A Cross-Correlation Matrix-Based MMUSIC Algorithm

Common modified multiple signal classification (MMUSIC) algorithm can decrease the inter-source correlation coefficient to 63% of the original, which can improve the relevant signals direction of arrival (DOA) estimation performance, and does not reduce the observable number of signals. It utilizes only the correlation matrices of observed array signal vectors X and of the corresponding inverse array vectors Y. A new MMUSIC algorithm considering the information contained in the crosscorrelation of vectors X, Y is proposed in the paper. Experiment results show that the new cross-correlation matrix based MMUSIC algorithm can enhance the ability of identifying small space interval (about 3deg) signals and improve the DOA estimation performance, such as the estimation deviation decreases about 0.05deg when the SNR=10 dB with 200 snapshots for 11-element linear array. The proposed method can also be referred to as the first step towards the user´s location distribution sensing of cognitive radio system.