A New Heterogeneous Track Fusion with Information Decorrelation Algorithm for Target Tracking in a Multistatic Sensor System with Non-Cooperative Moving Transmitters

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1 June 2020

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This paper considers a target tracking problem in a non-cooperative multistatic system, where several transmitters are moving and their positions are unknown. The receiver listens to the signals from non-cooperative transmitters via direct and indirect (bouncing from targets) paths. The transmitters and targets are then tracked based on the measured bearings and the bistatic ranges (derived from the time difference of arrival of the direct and indirect path signals) simultaneously. In previous work, we proved that the transmitter trajectories are observable when the two transmitters are not located on the same line from the receiver, and developed an approximate algorithm to perform estimation based on covariance inflation (CI). In this paper, a new estimation algorithm, heterogeneous track fusion with in-formation decorrelation (HTF-D), is developed. It aims to achieve optimal estimates without using a large augmented state consisting of all transmitter and target states. The approach tracks targets individually, and fuses these highly correlated tracks through a novel information decorrelation method. The performance of the HTF-D is evaluated through simulation tests. The results show that the HTF-D provides better estimates than the CI algorithm, and achieves the same accuracy as the optimal algorithm when the latter does not suffer from numerical problems due to its large augmented state. The HTF-D estimates are also consistent statistically.