Acoustic Energy-based Sensor Localization With Unknown Transmit Energy Levels

Abstract

When the transmit energy levels are unavailable, semidefinite programming (SDP), mixed second order cone programming and semidefinite programming (SOC/SDP) and the linear least square estimator with source-anchor measurements (LLS-SA) are proposed to estimate the source locations in the wireless sensor networks. The proposed three algorithms avoid the shortcoming of the maximum likelihood (ML) estimator which requires the initial solution guess to ensure the global convergence. The simulations show that the convex optimisation algorithms including the SDP and SOC/SDP provide more robust solutions to the source location estimates compared with the linear estimator of LLS-SA. However, the proposed LLS-SA runs faster than the SDP and SOC/SDP. The accuracy performance of the designed SOC/SDP is similar to that of the SDP, but the complexity of the SOC/SDP is greatly lower than that of the SDP for the same network configuration.