【摘 要】
：
针对l1范数下奇异值分解的l1-SVD稀疏信号重建的波达方向估计方法存在求解量的稀疏性较差且空间谱中存在较多的伪峰,不能准确估计波达方向的问题,对接收信号矩阵进行预处理,
【机 构】
：
西安邮电大学通信与信息工程学院,西安交通大学电子与信息工程学院,
论文部分内容阅读
针对l1范数下奇异值分解的l1-SVD稀疏信号重建的波达方向估计方法存在求解量的稀疏性较差且空间谱中存在较多的伪峰,不能准确估计波达方向的问题,对接收信号矩阵进行预处理,并使用信号子空间设计权值矢量得到更好的稀疏性和更好地逼近l0范数,利用得到的权值矢量对l1-SVD算法中解矢量的各个元素进行加权,以得到的加权l1范数作为最小化的目标函数进行优化.仿真结果表明,提出的算法在快拍数、正则化参数和信噪比等条件改变的情况下能有效抑制伪峰,并准确稳定地估计出波达方向.
The DOA estimation method of l1-SVD sparse signal reconstruction under the singular value decomposition of l1 norm has the problems of poor sparsity of solution and spurious peaks in the spatial spectrum, which can not accurately estimate the DOA. Receive the signal matrix pretreatment, and the use of signal subspace design weight vector to get better sparse and better approximation l0 norm, the use of the weight vector l1-SVD algorithm solution vector weight of each element , And the weighted l1 norm obtained is optimized as the minimization objective function.The simulation results show that the proposed algorithm can effectively suppress the spurious peaks under the condition of fast number of shots, regularization parameters and signal-to-noise ratio, and is accurate The direction of arrival is stably estimated.
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