Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior  

作　　者：Shanwen Guan Xinhua Lu Ji Li Rushi Lan Xiaonan Luo 

机构地区：[1]Guangxi Key Laboratory of Image and Graphic Intelligent Processing,Guilin University of Electronic Technology,Guilin 541004,China [2]Guilin Huigu Institute of AI Industrial Technology,Guilin 541004,China [3]School of Information Engineering,Nanyang Institute of Technology,Nanyang 473000,China

出　　处：《Tsinghua Science and Technology》2024年第4期1069-1081,共13页清华大学学报自然科学版（英文版）

基　　金：supported in part by the National Natural Science Foundation of China(Nos.6202780103 and 62033001);the Innovation Key Project of Guangxi Province(No.AA22068059);the Key Research and Development Program of Guilin(No.2020010332);the Natural Science Foundation of Henan Province(No.222300420504);Academic Degrees and Graduate Education Reform Project of Henan Province(No.2021SJGLX262Y).

摘　　要：When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

关 键 词：wideband direction of arrival(DOA)estimation sparse Bayesian learning(SBL) unitary approximate message passing(UAMP)algorithm Dirichlet process(DP) 

分 类 号：R36[医药卫生—病理学] R-05[医药卫生—基础医学]