منابع مشابه
Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter
The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effec...
متن کاملHybrid multi-Bernoulli CPHD filter for superpositional sensors
We propose, for the superpositional sensor scenario, a hybrid between the multi-Bernoulli filter and the cardinalized probability hypothesis density (CPHD) filter. We use a multi-Bernoulli random finite set (RFS) to model existing targets and we use an independent and identically distributed cluster (IIDC) RFS to model newborn targets and targets with low probability of existence. Our main cont...
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The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...
متن کاملAmplitude-Aided CPHD Filter for Multitarget Tracking in Infrared Images
The cardinalized probability hypothesis density (CPHD) filter is a powerful tool for multitarget tracking (MTT). However, conventional CPHD filter discriminates targets from clutter only via the motion information, which is not reasonable in the situation of dense clutter. In the tracking, the amplitude of target returns is usually stronger than those coming from clutter, so the amplitude infor...
متن کاملA Generalized Labeled Multi-Bernoulli Filter with Object Spawning
Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter such as the Generalized Labeled Multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In t...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2017
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2016.2597126