Self-Calibration Algorithm for Receiver Position Error in Passive Source Localization

Receiver position error is known to degrade significantly the passive source localization accuracy. A new algorithm based on self-calibration of receiver position error is proposed. The Cramer-Rao Lower Bound of source location estimate under Gaussian noise model is derived. Using Taylor series expansion, a linear equation is established and the LMMSE estimator of receiver position error is obtained. The receiver position is improved and the estimate of the source location is achieved by Chan location algorithm. Simulation results indicate that the proposed solution reaches an accuracy close to the CRLB under Gaussian noise.