Planning a search for moving ground targets is difficult for humans and computationally intractable. This paper describes a technique to solve such problems. The main idea is to combine probability of detection assessments with computational search heuristics to generate sensor plans which approximately maximize either the probability of detection or a user- specified knowledge function (e.g., determining the target's probable destination; locating the enemy tanks). In contrast to super computer-based moving target search planning, our technique has been implemented using workstation technology. The data structures generated by sensor planning can be used to evaluate sensor reports during plan execution. Our system revises its objective function with each sensor report, allowing the user to assess both the current situation as well as the expected value of future information. This capability is particularly useful in situations involving a high rate of sensor reporting, helping the user focus his attention on sensors reports most pertinent to current needs. Our planning approach is implemented in a three layer architecture. The layers are: mobility analysis, followed by sensor coverage analysis, and concluding with sensor plan analysis. It is possible using these layers to describe the physical, spatial, and temporal characteristics of a scenario in the first two layers, and customize the final analysis to specific intelligence objectives. The architecture also allows a user to customize operational parameters in each of the three major components of the system. As examples of these performance options, we briefly describe the mobility analysis and discuss issues affecting sensor plan analysis.

Date Published: 6 October 1994
PDF: 11 pages
Proc. SPIE 2355, Sensor Fusion VII, (6 October 1994); doi: 10.1117/12.189073

Published in SPIE Proceedings Vol. 2355:
Sensor Fusion VII
Paul S. Schenker, Editor(s)