Sequential algorithm for extended H∞ filter-based target tracking in wireless sensor networks

The extended H
_∞
filter is usually used to target tracking applications in the case of having no knowledge of the statistics of sensor measurements and the maneuvering properties of the target. In this paper, we present a target tracking approach in wireless sensor networks based on the sequential implementation of the extended H
_∞
filter. At every time instant each sensor in the current tracking cluster except the last one sequentially updates the target state based on the target state estimate received from the previous sensor and its measurement using the extended Kalman filter, then transmits its estimated result to the next sensor. The last sensor achieves the resultant target state estimate based on the extended H
_∞
filter. Simulations results show that the proposed target tracking approach can achieves the same tracking accuracy as the centralized H
_∞
filter-based tracking approach, but averages the energy consumption in the cluster.