Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field

摘要: In this paper, we derive the maximum-likelihood (ML) location estimator for wideband sources in near field of sensor array. The ML is optimized a single step, as opposed to other estimators that are separately relative time-delay and source estimations. For multisource case, propose demonstrate an efficient alternating projection procedure based on sequential iterative search single-source parameters. proposed algorithm shown yield superior performance over suboptimal techniques, including MUSIC two-step least-squares methods, with respect derived Cramer-Rao bound (CRB). From CRB analysis, find better estimates can be obtained high-frequency signals than low-frequency signals. addition, large range estimation error results when signal unknown, but such unknown parameter does not have much impact angle estimation. some applications, locations sensors may must estimated. method extended estimate from location. After number source-location frames, uncalibrated determined estimator.