Multitarget tracking performance metric: deficiency aware subpattern assignment

Oksuz, Kemal
Multitarget tracking is a sequential estimation problem where conditioned on noisy sensor measurements, state variables of several targets need to be estimated recursively. In this study, the authors propose a novel performance measure for multitarget tracking named as Deficiency Aware Subpattern Assignment (DASA), that can be used to consistently compare algorithms in a broad spectrum of formulations ranging from conventional data association methods to random finite set based multitarget tracking algorithms. The DASA metric combines three components (localisation, type 1 and type 2 errors) in order to represent the behaviour of the tracking filter coherently. Furthermore, a Monte Carlo method is proposed in order to set the cut-off parameter for the case that the measurement model is known. They illustrate in their simulations that DASA improves upon the previously proposed Optimal Subpattern Assignment metric.


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Citation Formats
K. Oksuz and A. T. CEMGİL, “Multitarget tracking performance metric: deficiency aware subpattern assignment,” IET RADAR SONAR AND NAVIGATION, pp. 373–381, 2018, Accessed: 00, 2020. [Online]. Available: