Adaptive target tracking using multistatic sensor with unknown moving transmitter positions

Abstract

It is desirable for a sensor to keep silent to avoid being detected. Passive tracking is therefore preferred as it estimates target trajectories through “listening” to the signals emitted by others without any emission. The multistatic concept can be used for this application, where the receiver (or the listener) is considered as own sensor, and the transmitters can be emitters deployed on stationary or moving platforms. Such a multistatic system requires the positions of the transmitters to be known by the receiver. Unfortunately, this is not always true for non-cooperative transmitters (especially for moving transmitters), who do not inform the receiver their positions timely. This paper proposes a multistatic configuration with a receiver and two transmitters with unknown position. This configuration can provide good observability for the trajectories of the transmitters and targets based on the measured bearings and the time-difference-of-arrival (TDOA) of the direct and indirect path signals. A two-stage unscented Kalman filter (UKF) is developed to track the transmitters and target simultaneously. Unlike the algorithms from the literature which assume known transmitter positions, the algorithm of this paper estimates the state of the target while adapting itself to the moving transmitters' locations. Simulation tests are conducted to show the filter performance.