Multitarget miss distance via optimal assignment

被引:141
作者
Hoffman, JR [1 ]
Mahler, RPS [1 ]
机构
[1] Lockheed Martin Maritime Sensors & Syst Tact Syst, Eagan, MN 55121 USA
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS | 2004年 / 34卷 / 03期
关键词
mallows distance; performance evaluation; random sets; sensor management; Wasserstein distance;
D O I
10.1109/TSMCA.2004.824848
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The concept of miss distance-Euclidean, Mahalanobis, etc.-is a fundamental, far-reaching, and taken-for-granted element of the engineering theory and practice of single-target systems. In this paper we introduce a comprehensive L-p-type theory of distance metrics for multitarget (and, more generally, multiobject) systems. We show that this theory extends, and provides a rigorous theoretical basis for, an intuitively appealing optimal-assignment approach proposed by Drummond for evaluating the performance of multitarget tracking algorithms. We describe tractable computational approaches for computing such metrics based on standard optima assignment or convex optimization techniques. We describe the potentially far-reaching implications of these metrics for applications such as performance evaluation and sensor management. In the former case, we demonstrate the application of multitarget miss-distance metrics as measures of effectiveness (MoEs) for multitarget tracking algorithms.
引用
收藏
页码:327 / 336
页数:10
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