2-D DOA Estimation With Imperfect L-Shaped Array Using Active Calibration
Shiyan Liu, Zhang Zhi, Yu Guo
Abstract
The imperfect arrays which cause the manifold matrix of the received signal to be unknown can degrade seriously the performance of traditional direction of arrival (DOA) estimation algorithms. In this letter, we consider an imperfect L-shaped array (LsA) whose two uniform linear arrays are not perpendicular to each other. Specifically, two novel two-dimensional (2-D) DOA estimation algorithms are proposed in this case, where one is using a calibration signal to calibrate the imperfect array according to the array structural features before estimating the DOA by the 2-D MUSIC algorithm, and the other is improving the iterative maximum likelihood (ML) calibration algorithm by linear regression according to the sensor distribution characteristics with the 2-D MUSIC algorithm. Simulation results illustrate that: a) the array calibration accuracy of two proposed algorithms mentioned above outperforms the existing methods, and b) the DOA estimation after array calibration using each of the two algorithms can achieve similar performance to the Cramér-Rao bound (CRB).