A novel source localization approach using acoustic energy measurements from the individual sensors in the sensor field is presented. This new approach is based on the acoustic energy decay model that acoustic energy decays inverse of distance square under the conditions that the sound propagates in the free and homogenous space and the targets are pre-detected to be in a certain region of the sensor field. This new approach is power efficient and needs low communication bandwidth and therefore, is suitable for the source localization in the distributed sensor network system. Maximum Likelihood (ML) estimation with Expectation Maximization (EM) solution and projection solution are proposed to solve this energy based source location (EBL) problem. Cramer-Rao Bound (CRB) is derived and used for the sensor deployment analysis. Experiments and simulations are conducted to evaluate ML algorithm with different solutions and to compare it with the Nonlinear Least Square (NLS) algorithm using energy ratio function that we proposed previously. Results show that energy based acoustic source localization algorithms are accurate and robust.
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