University of Electronic Science and Technology of China/School of Communication and Information Engineering, Chengdu, China

---

Abstract—In most cases, we estimate the direction-ofarrivals (DOAs) of signals by using subspace methods, which obtains DOA estimation through the eigenvalue decomposition of the sample covariance matrix. But when the signals are correlative, the sample covariance matrix is not full rank, and so the subspace methods are not applicable. Using a uniform linear array (ULA), a new method for DOA estimation is proposed in this paper, which can estimate the DOAs of multiple signals in spatially nonstationary uncorrelated noise environment. The method firstly constructs a new covariance matrix by using forward/backward smoothing technique, and then the matrix is transformed and construct the differential covariance matrix. Simulation results show that the proposed method can reduce the influence of the noise and improve the performance of DOA estimation. In addition, it is also applicable to the correlative signals.

Index Terms—DOA estimation, subspace methods, sample covariance matrix, differential covariance matrix, correlative signals

[PDF]

Cite: Jie Zhou, Guangjun Li and Zhi Zheng, " DOA Estimation Method Based on Differential Covariance Matrix," Journal of Computers vol. 8, no. 4, pp. 1078-1082, 2013.