Fast subspace algorithm for two-dimensional DOA estimation

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作者：

Wuhan National Laboratory for Optoelectronics, Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China ^{[1
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来源：

Huazhong Ligong Daxue Xuebao | 2008年 / 4卷 / 20-23期

关键词：

Computer simulation - Covariance matrix - Signal processing - Signal to noise ratio;

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摘要：

A fast subspace algorithm for two-dimensional DOA (direction of arrival) estimation is presented, in which the signal subspace of reduced dimension from a submatrix of the array covariance matrix can be obtained without eigen-decomposition. It only needs to estimate the subarray covariance matrix instead of the whole array covariance matrix, thereby indicating that the algorithm is computationally advantageous and more easily realization. The algorithm is suitable for application in short-time sampled data and fast time-varying environments. Theoretical analysis and computer simulation results show that the computation load of the new algorithm is one fourth of that of the basic MUSIC algorithm. Compare to MUSIC, there is slight degradation of performance in low SNR (signal-to-noise ratio), having similar performance when SNR is more than 5 dB.

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