Evolutionary control of an autonomous field

An autonomous field of sensor nodes needs to acquire and track targets of interest traversing the field. Small detection ranges limit the detectability of the field. As detections occur in the field detections are transmitted acoustically to a master node. Both detection processing and acoustic communication drain a node´s power source. In order to maximize field life, an approach must be developed to control processes carried out in the field. In this paper we develop an adaptive threshold control scheme. This technique will minimize the power consumption while still maintaining the field-level probability of detection. The power consumption of the field of sensor nodes is driven by the false alarm rate and target detection rate at the individual sensor nodes in this problem formulation. The control law to be developed is based upon a stochastic optimization technique known as evolutionary programming. At the end of the paper, a set of results are presented that will show that by dynamically adjusting sensor thresholds and routing structures, the controlled field will have twice the life of the fixed field.