Sensor Management Research
Abstract
This grant is supporting development of mathematical foundations for sensor management systems. This year's accomplishments are in three areas: Extension of a Kalman-filter based discrimination metric to interacting multiple model filters; extension of sensor management based on Joint Multitarget Probabilities to incorporate multiple sensor modes and target classification; and development of fast methods to solve the Fokker-Planck equation for real-time non-linear filtering applications. To support sensor management representations of multitarget probability densities must be developed that model the uncertainty between quantities such as the number of targets, their locations and their class. To solve this problem and study it in a simple setting, the notion of Joint Multitarget Probabilities for detection, tracking, and target classification was developed and tested. In certain cases the time-evolution of these probabilities is characterized by a partial differential equation called the Fokker-Planck equation leading to a nonlinear filter. Several prototype nonlinear filters using the Alternating Direction Implicit scheme to solve the Fokker-Planck equation in real-time were formulated. In these applications it seems to offer significant improvement in estimation performance at a supportable cost in computational load.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 31, 1997
- Accession Number
- ADA336869
Entities
People
- Avner Friedman
- Keith Kastella
Organizations
- University of Minnesota