Nonlinear Filtering for Ground Target Applications

نویسندگان

  • Keith Kastella
  • Chris Kreucher
  • Michael A. Pagels
چکیده

This paper describes a nonlinear filter for ground target tracking. Hospitability for maneuver derived from terrain, road and vehicle dynamics constraints is incorporated directly into the filter's motion model. The conditional probability density for the target state is maintained and updated with sensor measurements as soon as they become available. The conditional density is time updated between sensor measurements using finite difference methods. In simulations using square-law detected measurements the filter is able to track maneuvering ground targets when the Signal to Interference + Noise Ratio (SINR) is between 6 and 9 dB.

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تاریخ انتشار 2000