Multidimensional SME filter for multitarget tracking

Douglas J. Muder; Sean D. O'Neil

doi:10.1117/12.157789

22 October 1993 Multidimensional SME filter for multitarget tracking

Douglas J. Muder, Sean D. O'Neil

Proceedings Volume 1954, Signal and Data Processing of Small Targets 1993; (1993) https://doi.org/10.1117/12.157789
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Kamen et al. have developed the symmetric measurement equation (SME) filter as an alternative to multi-target trackers based on data association. This paper presents an improved multi-dimensional SME tracking algorithm which agrees with Kamen's for one-dimensional scenarios and avoids the ghost target problem in higher dimensions. In addition, we provide a more efficient method for computing the noise covariance matrix of the SME coefficients. This was the major computational bottleneck of earlier SME implementation, and we have reduced its complexity from at least 2^N/2 operations to at most D⁴N⁵, where N is the number of targets and D the number of dimensions. Computer simulations illustrate a failure mode that the new algorithm avoids, and gives a sample comparison to a standard data- association algorithm, global nearest neighbor.

Citation Download Citation

Douglas J. Muder and Sean D. O'Neil "Multidimensional SME filter for multitarget tracking", Proc. SPIE 1954, Signal and Data Processing of Small Targets 1993, (22 October 1993); https://doi.org/10.1117/12.157789

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