Probability hypothesis density filter with adaptive parameter estimation for tracking multiple maneuvering targets
نویسندگان
چکیده
منابع مشابه
Multiple Target Tracking with The Probability Hypothesis Density Filter
The random-set framework for multiple target tracking offers a distinct alternative to the traditional approach to multiple target tracking by treating the collections of individual targets and observations as finite-sets. The multi-target state is predicted and updated recursively based on the set-valued observation. The complexity of computing the multi-target recursion grows exponentially wi...
متن کاملAcoustic Channel Tracking with the Cardinalized Probability Hypothesis Density Filter and the Multiple Hypothesis Tracker
Two datasets, one simplistic that assumes direct observation of paths and the other based on observations derived from compressed sensing and an assumed OFDM communications underpinning, simulate underwater acoustic channels. The Cardinalized Probability Hypothesis Density filter and the Multiple Hypothesis Tracker are applied to these wireless channels. The performances of the two trackers are...
متن کاملA shrinkage probability hypothesis density filter for multitarget tracking
In radar systems, tracking targets in low signal-to-noise ratio (SNR) environments is a very important task. There are some algorithms designed for multitarget tracking. Their performances, however, are not satisfactory in low SNR environments. Track-before-detect (TBD) algorithms have been developed as a class of improved methods for tracking in low SNR environments. However, multitarget TBD i...
متن کاملA Novel Merging Algorithm in Gaussian Mixture Probability Hypothesis Density Filter for Close Proximity Targets Tracking ⋆
This paper proposes a novel merging algorithm in Gaussian mixture probability hypothesis density filter to track close proximity targets. The proposed algorithm is added after GM-PHD recursion, in a condition that more than one target has the same state. The weights of Gaussian components decide whether the components can be utilized to extract states, and the means and covariances of Gaussian ...
متن کاملState Estimation and Smoothing for the Probability Hypothesis Density Filter
Tracking multiple objects is a challenging problem for an automated system, with applications in many domains. Typically the system must be able to represent the posterior distribution of the state of the targets, using a recursive algorithm that takes information from noisy measurements. However, in many important cases the number of targets is also unknown, and has also to be estimated from d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Chinese Journal of Aeronautics
سال: 2016
ISSN: 1000-9361
DOI: 10.1016/j.cja.2016.09.010