Target detection metrics and tracking for UWB radar sensor networks

A radar sensor network (RSN) is a wireless network system, typically composed of one transmitting (TX) node and several receiving (RX) nodes, aimed at detecting and tracking an intruder (target) moving within a given surveillance area. In this paper, RSNs based on impulse radio ultra-wideband (UWB) are investigated. In the considered system, at each scanning each RX node calculates a soft image of the surveillance area based on the target-scattered UWB pulses. All images are then transferred to a fusion node where the decision about target presence or absence is taken. Optimum decision metrics and likelihood tests are developed, together with approximated metrics reducing the complexity of the detection block. Moreover, it is illustrated how the soft images produced by the RX nodes may be effectively exploited by tracking algorithms relying on Bayesian filters.