27 April 2018 Track stitching and approximate track association on a pairwise-likelihood graph
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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
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Lingji Chen, Sarah E. Rumbley, "Track stitching and approximate track association on a pairwise-likelihood graph", Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 1064602 (27 April 2018); doi: 10.1117/12.2304484; https://doi.org/10.1117/12.2304484
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