Recently, Doppler radars have been used in various applications from the detection and the classification of indoor human activities to the detection of airplanes. To improve both the degrees of freedom (DOF) and the estimation accuracy of the direction-of-arrival (DOA) of targets, multiple-input multiple-output (MIMO) radar has received much attention in recent years. The temporal spatial virtual array based on Doppler shift of a moving target has been one of methods to improve DOA estimation accuracy. However, the DOA estimation accuracy based on the method depends on the velocity and the direction of the target on which we focus. Also, the temporal spatial virtual array should be generated based on the information of the single target. Thus, it is difficult to implement the method if there are multiple targets. In this paper, we propose a new method that provides high accuracy of DOA estimation by using the temporal spatial virtual array without dependence on the velocity, the direction and the number of existing targets. We demonstrate the DOA estimation accuracy and the effectiveness of the proposed method via simulations.

We propose a new direction-of-arrival (DOA) estimation method of wideband signals. In several decades, many approaches to estimate DOA of wideband signal sources have been proposed. Test of orthogonality of projected subspaces (TOPS) and Squared TOPS are the estimation algorithms to realize high resolution performance of closely spaced signal sources. These methods, however, are not suitable for DOA estimation of multiple signal sources, because the spatial spectrum calculated by Squared TOPS has some false peaks. Therefore, the authors have proposed the weighted squared TOPS (WS-TOPS) to suppress these false peaks by modifying the orthogonality evaluation matrix, WS-TOPS also achieves better DOA estimation accuracy than that of Squared TOPS. On the other hand, WS-TOPS has a drawback, it requires high computational complexity. Our new method can realize good DOA estimation performance, which is better than that of Squared TOPS, with low computational complexity by reducing the size of orthogonality evaluation matrix and the number of subspaces to be used. Simulation results show that the new method can provide high resolution performance and high DOA estimation accuracy with low computational complexity.