A single-sensor single-target Mixture Reduction (MR) data association algorithm is extended for use in multisensor multitarget tracking situations. MR is extended for tracking an arbitrary number of targets using an arbitrary number of sensors under the assumption that the sensor measurement errors are independent across sensors. Like the single-sensor single-target MR algorithm, which gives better performance than the Probabilistic Data Association (PDA) filter, the multisensor multitarget MR extensions give similar improvements in performance compared to the Joint Probabilistic Data Association (JPDA) and Multisensor JPDA (MSJPDA) algorithms. Further, in the formulations for the multisensor and multitarget MR algorithms, the equations for...
In this paper, the two commonly used algorithms for association namely the Nearest Neighbour (NN) an...
Abstract—A standard assumption in most tracking algorithms, like the Probabilistic Data Association ...
Two commonly used algorithms for association, Nearest Neighbour (NN) and Probabilistic Data Associat...
When tracking multiple targets using multiple sensors, the performance evaluation of different estim...
This paper presents a novel approach to multitarget multisensor tracking, based on the combination o...
This paper proposes a novel joint multi-target tracking and track maintenance algorithm over a senso...
In the design of target tracking algorithms, the aspect of sensor resolution is rarely considered. I...
In the design of target tracking algorithms, the aspect of sensor resolution is rarely considered. I...
In this dissertation, we consider various aspects of tracking multiple targets in clutter. The prima...
The point target assumption, which suggests that a target can generate at most one measurement at a ...
The use of state space techniques to track targets using measurements from multiple sensors is consi...
Multi-sensor multi-target tracking and track association is a research topic with applications in ma...
Data association problem for multitarget tracking is determination of the relationship between targe...
The central theme of this research is how to track the motion of one or more moving targets using no...
Most classical target tracking algorithms assume that one target generates one measurement per scan....
In this paper, the two commonly used algorithms for association namely the Nearest Neighbour (NN) an...
Abstract—A standard assumption in most tracking algorithms, like the Probabilistic Data Association ...
Two commonly used algorithms for association, Nearest Neighbour (NN) and Probabilistic Data Associat...
When tracking multiple targets using multiple sensors, the performance evaluation of different estim...
This paper presents a novel approach to multitarget multisensor tracking, based on the combination o...
This paper proposes a novel joint multi-target tracking and track maintenance algorithm over a senso...
In the design of target tracking algorithms, the aspect of sensor resolution is rarely considered. I...
In the design of target tracking algorithms, the aspect of sensor resolution is rarely considered. I...
In this dissertation, we consider various aspects of tracking multiple targets in clutter. The prima...
The point target assumption, which suggests that a target can generate at most one measurement at a ...
The use of state space techniques to track targets using measurements from multiple sensors is consi...
Multi-sensor multi-target tracking and track association is a research topic with applications in ma...
Data association problem for multitarget tracking is determination of the relationship between targe...
The central theme of this research is how to track the motion of one or more moving targets using no...
Most classical target tracking algorithms assume that one target generates one measurement per scan....
In this paper, the two commonly used algorithms for association namely the Nearest Neighbour (NN) an...
Abstract—A standard assumption in most tracking algorithms, like the Probabilistic Data Association ...
Two commonly used algorithms for association, Nearest Neighbour (NN) and Probabilistic Data Associat...