＂ s iterative base on the eigenspace＂ s disassemble and proposed the eb-lscm algorithm .Simulation results show the eb-lscm algorithm is superior to the lscma in astringency.