Collaborative Direction-of-Arrival Estimation Exploiting One-Bit Cross-Correlations
Yimin Daniel Zhang, Ashley Prater-Bennette · 2021 55th Asilomar Conference on Signals, Systems, and Computers · 2021
In this paper, we consider a collaborative direction-of-arrival (DOA) estimation problem in which multiple quasi-collocated subarrays are employed. Our objective is to effectively utilize the full potential offered by the distributed array with minimum communication traffic between the subarrays and the processing center. In the proposed scheme, each subarray computes the self-subarray covariance matrix with the full precision. Each subarray then sends the estimated covariance matrix together with the one-bit version of the raw data to the processing center. The processing center computes the cross-subarray covariance matrices between different subarrays based on the one-bit data, which, together with the self-subarray covariance matrices which are computed and reported by the subarrays, are used to estimate the source DOAs. The combined exploitation of the full-precision self-subarray covariance matrices and the low-precision cross-subarray covariance matrices ensures full degrees of freedom offered by the array with only slight performance loss compared with the case where all covariance matrices are provided with full precision.