A FOURTH-ORDER CUMULANT BASED RECURSIVE APPROACH TO DOA ESTIMATION WITH SPARSITY CONSTRAINT
基于四阶累积量的后验稀疏约束迭代DOA估计方法

One disadvantage with subspace-based DOA estimate method is that it is difficult to incorporate prior knowledge of the signal correlation into the eigen-decomposition. Herein, an estimator that combines ideas from subspace and four-order cumulant matching method is proposed, which makes it possible to incorporate the prior knowledge of signal correlation and sparsity of the DOA estimation into the estimator. Theoretical analysis and numerical results illustrate the robust and high resolution character of the estimator.