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中文摘要：
提出了一种基于四阶累积量稀疏表示的估计方法，解决信号数多于阵元数时的DOA估计问题。该方法首先构造了包含所有DOA信息的最小冗余矢量，利用扩展阵列的最小冗余导向矢量构造完备字典减小完备字典的复杂度；然后利用L1范数作为稀疏约束条件建立稀疏模型进行DOA估计。理论分析和仿真实验，验证了该方法能够估计出的信号个数大于阵元数目，可直接应用于相干信号，比MUSIC-like算法具有更好的性能。
英文摘要：
A sparse representation based on fourth-order cumulants is proposed in this paper,which is to solve the Direction Of Arrival （DOA）estimation when the number of signals are larger than the number of array. Firstly,the minimum redundant vector is generated which contain all the DOA information and remove redundancy information. After that,the over-complete dictionary with the minimum redundant steering vectors is created. A sparse DOA estimation model is constructed with L1 norm as constraint. Theoretical analysis and simulation results show that the method can estimate the number of signals is larger than the number of array elements and can be applied to the coherent signal directly. It has better performance than the normal sparse representation methods and MUSIC-like method.
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