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Performance Comparison of Maneuver Detection Algorithms

  • Sebastian Bayerl
  • Georg Herbold
  • Lorenzo Pettazzi
Conference paper

Abstract

This paper compares several algorithms for target maneuver detection. The algorithms are based on input estimation coupled with Kalman filter or IMM filtering. The performance of each method is analyzed computing a Pareto frontier, which is based on different quality criteria such as root mean square (rms) of state estimation error and time of maneuver detection. It is shown that computation of such Pareto frontiers allows to compare the performance of the different detectors in a systematic way.

Keywords

Pareto Frontier Unknown Input Detection Delay State Estimation Error Input Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sebastian Bayerl
    • 1
  • Georg Herbold
    • 2
  • Lorenzo Pettazzi
    • 3
  1. 1.Deggendorf University of Applied SciencesDeggendorfGermany
  2. 2.MBDA / LFK-Lenkflugkörpersysteme GmbHUnterschleißheimGermany
  3. 3.European Organisation for Astronomical Research in the Southern HemisphereGarchingGermany

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