一种基于L1范数的目标源测向算法

在高维信号处理中,为了有效地估计信号的角度,提出了基于L1范数的二阶锥规划算法(L1-SVD).该算法将稀疏重构用于目标源测向技术,在窄带信号的模型基础上,引进稀疏域模型,将一个高维信号的角度估计问题抽象成欠定方程组求解问题.经Matlab仿真验证,与其他最小范数法以及经典多重信号分类算法相比,该算法在较大的信噪比范围内都能取得较低的重构误差和较高的成功概率,对相关性较大的信号也能进行识别.这证明了该算法能够有效地实现目标源测向.

A Target Source Direction Estimation Algorithm Based on L1 Norm

To estimate the angle signal in the high-dimensional signal processing efficiently,a second-order cone algorithm based on L1 norm(L1-SVD) is proposed.The algorithm applys sparse reconstruction to the target direction finding technology.Sparse domain model is introduced based on narrowband signal model,in which angle estimation problem of a high-dimensional signal is abstracted into underdetermined equations problems.Simulation results with Matlab show that,compared with other minimum norm methods and classic multiple signal classification algorithm,L1-SVD can achieve lower reconstruction error and a higher probability of success in a wide range of signal to noise ratio and identify the signal with larger correlation.So it is proved that the algorithm can achieve the target source direction estimation effectively.