Management of target-tracking sensor networks
Binary proximity sensors are an inexpensive approach to target tracking in cyber-physical and other applications. In this paper, we use analysis and simulation to study tradeoffs in the management of such networks. The use of simple averaging is compared against a more complex convex hull calculation for position estimation. We model the impact of sensor density on the accuracy of the position estimate and present performance results associated with the choice of sampling period and sensor wakeup area. We provide an iterative filtering approach to protect against false positives. We also model the effect of a non-uniform sensor scatter.
sensor networks target tracking binary sensing probabilistic waking