Ground target tracking using terrain information

In this paper a hybrid Kalman filter is derived for the tracking of ground based targets. The propagation is performed using unscented Kalman filter equations, while the updates are performed using extended Kalman filter equations. The novel feature of this hybrid filter is that terrain information has been incorporated to improve the accuracy of state estimates. This information, termed trafficability, incorporates local terrain slope, ground vegetation and other factors to put constraints on the vehicles maximum speed. The estimated velocity vector is deflected based on the trafficability values of nearby locations. Simulations show that the use of trafficability can improve estimated accuracy in locations where the vehicle path is influenced by terrain features.

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