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Capon algorithm is a common algorithm for the estimating of direction of arrival (DOA). As it needs two-dimensional (2D) spectrum peak search which costs a tremendous computational complexity, in this paper, we propose a successive algorithm based on Capon algorithm for non-uniform L-shaped array to avoid the high computational complexity which only needs three one-dimensional spectrum peak search. The successive Capon algorithm has an acceptable performance and can obtain automatically paired 2D DOA estimation for L-shaped array. Extensive simulations have been conducted to verify the usefulness of the algorithm. 1.Introduction The estimation of DOA is one of the fundamental problem in array signal processing and is very important for various engineering applications such as radar, sonar, wireless communication and medical imaging [1][2]. Among the various arrays like the parallel uniform linear array, the rectangular array and the circular array, L-shaped array which consists of two linear subarray connected orthogonally at one end of each array, is commonly used for 2D DOA estimation array as it features a simple structure and can obtain a relatively high estimation accuracy in practice. Thus 2D DOA estimation with L-shaped array has attract a great attention. 2D Capon algorithm exploits the suppression of the noise and interference coming from the direction of the non-sources. And it estimates the DOAs with the signal power invariance criterion. However, it needs 2D spectrum peak search which has a high computational complexity. Ref.[3] addresses a problem of blind 2D DOA estimation with L-shaped array. It links the 2D DOA estimation problem to the trilinear model and gets much better estimation performance. But it has a high computational complexity. In [4], Jiang proposed a reduced-dimension Capon algorithm for planar array which had a low computational complexity. In this paper, we propose the successive Capon algorithm which only needs three one-dimensional search to achieve the 2D DOA estimation and it also has a low computational complexity. The reminder of this paper is organized as follows. In section 2, we present the data model. In section 3, we describe the successive Capon algorithm. Simulation results are presented in section 4 and we conclude this paper in section 5. Notations: Lower-case (upper-case) boldface symbols denote vectors (matrices). ( ) • , ( ) • , 1 ( ) • , ( ) • denote the transpose, the conjugate transpose, the inverse and the pseudo inverse, respectively. ( ) E • denotes the expectation operator.

2D DOA estimation for non-uniform L-shaped array via a successive Capon algorithm