This paper compares six different algorithms for target maneuver
detection in a number of typical maneuvering target tracking
scenarios. Measurement residual based chi-square test, input
estimate based chi-square test, input estimate based significance
test, generalized likelihood ratio, cumulative sum, and
marginalized likelihood ratio detectors are examined. Maneuver
onset detection times and ROC curves are presented and performance
measures are discussed through simulations. Further, the effect of
different window sizes on detection performance is evaluated.
Proc. SPIE. 5204, Signal and Data Processing of Small Targets 2003
KEYWORDS: Statistical analysis, Data modeling, Error analysis, 3D modeling, Monte Carlo methods, Particle filters, Statistical modeling, Performance modeling, Systems modeling, Filtering (signal processing)
The authors have developed a toolbox for hybrid estimator evaluation which allows rapid comparison of algorithms in different scenarios. The toolbox is flexible in implementing, simulating, and evaluating various algorithms, particularly those for hybrid estimation - state estimation under parametrical and/or structural uncertainties. While the toolbox is extensible, numerous models, filters, estimators, and error measures are provided by default. In this paper, examples are given of short programs written in Matlab that illustrate some of the benefits that such a toolbox can bring to researchers.