This paper presents a simple but high resolution DOA estimation method using second-order differential of MUSIC spectrum. MUSIC method is paid attention as one of "Superresolution" DOA estimation methods because of their brilliant characteristics, however MUSIC also has the problem of estimation accuracy in severe environments like low SNR, small number of snapshots, or incident waves from closely-spaced angles. Especially the case of two or more incident waves from closely-spaced angles, MUSIC often fails in making spectrum peaks that leads inaccurate DOA estimation. We pay attention to the fact that the second-order differential of MUSIC spectrum makes negative peaks around the original DOAs even when MUSIC spectrum does not make peaks there. We try to estimate DOAs not by MUSIC spectrum but by the second-order differential of the MUSIC spectrum, and to find its peaks for being estimated DOAs. The performance of the present method is evaluated in compared with MUSIC and Root-MUSIC methods through computer simulations and experiments.

This paper presents a scheme for accurately detecting the number of incident waves arriving at array antennas. The array antenna and MIMO techniques are developing as 4th generation mobile communication systems and wireless LAN technologies, and the accurate estimation of the propagation environment is becoming more important. This paper emphasizes the accurate detection of the number of incident waves; one of the important characteristics in multidirectional communication. There are some recent papers on accurate detection but they have problems of estimation accuracy or computational cost in severe environment like low SNR, small number of snapshots or waves with close angles. Hence, AIC and MDL methods based on statistics and information theory are still often used. In this paper, we propose an accurate estimation method of the number of arrival signals using the orthogonality of subspaces derived from preliminary estimation of signal subspace. The proposed method accurately estimates the number of signals also in severe environments where AIC and MDL methods can hardly estimate. We evaluate the performance of these methods through some computer simulation and experiments in anechoic chamber.