Add to ORKGIn Bayesian multi-target filtering we have to contend with two notable sources of uncertainty, clutter and detection. Knowledge of parameters such as clutter rate and detection profile are of critical importance in multi-target filters such as the probability hypothesis density (PHD) and Cardinalized PHD (CPHD) filters. Naive application of the CPHD (and PHD) filter with mismatches in clutter and detection model parameters results in biased estimates. In this paper we show how to use the CPHD (and PHD) filter in unknown clutter rate and detection profile. © 2011 IEEE
In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection p...
© 2014 IEEE. In previous publications the author introduced CPHD filters designed to detect and trac...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
In Bayesian multi-target filtering, we have to contend with two notable sources of uncertainty, clut...
The “clutter-agnostic” CPHD filter was introduced at the 2010 SPIE Defense, Security and Sensing Sym...
The "background-agnostic" CPHD filter was introduced at the 2010 SPIE Defense, Security and Sensing ...
The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for ...
Abstract — The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian alg...
The Probability Hypothesis Density (PHD) filter and the Cardinalized PHD (CPHD) filter are two compu...
The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the...
We study various multi-sensor PHD and CPHD filters and their implementations. 1 Problem Statement Th...
This paper describes a general approach for deriving PHD/CPHD filters that must estimate the backgro...
It was recently demonstrated that the Gaussian Mixture Cardinalised Probability Hypothesis Density (...
Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and pr...
© 2015 SPIE. Previous research has produced CPHD filters that can detect and track multiple targets ...
In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection p...
© 2014 IEEE. In previous publications the author introduced CPHD filters designed to detect and trac...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...
In Bayesian multi-target filtering, we have to contend with two notable sources of uncertainty, clut...
The “clutter-agnostic” CPHD filter was introduced at the 2010 SPIE Defense, Security and Sensing Sym...
The "background-agnostic" CPHD filter was introduced at the 2010 SPIE Defense, Security and Sensing ...
The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for ...
Abstract — The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian alg...
The Probability Hypothesis Density (PHD) filter and the Cardinalized PHD (CPHD) filter are two compu...
The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the...
We study various multi-sensor PHD and CPHD filters and their implementations. 1 Problem Statement Th...
This paper describes a general approach for deriving PHD/CPHD filters that must estimate the backgro...
It was recently demonstrated that the Gaussian Mixture Cardinalised Probability Hypothesis Density (...
Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and pr...
© 2015 SPIE. Previous research has produced CPHD filters that can detect and track multiple targets ...
In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection p...
© 2014 IEEE. In previous publications the author introduced CPHD filters designed to detect and trac...
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets...