Joint Detection and Direction-of-Arrival Estimation using Bayesian method

Maximum a posterior (MAP) estimator has been shown to perform perfectly for direction-of-arrival (DOA) under the assumption that the number of sources is known. Specifically, in this work we proposed a MAP estimator for DOA, and extend it to a new approach called DDBM for joint detection and DOA estimation simultaneously. Results of both simulation and experiment demonstrate that the proposed method outperforms the AIC and MDL for detection, and also is better than MUSIC and MiniNorm for estimation simultaneously, whereas the computational burden would not aggravate.