Performance Comparison of the IMMPDAF Algorithm Using Real and Simulated Radar Measurements

Marcelo Lucena de Souza, Alberto Gaspar Guimarães, Ernesto Leite Pinto


Performance indexes obtained in idealized simulated scenarios are the primary source of data for evaluating different target tracking algorithms in most researches presented in the literature. Despite the convenience of simulation, ultimate evaluation of a tracking algorithm must be made in real scenarios. Unfortunately, real radar measurements as well as accurate aircraft position, necessary for calculating tracking errors, are not easily available. In this paper, we present an evaluation of the well-known Interacting Multiple-Model with Probabilistic Data Association Filtering algorithm using data obtained from a flight inspection of a Brazilian Air Force ground-based long-range surveillance radar. The presented results show that, in this scenario the Interacting Multiple-Model with Probabilistic Data Association Filtering algorithm performance using real data is worse compared to simulation. Statistical properties of the real radar measurements are also investigated, and some evidence is found that embedded noise is not well modeled as perfectly white.


Radar tracking; State estimation; Data simulation; Radar data

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