Search performance prediction for multistatic sensor fields

An existing search performance model for distributed passive sensor networks is extended to multistatic sensor networks comprised of active sources and passive receivers. The model provides an upper bound on the detection range of a receiver in the field, and uses this bound to compute the expected probability of successful search for a given target track. This expected probability depends on the numbers of sources and receivers in the field, their location distribution functions, and the location and orientation of the track. For uniformly (randomly) distributed sources and receivers, the distribution function for the upper bound on receiver detection range can be computed analytically in closed form. We show that the resulting estimates of probability of successful search for uniformly distributed multistatic fields is a reasonable approximation to more accurate values obtained via Monte Carlo simulation for various numbers of sources and receivers, and for various numbers of required detections. We conclude with a discussion of how this model may be used in designing and planning multistatic systems for undersea surveillance.