Intelligent ping sequencing for multiple target tracking in distributed sensor fields.

摘要

The problem of determining optimal pinging strategies in multistatic sonar systems with multiple sources is addressed. Algorithms are presented that can be used to determine optimal pinging strategies for generalized search scenarios and for holding confirmed target tracks. An important part of this work is the development of metrics to be used in the optimization procedures. For maintaining search coverage, a "Probability of Target Presence" metric formulation is used. This formulation utilizes sonar performance prediction and a Bayesian update equation to incorporate negative information (i.e., searching an area but finding no targets) into the optimization procedure. The possibility of targets moving into previously searched areas is accounted for by using a Fokker-Planck drift/diffusion formulation. Monte Carlo simulations are used to show the accuracy and efficiency of this formulation. It is demonstrated that by choosing the ping sequence intelligently, the field performance can be improved compared to random or sequential ping sequencing. Strategies are discussed that can be used to increase the performance of a multistatic field, such as the use of bandwidth diversity and track quality.