The problem of Doppler-based target position and velocity estimation using a sensor network is outlined. The minimum number of Doppler-shift measurements at distinct generic sensor positions in order to have a finite number of solutions, and later, a unique solution for the unknown target position and velocity are stated analytically. Furthermore we study the same problem, where not only Doppler-shift measurements are collected, but also other types of measurements are available, e. g,. bearing or distance to the target from each of the sensors. Later we study the Cramer-Rao inequality associated with the Doppler-shift measurements to a target in a sensor network, and we use the Cramer-Rao bound to illustrate some results on optimal placements of the sensors when the goal is to estimate the velocity of the target. Some simulation results are presented at the end.

This paper outlines the problem of doppler-based target position and velocity estimation using a sensor network. The minimum number of doppler shift measurements at distinct generic sensor positions to have a finite number of solutions, and later, a unique solution for the unknown target position and velocity is stated analytically, for the case when no measurement noise is present. Furthermore, we study the same problem where not only doppler shift measurements are collected, but also other types of measurements are available, e.g. bearing or distance to the target from each of the sensors. Subsequently, allowing nonzero measurement noise, we present an optimization method to estimate the position and the velocity of the target. An illustrative example is presented to show the validity of the analysis and the performance of the estimation method proposed. Some concluding remarks and future work directions are presented in the end.

This paper outlines the problem of multi-static Doppler-based target position and velocity estimation. The Fisher information matrix is derived given a separate target illuminator and then given a target-based isotropic signal emission. Some remarks concerning the Cramer-Rao inequality and its relationship to the estimation problem are given. Some results concerning the placement of the receivers are given and some open problems are discussed.

This paper provides an investigation of the fundamental and practical distinctions between state estimates obtained by using the positional components of a phased array radar (PAR) measurements versus the estimate obtained by using the additional Doppler component. By employing the Doppler component of PAR measurements several significant improvements in tracking system performance are practically achievable including: lower state estimate uncertainty, increased measurement origin certainty, increased identifiability of target maneuvers and increased tracking system robustness.