An approximate minimum MOSPA estimator
Paper in proceedings, 2011

Optimizing over a variant of the Mean Optimal Subpattern Assignment (MOSPA) metric is equivalent to optimizing over the track accuracy statistic often used in target tracking benchmarks. Past work has shown how obtaining a Minimum MOSPA (MMOSPA) estimate for target locations from a Probability Density Function (PDF) outperforms more traditional methods (e.g. maximum likelihood (ML) or Minimum Mean Squared Error (MMSE) estimates) with regard to track accuracy metrics. In this paper, we derive an approximation to the MMOSPA estimator in the two-target case, which is generally very complicated, based on minimizing a Bhattacharyya-like bound. It has a particularly nice form for Gaussian mixtures. We thence compare the new estimator to that obtained from using the MMSE and the optimal MMOSPA estimators.

Author

David Crouse

P. Willett

Marco Guerriero

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Proc. 36th international conference on acoustics, speech and signal processing, ICASSP 2011; Prague; 22 May 2011 through 27 May 2011

Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Probability Theory and Statistics

Other Electrical Engineering, Electronic Engineering, Information Engineering

More information

Created

10/7/2017