Multidimensional scaling-based passive emitter localization from time difference of arrival and frequency difference of arrival measurements with sensor location uncertainties

The accuracy of an emitter location estimate is very sensitive to the accurate receiver locations. This paper proposed a novel weighted multidimensional scaling (MDS) algorithm for estimating the position and velocity of a moving emitter with sensor location uncertainties using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. MDS is an attractive technique for robust localization with large measurement noises due to the dimension knowledge and eigen-structure information. This weighted MDS algorithm formulates the localization residual with the linear form of measurement noises and sensor location errors and then uses weighted least squares (WLS) to estimate the location of the emitter. It is closed-form. Simulation results show that the proposed estimator can reach the Cramer-Rao lower bound (CRLB) in small noise region. It achieves better performance than the two-step WLS estimator and constrained total least squares (CTLS) estimator in moderate noise region.