TDOA-based Target Localization Under Distance-dependent Noise Model

Abstract

This paper focuses on target localization utilizing time difference of arrival (TDOA) measurements in 2-dimensional spaces. Differently from existing researches that the variance of TDOA measurement noise is independent of sensor-to-target distance, we set up the more practical model under the model of the distance-dependent noises. Firstly, we derive maximum likelihood estimator (MLE) and the Cramer-Rao lower bound (CRLB). Then, this instrumental variable (IVE) and this pseudolinear estimator (PLE) are introduced. Finally, simulation results show the bias norm and RMSE performance of PLE, IVE and MLE, and compared with the CRLB.