Paper
4 May 2009 The extended preferred ordering theorem for precision acquisition tracking and pointing
Donald M. Leskiw, Hong Wang
Author Affiliations +
Abstract
In radar tracking, the Preferred Ordering Theorem for updating the state vector in rectangular coordinates using an Extended Kalman Filter states that the measurement components of a detection should be used sequentially in the order azimuth first, then elevation, and range last. Such is counterintuitive to a common belief that the most accurate measurement should be used first, since that is usually range. However, it is observed here that the theorem can lose its efficacy as a track converges - and that the expected value of an EKF update is not always well-defined. An "extension" is therefore given, which is dubbed the DKF after Desargues, since it is based on an analysis involving projective geometry. With this approach the conditional update of a track in rectangular coordinates becomes well defined in the sense that a preferred order is obviated, and it can now be updated using a range or angle observation, separately or sequentially in either order, with less error. In this presentation the basic issues are illustrated, and the DFK is defined and contrasted with the EKF for the two-dimensional motionless target case.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Donald M. Leskiw and Hong Wang "The extended preferred ordering theorem for precision acquisition tracking and pointing", Proc. SPIE 7338, Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIII, 73380G (4 May 2009); https://doi.org/10.1117/12.819046
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Cited by 1 scholarly publication.
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KEYWORDS
Radar

Matrices

Filtering (signal processing)

Acquisition tracking and pointing

Monte Carlo methods

Particle filters

Statistical analysis

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