  In this paper, we propose a new metric which measures the distance between
two finite sets of tracks (a track is a path of either a real or estimated
target). This metric is based on the same principle as the Optimal Subpattern
Assignment (OSPA) metric devised by Schuhmacher et al. Importantly however, the
new metric measures the distance between two finite sets of tracks whereas the
OSPA metric measures the distance between two finite sets of target states. By
also considering the properties of false tracks, missed tracks and many tracks
assigned to one track situations caused by missed detections and false alarms,
the minimization of all distances between tracks across two finite sets of
tracks employed by the new OSPAMT metric enables performance evaluation of
multi-target tracking (MTT) algorithms in a more comprehensive and accurate
manner than existing metrics such as the OSPA metric and the enhanced OSPAT
metric introduced by Ristic et al which measures the distance between two
finite sets of labeled target states.
