MAXIMUM LIKELIHOOD ESTIMATION OF TARGET ACCELERATION.

David A. Haessig, Bernard Friedland

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

Maximum likelihood failure detection (MLFD) theory is used to estimate the acceleration of a moving target performing an evasive maneuver during an air-to-air interception. Target acceleration is shown to introduce a bias in the residual of the navigation (Kalman) filter. The MLFD algorithm processes this biased residual to detect acceleration transitions, estimate the acceleration subsequent to the transition, and provide a correction term that approximately cancels the error due to target acceleration in estimating the projected miss distance. Simulation results demonstrating for a particular case that the rms terminal miss distance is reduced from 6. 8 to 0. 9 feet by application of the MLFD algorithm are presented.

Original languageEnglish (US)
Pages (from-to)1398-1402
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - Dec 1 1984
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

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