Multidimensional MUSIC DOA estimation using ant colony optimization algorithm

The estimation of the direction-of-arrival (DOA) of signals is an important issue in array signal processing. A multidimensional version of MUSIC (MD-MUSIC) algorithm is a well known excellent algorithm for DOA estimation. However, this algorithm is totally impractical for its prohibitive computational burden incurred by multi-dimensional grid search. In order to solve this problem, ant colony optimization (ACO) is introduced to combine with the MD-MUSIC algorithm, and a new algorithm with lower computational burden called ACOMD-MUSIC is proposed. In this proposed algorithm, a kind of continuous pheromone probability distribution (Gaussian kernel probability density function) in the sampling process is used. The global maximum of MD-MUSIC spatial spectrum function could be reached after reasonable iterations. Simulation results illustrate that the proposed algorithm provides similar performance as MD-MUSIC algorithm, while its computational cost is only 1/13 of MD-MUSIC algorithm.