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Track stitching and approximate track association on a pairwise-likelihood graph
Author(s): Lingji Chen; Sarah E. Rumbley
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Paper Abstract

Single-sensor track stitching is a path cover problem on a graph with pairwise log likelihoods. This paper provides a theoretical justification for pursuing track association on such a graph by using a sum of pairwise log likelihoods in place of the multi-sensor log likelihood. It outlines solution strategies through clique cover, cotemporal subgraph decomposition, and super-node stitching

Paper Details

Date Published: 27 April 2018
PDF: 7 pages
Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 1064602 (27 April 2018); doi: 10.1117/12.2304484
Show Author Affiliations
Lingji Chen, nuTonomy (United States)
Sarah E. Rumbley, BAE Systems (United States)

Published in SPIE Proceedings Vol. 10646:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII
Ivan Kadar, Editor(s)

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