DOA Estimation Using SVDSPM Method Based on Weighted Immune Genetic Algorithm

The 3dB beamwidth of the DOA estimation method based on the singular value decomposition of the signal phase matching principle (SVDSPM) was about 1/3 to 1/2 as much as that obtained by MUSIC at different SNR. However, the SVDSPM algorithm searched the optimal solutions with certain frequency, and the complexity and computational load of optimizing the variables prevented it from applications in the range of unknown wideband. To solve this problem, the simple genetic algorithm (SGA) and the immune genetic algorithm (IGA) are introduced for estimating DOA rapidly, but their stability and accuracy are not enough to implement the high-resolution SVDSPM algorithm. Therefore, a weighted immune genetic algorithm (WIGA) is proposed to optimize the SVDSPM direction finding algorithm, which uses the two-individual mean information entropy for the immune selection, assigns the different weight to each term of the total information entropy at the same loci in a pair of individuals, and constructs a better selection scheme to ensures more various individuals for preserving the diversity of the population. Simulation results show this proposed algorithm performs well in terms of the quality of solution and computational cost.