A Fast Direction Finding Algorithm Based on Correlation Processing

To reduce the computational complexity of direction finding algorithms based on correlation processing, a fast algorithm is presented in this paper. Unlike the conventional direction finding algorithms which calculates the correlation coefficients in the whole azimuth range, the improved algorithm measure the direction of arrival (DOA) roughly first, then, measure the DOA only in finite angle interval and searches the maximal correlation coefficient, thus shorten the execution time greatly. In addition, the algorithm has no influence on the accuracy of direction finding. The best proportion between samples for rough measurement and samples for fine measurement is analyzed. Computer simulation results confirm that the proposed method can shorten the computation time greatly, and the proposed algorithm has practical application value in the instantaneous direction finding.