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Covariance control for multisensor systems
M Kalandros - IEEE Transactions on Aerospace and Electronic …, 2002 - ieeexplore.ieee.org
As the profusion of different sensors improves the capabilities of tracking platforms, tracking
objectives can move from simply trying to achieve the most with a limited sensor suite to …
objectives can move from simply trying to achieve the most with a limited sensor suite to …
Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing
We consider the problem of tracking multiple maneuvering targets in clutter using switching
multiple target motion models. A suboptimal filtering algorithm is developed by applying the …
multiple target motion models. A suboptimal filtering algorithm is developed by applying the …
Tutorial on multisensor management and fusion algorithms for target tracking
This paper provides an introduction to sensor fusion techniques for target tracking. It
presents an overview of common filtering techniques that are effective for moving targets as …
presents an overview of common filtering techniques that are effective for moving targets as …
Tracking of multiple maneuvering targets in clutter using multiple sensors, IMM, and JPDA coupled filtering
We consider the problem of tracking multiple maneuvering targets in clutter using switching
multiple target motion models. A novel suboptimal filtering algorithm is developed by …
multiple target motion models. A novel suboptimal filtering algorithm is developed by …
Multisensor covariance control strategies for reducing bias effects in interacting target scenarios
Algorithms are presented for managing sensor information to reduce the effects of bias when
tracking interacting targets. When targets are close enough together that their measurement …
tracking interacting targets. When targets are close enough together that their measurement …
Scalable multitarget tracking using multiple sensors: A belief propagation approach
We propose a method for multisensor-multitarget tracking with excellent scalability in the
number of targets (which is assumed known), the number of sensors, and the number of …
number of targets (which is assumed known), the number of sensors, and the number of …
Multi‐sensor track‐to‐track fusion with target existence in cluttered environments
Multi‐sensor fusion for multiple target tracking in cluttered environments is needed for
improving tracking accuracy and track maintenance over single sensor target tracking in real …
improving tracking accuracy and track maintenance over single sensor target tracking in real …
The optimal order of processing sensor information in sequential multisensor fusion algorithms
We examine the order of sensor processing in the sequential multisensor probabilistic data
association (MSPDA) filter for target tracking applications. If two sensors of different qualities …
association (MSPDA) filter for target tracking applications. If two sensors of different qualities …
Variance estimation and ranking of Gaussian mixture distributions in target tracking applications
Variance estimation and ranking methods are developed for stochastic processes modeled
by Gaussian mixture distributions. It is shown that the variance estimate from a Gaussian …
by Gaussian mixture distributions. It is shown that the variance estimate from a Gaussian …
Computing budget allocation for efficient ranking and selection of variances with application to target tracking algorithms
This paper addresses the problem of ranking and selection for stochastic processes, such as
target tracking algorithms, where variance is the performance metric. Comparison of different …
target tracking algorithms, where variance is the performance metric. Comparison of different …