Multiple Extended Target Tracking With Labeled Random Finite Sets
MetadataShow full item record
Targets that generate multiple measurements at a given instant in time are commonly known as extended targets. These present a challenge for many tracking algorithms, as they violate one of the key assumptions of the standard measurement model. In this paper, a new algorithm is proposed for tracking multiple extended targets in clutter, which is capable of estimating the number of targets, as well the trajectories of their states, comprising the kinematics, measurement rates, and extents. The proposed technique is based on modeling the multi-target state as a generalized labeled multi-Bernoulli (GLMB) random finite set (RFS), within which the extended targets are modeled using gamma Gaussian inverse Wishart (GGIW) distributions. A cheaper variant of the algorithm is also proposed, based on the labelled multi-Bernoulli (LMB) filter. The proposed GLMB/LMB-based algorithms are compared with an extended target version of the cardinalized probability hypothesis density (CPHD) filter, and simulation results show that the (G)LMB has improved estimation and tracking performance.
Showing items related by title, author, creator and subject.
Adaptive antenna array beamforming using a concatenation of recursive least square and least mean square algorithmsSrar, Jalal Abdulsayed (2011)In recent years, adaptive or smart antennas have become a key component for various wireless applications, such as radar, sonar and cellular mobile communications including worldwide interoperability for microwave ...
Beard, M.; Reuter, S.; Granström, K.; Vo, Ba-Ngu; Vo, Ba Tuong; Scheel, A. (2015)This paper addresses extended multi-target tracking in clutter, i.e. tracking targets that may produce more than one measurement on each scan. We propose a new algorithm for solving this problem, that is capable of ...
Leoputra, Wilson Suryajaya (2009)Foreground object detection is a fundamental task in computer vision with many applications in areas such as object tracking, event identification, and behavior analysis. Most conventional foreground object detection ...