Joint Source Localization and Association Through Overcomplete Representation Under Multipath Propagation Environment
Yuan Liu, Zhi-Wei Tan, Andy W. H. Khong, Hongwei Liu
Abstract
This work addresses the source localization and association problem in a multipath propagation environment. By focusing on the limitation of the prior information in practical applications, we propose a target localization and association method based on iterative optimization with semi-unitary constraint and eigen-decomposition techniques. In contrast to the previous works, the proposed method can localize spatial sources and associate the incident paths to each source without prior knowledge pertaining to the propagation environment. Moreover, the proposed approach can be applied to an arbitrary array geometry without reducing the effective array aperture. Both simulations and real data experiments validate the effectiveness and robustness of the proposed method.