Track initialization for TOMHT using auxiliary CPHD filter

Abstract

In this paper, a new track initialization method for the track-oriented multiple hypothesis tracking (TOMHT) is proposed. An auxiliary cardinalized probability hypothesis density (CPHD) filter, which is modified to estimate the distribution of the number of target-originated measurements, is proposed. After obtaining the maximum a posteriori (MAP) estimate of the number of target-originated measurements, the K-cardinality 2-D assignment technique is used to find the optimal measurement-to-track association hypothesis, which is not only subjected to the standard “one-to-one” feasibility constraints, but also the constraint that a given number of measurements are associated to newly initialized tracks. Furthermore, by assuming that the velocities of the initial tracks are independent and identically distributed (i.i.d.) with a probability distribution determined by the output of the auxiliary CPHD filter, the information about the target state from the auxiliary CPHD filter is integrated into the track initialization. After the K-cardinality 2-D assignment, the results from the TOMHT are fed back to the CPHD filter to remove the measurements being associated with the confirmed and the tentative tracks. Then the CPHD will be updated again using the reduced measurement set. Simulation results show that the proposed track initialization method is able to decrease the false track rate by adaptively controlling the track initiation latency, based on the information about the clutter spatial intensity.