DOA Estimation and Separation of Multipath Wideband Signal Based on Parallel Factor Model

In complex multipath environments, accurate direction of arrival (DOA) estimation for wideband signal and effectively separating the main path signal remain challenging problems. This paper addresses this issue by leveraging the parallel factor (PARAFAC) model fitting and the multi-frequency characteristics of wideband signal. Firstly, the PARAFAC model is constructed based on the wideband array output to suppress the noise influence. The propagation matrix, which includes DOA and time delay information, is then separated using a trilinear alternating least squares method. Subsequently, accurate DOA estimation and time delay vectors are obtained using a distributed compressed sensing approach. Finally, the multi-frequency characteristics of the wideband signal are employed to distinguish the main path of the multipath signal based on time delay differences among different paths. Both simulation and practical tests are conducted to verify the superiority of the proposed method compared to other state-of-art methods.