2017/04/20 by Wassim Suleiman, Suleiman, Wassim, Pouyan Parvazi +5
Computer Science · Engineering · #Antenna Design and Optimization #Applications (stat.AP) #Direction-of-Arrival Estimation Techniques #FOS: Computer and information sciences #Speech and Audio Processing
paper · pdf · doi:10.48550/arxiv.1704.06000
openalex publication_date 2017/04/20 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
In this paper, direction-of-arrival (DOA) estimation using non-coherent\nprocessing for partly calibrated arrays composed of multiple subarrays is\nconsidered. The subarrays are assumed to compute locally the sample covariance\nmatrices of their measurements and communicate them to the processing center. A\nsufficient condition for the unique identifiability of the sources in the\naforementioned non-coherent processing scheme is presented. We prove that,\nunder mild conditions, with the non-coherent system of subarrays, it is\npossible to identify more sources than identifiable by each individual\nsubarray. This property of non-coherent processing has not been investigated\nbefore. We derive the Maximum Likelihood estimator (MLE) for DOA estimation at\nthe processing center using the sample covariance matrices received from the\nsubarrays. Moreover, the Cramer-Rao Bound (CRB) for our measurement model is\nderived and is used to assess the presented DOA estimators. The behaviour of\nthe CRB at high signal-to-noise ratio (SNR) is analyzed. In contrast to\ncoherent processing, we prove that the CRB approaches zero at high SNR only if\nat least one subarray can identify the sources individually.\n