| Paper: | SAM-P4.7 | ||
| Session: | Direction-of-Arrival Estimation | ||
| Time: | Wednesday, May 19, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Beamforming, direction-of-arrival estimation, and space-time adaptive processing | ||
| Title: | IMPROVING THE ROBUSTNESS OF THE RARE ALGORITHM AGAINST SUBARRAY ORIENTATION ERRORS | ||
| Authors: | Sherif Abd Elkader; McMaster University | ||
| Alex Gershman; McMaster University | |||
| Kon Max Wong; McMaster University | |||
| Abstract: | We study the problem of direction-of-arrival (DOA) estimation using partly calibrated arrays composed of multiple subarrays with unknown inter-subarray parameters and imperfectly known subarray orientations. The recently developed spectral and root variants of the rank reduction estimator (RARE) can handle scenarios where no calibration between subarrays is available but, unfortunately, they are very sensitive to subarray orientation errors. Therefore, conventional RARE can be applied to such partly calibrated arrays only if all subarray misorientations are negligibly small. In this paper, we develop a new modification of RARE which improves its robustness against subarray misorientations. The performance of the proposed robust RARE algorithm is demonstrated to be close to the stochastic Cramer-Rao bound (CRB) of the considered estimation problem. | ||
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