基于加权平滑l_0范数的单快拍波达方向估计

针对现有基于压缩感知的DOA估计算法估计精度不高的问题,提出一种基于加权平滑l0范数的单快拍DOA估计算法。所提算法采用一种新的加权方式,在构造一个恰当的平滑连续函数后,根据接收数据的初始解确定一个合适的递减的{σ}序列[σ_1,σ_2,?,σ_J],并对每一个σ值,用最速下降法来求解l0范数的逼近函数H_σ(S)的最小值;然后将该σ值作为下一次迭代的初始值,并在每次迭代开始时更新权值,通过多次的迭代获得逼近函数的最小解,即逼近的最小l0范数。通过仿真实验表明所提算法可对DOA进行有效估计,且容易实现、精度较高,与未加权的改进平滑l_0范数DOA估计方法相比具有更好的估计性能。

Single Snapshot DOA Estimation Based on Weighted Smoothed l 0 Norm

In order to improve the estimation accuracy of the existing DOA estimation algorithms based on compressive sensing,a single snapshot DOA estimation algorithm based on weighted smoothed l0 norm (WSL0) has been pro-posed in this article. Firstly,a proper smooth continuous function is constructed by using a new weighting method. Ac-cording to the initial solution of receiving data, a proper decreasing sequence [ ]σ1,σ2,?,σJ is given. Solve the mini-mum value of the approximation function Hσ(S) for every single σ by using the steepest descent method. Then set the σ as the initial value of next iteration and update the weights at the beginning of each iteration, thus, the mini-mum solution of Hσ(S) ,that is the approximated minimum l0 norm can be obtained after a number of iterations. The proposed algorithm is easy to implement and can estimate DOA effectively with high precision. Compared with the DOA estimation algorithm based on unweighted smoothed l0 norm,the proposed algorithm has better estimation performance.