Comparison of a jump-diffusion tracker with a Kalman tracker: an evaluation with emphasis on air traffic control

Comparison of a jump-diffusion tracker with a Kalman tracker: an evaluation with emphasis on air traffic control

Blom, H.A.P.

National Aerospace Laboratory NLR

1983-03-30

A sophisticated starting point for a probabilistic approach to the radar tracking problem is a Markov jump-diffusion model for the aircraft dynamics, its control and the radar measurements. From nonlinear filtering theory, a closed form description of the evolution of the conditional distribution of this Markov process can be obtained. This jump-diffusion filter, however, is infinite dimensional and approximations are necessary for algorithmic implementation. The indirect approach of approximating the jump-diffusion by a diffusion leads to a Kalman-like tracker. The recently developed approach of approximating the jump-diffusion filter directly, leads to a bank of interacting Kalman-like trackers. The report is directed to the evaluation of tracking algorithms that are based on these two approaches. Their results are compared in an air traffic control environment. It is concluded that the jump-diffusion' tracker performs considerably better than the Kalman tracker.

tracking position
tracking filters
jump detection
kalman filters
diffusion theory
monte carlo method
markov processes
air traffic control
radar tracking
clutter
surveillance radar
flight paths
turning flights
aircraft manoeuvres
algorithms
standard deviation

http://resolver.tudelft.nl/uuid:5fb7e72d-9e47-4792-99d6-377ce67df954

Nationaal Lucht- en Ruimtevaartlaboratorium

Campus only

NLR-TR 83063 U

Aerospace Engineering Reports

report

(c) 1983 National Aerospace Laboratory NLR