Realtime Control of Multiple Sensor Systems

Project will develop methods for the optimal management of sensor systems. As a specific application, we consider the nonlinear filtering of a vector diffusion process, with several noisy vector observations. Any number of sensors can be utilized in the signal processing performaned by the nonlinear filter. The problem considered is the optimal selection of a schedule of these sensors from the available set, so as to optimally estimate a function of the state at the final time. We will design algorithms for the solution to produce optimal sensor schedules. In Phase I we shall consider a limited number of sensors designed to intercept radar signals. Benefits will include realtime, feedback control procedures for sensor management, and data fusion. Algorithms for managment of complex systems of sensors will find commercial application in large scale industrial processes, especailly for quality control and fault detection.