Detection of mobile targets on the plane and in space using heterogeneous sensor networks.

Detection of targets moving within a field of interest is a fundamental service Wireless Sensor Network (WSN) service. The WSN’s target detection performance is directly related to the placement of the sensors within the field of interest. In this paper, we address the problem of deterministic sensor deployment on the plane and in space, for the purpose of detecting mobile targets. We map the target detection problem to a line-set intersection problem and derive analytic expressions for the probability of detecting mobile targets. Compared to previous works, our mapping allows us to consider sensors with heterogeneous sensing capabilities, thus analyzing sensor networks that employ multiple sensing modalities. We show that the complexity of evaluating the target detection probability grows exponentially with the network size and, hence, derive appropriate lower and upper bounds. We also show that maximizing the lower bound on the probability for target detection on the plane and in space, is analogous to the problem of minimizing the average symbol error probability in two-dimensional and three-dimensional digital modulation schemes, respectively, over additive white Gaussian noise. These problems can be addressed using the circle packing problem for the plane, and the sphere packing problem for space. Using the analogy to digital modulation schemes, we derive sensor constellations from well known signal constellations with low average symbol error probability. [ABSTRACT FROM AUTHOR]