MUSIC-Like DOA Estimation Without Estimating the Number of Sources

摘要

This paper presents a new direction-of-arrival (DOA) estimation algorithm, where DOA estimation is realized in the framework of beamforming by introducing a new optimization problem. The new optimization problem aims to minimize the variance of the array output subject to retaining the output power at the look direction and precluding a trivial solution. The proposed algorithm is equivalent to the multiple signal classification (MUSIC) algorithm in some special cases, it is therefore named as the MUSIC-like method. However, different from the classical MUSIC algorithm, the new method is not based on subspace decomposition and the number of sources is hence not required for direction finding. This enables us to avoid performance deterioration caused by incorrect source number estimation. The effectiveness and advantage of the proposed algorithm is theoretically investigated, and computational complexity is also addressed. To verify the theoretical analysis, computer simulations are implemented and comparisons with other algorithms are made.