CANDECOMP&PARAFAC-based Near-Field Source Localization by Passive Sensor Arrays

Abstract

This paper discusses the singular source’s Direction-Of-Arrival (DOA) and Direction-Of-Distance (DOD) estimation method based on a tensor decomposition algorithm in the near-field situation. With the assistance of the uniqueness of tensor decomposition, the proposed method achieves a high-accuracy performance in both DOA and DOD estimations. For Uniform Linear Arrays (ULA), the steering vector of near-field sources is determined by both angle and distance parameters. Two modified models are built for DOA and DOD estimations respectively and each of them contains only one parameter. These two models are furtherly turned to tensor models by cutting to slices. Rank-l tensor approximation Alternating Least Squares (ALS) algorithms are then used to estimate DOA and DOD for its general global convergence property. The results are used for localization and numerical simulations have verified the effectiveness of the proposed method.