A Generalized Information Matrix Fusion Based Heterogeneous Track-to-Track Fusion Algorithm

The problem of Track-to-Track Fusion (T2TF) is very important for distributed tracking systems. It allows the use of the hierarchical fusion structure, where local tracks are sent to the fusion center (FC) as summaries of local information about the states of the targets, and fused to get the global track estimates. Compared to the centralized measurement-to-track fusion (CTF), the T2TF approach has low communication cost and is more suitable for practical implementation. Although having been widely investigated in the literature, most T2TF algorithms dealt with the fusion of homogenous tracks that have the same state of the target. However, in general, local trackers may use different motion models for the same target, and have different state spaces. This raises the problem of Heterogeneous Track-to-Track Fusion (HT2TF). In this paper, we propose the algorithm for HT2TF based on the generalized Information Matrix Fusion (GIMF) to handle the fusion of heterogenous tracks in the presence of possible communication delays. Compared to the fusion based on the LMMSE criterion, the proposed algorithm does not require the crosscovariance between the tracks for the fusion, which greatly simplify its implementation. Simulation results show that the proposed HT2TF algorithm has good consistency and fusion accuracy. Conference Name: Proc. SPIE Conf. on Signal Processing, Sensor Fusion, and Target Recognition, #8050-41 Conference Date: April 01, 2011 The problem of Track-to-Track Fusion (T2TF) is very important for distributed tracking systems. It allows the use of the hierarchical fusion structure, where local tracks are sent to the fusion center (FC) as summaries of local information about the states of the targets, and fused to get the global track estimates. Compared to the centralized measurement-to-track fusion (CTF), the T2TF approach has low communication cost and is more suitable for practical implementation. Although having been widely investigated in the literature, most T2TF algorithms dealt with the fusion of homogenous tracks that have the same state of the target. However, in general, local trackers may use different motion models for the same target, and have different state spaces. This raises the problem of Heterogeneous Track-to-Track Fusion (HT2TF). In this paper, we propose the algorithm for HT2TF based on the generalized Information Matrix Fusion (GIMF) to handle the fusion of heterogenous tracks in the presence of possible communication delays. Compared to the fusion based on the LMMSE criterion, the proposed algorithm does not require the crosscovariance between the tracks for the fusion, which greatly simplify its implementation. Simulation results show that the proposed HT2TF algorithm has good consistency and fusion accuracy. A Generalized Information Matrix Fusion Based Heterogeneous Track-to-Track Fusion Algorithm∗ Xin Tiana, Yaakov Bar-Shaloma, Ting Yuana, Erik Blaschb, Khanh Phamc and Genshe Chend aDept. of Electrical and Computer Engineering, Univ. of Connecticut, Storrs, CT, USA bSensors Directorate, Air Force Research Laboratory, Wright-Patterson AFB, OH, USA cSpace Vehicles Directorate, Air Force Research Laboratory, Kirtland AFB, NM, USA dDCM Research Resources LLC, 14163 Furlong Way, Germantown, MD, USA