Minimization of sensor usage for target tracking in a network of irregularly spaced sensors

We address the following scenario: a single target moves through a field of stationary sensors with known locations. At each time epoch, each sensor is either active or not; each active sensor outputs either target detected or not detected. The probability of target detection is a decreasing function of the distance from a sensor to the target. A particle filter is used to track the target through the sensor field using all active sensor outputs. A heuristic configuration strategy is used to determine which sensors should be activated; Monte Carlo simulations show that the configuration strategy leads to a significant reduction in required active sensors with little degradation in the tracker performance.