DOA Estimation Method Based on Differential Covariance Matrix
|
| Title | DOA Estimation Method Based on Differential Covariance Matrix |
| Authors | |
| Abstract | In most cases, we estimate the direction-of-arrivals (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. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2013-04-01 |
| Source | Journal of Computers Vol 8, No 4 (2013) |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |