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Skip to Search Results- 3Non-linear filtering
- 2Target tracking
- 2Tracking
- 1Branching interacting particle system
- 1Filters (Mathematics)
- 1Homeomorphisms.
- 4Mathematical and Statistical Sciences, Department of
- 4Mathematical and Statistical Sciences, Department of/Research Publications (Mathematical and Statistical Sciences)
- 1Graduate and Postdoctoral Studies (GPS), Faculty of
- 1Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
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2003
Ballantyne, David, Wiersma, Jonathan, Kouritzin, Michael, Hailes, Jarett, Long, Hongwei
A hybrid weighted interacting particle filter, the selectively resampling particle filter (SERP), is used to detect and track multiple ships maneuvering in a region of water. The ship trajectories exhibit nonlinear dynamics and interact in a nonlinear manner such that the ships do not collide....
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2000
Ballantyne, David, Chan, Hubert, Kouritzin, Michael
Particle approximations are used to track a maneuvering signal given only a noisy, corrupted sequence of observations, as are encountered in target tracking and surveillance. The signal exhibits nonlinearities that preclude the optimal use of a Kalman filter. It obeys a stochastic differential...
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2001
Ballantyne, David, Hoffman, John, Kouritzin, Michael
Particle-based nonlinear filters provide a mathematically optimal (in the limit) and sound method for solving a number of difficult filtering problems. However, there are a number of practical difficulties that can occur when applying particle-based filtering techniques to real world problems....
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2002
Kim, Surrey, Kouritzin, Michael, Ballantyne, David
Particle-based nonlinear filters have proven to be effective and versatile methods for computing approximations to difficult filtering problems. We introduce a novel hybrid particle method, thought to possess an excellent compromise between the unadaptive nature of the weighted particle methods...