Oceanographic effects on optimized multistatic sonobuoy fields

Optimal monostatic sonobuoy fields were developed during the Cold War for deep, uniform undersea environments, where a simple median detection range defined a fixed spacing between sonobuoys. Oceanographic and acoustic conditions in littoral environments are so complex and dynamic that spatial and temporal variability destroys the basic homogeneous assumption associated with standard tactical search concepts. There have been several attempts to design near-optimal placements of passive and monostatic-active sonobuoys. Most of these are evaluation algorithms, as opposed to true planning algorithms. Recently, genetic algorithms (GA) were successfully applied to monostatic mobile sensors to produce near-optimal, non-standard search tracks for multiple searchers in complicated environments [D.P. Kierstead and D.R. DelBalzo, Military Operations Research Journal (March/April 2003)]. For the present work, we developed a new capability, SCOUT (Sensor Coordination for Optimal Utilization and Tactics) to optimize the locations and ping times of multistatic active sonobuoys in a complex, littoral environment. We made two major modifications to the mobile-sensor GA approach to account for bistatic sonobuoy fields. The first was in the structure, where we added a new chromosome to describe the bistatic search plan. It has one gene for each sonobuoy, consisting of a location and two ping times. Positions and times in the new chromosome mutate independently. The second modification was in detection modeling, where we incorporated a model for bistatic detection. For this work, we postulated that all sonobuoys could be monitored simultaneously, and that each was capable of bistatic detection from any of the other sonobuoy's sources. The SCOUT algorithms are an extension to our previous GA work and to the best of our knowledge they represent the only solution that designs sonobuoy placements in complicated environments from scratch, as opposed to recommending general effort allocations or simply evaluating standard patterns with different parameters. This paper discusses the new chromosome structure and initial simulation results. The results show a) that standard patterns are not optimal even for a homogeneous environment and b) that standard patterns are grossly ineffective in inhomogeneous environments where 20% improvements in detection are achieved with SCOUT.