Add to ORKGWe present in this paper two improved particle filter algorithms for ballistic target tracking. The first algorithm is a sampling/import-ance resampling (SIR) filter that uses an optimized importance function plus residual resampling to combat particle degeneracy, and also incorporates a Metropolis-Hastings (MH) move step to reduce particle impoverishment. The second proposed algorithm is an auxiliary particle filter (APF). Both algorithms show good performance results when compared to the ideal posterior Cramér-Rao lower bound for the mean square estimation error. 1
Abstract. The problem of tracking a reentry ballistic object by processing radar measurements is con...
The topic of this bachelor thesis is Optimal Bayesian estimate usage in target tracking with bistati...
Resampling is an essential step in particle filtering (PF) methods in order to avoid degeneracy. Sys...
We present in this paper a density-assisted particle filter (DAPF) algorithm for ballistic target tr...
In order to cope with the challenges of non-cooperative targets such as stealth targets to modern ra...
The estimation filter in radar systems must track targets ' position within low tracking error....
In this work, a new variant of particle filter has been proposed. In visual object tracking, particl...
The widespread application of unmanned aerial vehicles (UAVs) urgently requires an effective trackin...
International audienceThe deterministic Laplace method is combined with particle filtering for the s...
The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However w...
A particle filter (PF) is a recursive numerical technique which uses random sampling to approximate ...
In this paper, we address the target tracking problem for the case of maneuvering target, including ...
To boost the robustness of the traditional particle-filter-based tracking algorithm under complex sc...
In modern systems for air surveillance, it is important to have a high quality situationassessment. ...
AbstractA new particle filter is presented for nonlinear tracking problems. In practice, maneuvering...
Abstract. The problem of tracking a reentry ballistic object by processing radar measurements is con...
The topic of this bachelor thesis is Optimal Bayesian estimate usage in target tracking with bistati...
Resampling is an essential step in particle filtering (PF) methods in order to avoid degeneracy. Sys...
We present in this paper a density-assisted particle filter (DAPF) algorithm for ballistic target tr...
In order to cope with the challenges of non-cooperative targets such as stealth targets to modern ra...
The estimation filter in radar systems must track targets ' position within low tracking error....
In this work, a new variant of particle filter has been proposed. In visual object tracking, particl...
The widespread application of unmanned aerial vehicles (UAVs) urgently requires an effective trackin...
International audienceThe deterministic Laplace method is combined with particle filtering for the s...
The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However w...
A particle filter (PF) is a recursive numerical technique which uses random sampling to approximate ...
In this paper, we address the target tracking problem for the case of maneuvering target, including ...
To boost the robustness of the traditional particle-filter-based tracking algorithm under complex sc...
In modern systems for air surveillance, it is important to have a high quality situationassessment. ...
AbstractA new particle filter is presented for nonlinear tracking problems. In practice, maneuvering...
Abstract. The problem of tracking a reentry ballistic object by processing radar measurements is con...
The topic of this bachelor thesis is Optimal Bayesian estimate usage in target tracking with bistati...
Resampling is an essential step in particle filtering (PF) methods in order to avoid degeneracy. Sys...