AbstractThe problem of moving target localization from range and velocity difference measurements has attracted considerable attention in recent years. In this article, a novel weighted multidimensional scaling (MDS) algorithm is proposed to estimate the position and velocity of a moving target by utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements with sensor position and velocity errors. The proposed estimator is based on the optimization of a cost function related to the scalar product matrix in classical MDS. The estimator is accurate and closed form. The algorithm has a small mean square error compared with the 2-step weighted least squares (LS) algorithm in a moderate and high noise power level.