Joint DOA and Delay Estimation for 3D Indoor Localization in Next Generation WiFi and 5G
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This paper address the joint direction-of-arrival (DOA) and time delay (TD) estimation problem, which is a key technique for accurate indoor localization in next generation WiFi and 5G networks. We propose an efficient approximate maximum likelihood (AML) algorithm for this problem, which updates the DOA and TD parameters alternatingly. Then, we present closed-form Cramer-Rao bound (CRB) for joint DOA and TD estimation, based on which we provide further analysis to show the benefit of joint DOA and TD estimation over DOA-only estimation. Our analysis is the first theoretical proof of the benefit. Matlab code for the new algorithm is available at https://github.com/FWen/JADE.git.
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