RCS–Doppler-Assisted MM-GM-PHD Filter for Passive Radar in Non-Uniform Clutter [PDF]
SensorsIn passive radar, the multiple model probability hypothesis density (MM-PHD) filter has demonstrated robust capability in tracking multi-maneuvering targets.
Jia Wang +3 more
doaj +2 more sources
Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory
Sensors, 2017 Cooperative localization (CL) is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs).
Lichuan Zhang +3 more
doaj +3 more sources
Automated extraction of dolphin whistles—A sequential Monte Carlo probability hypothesis density approach [PDF]
The Journal of the Acoustical Society of America, 2020 The need for automated methods to detect and extract marine mammal vocalizations from acoustic data has increased in the last few decades due to the increased availability of long-term recording systems. Automated dolphin whistle extraction represents a challenging problem due to the time-varying number of overlapping whistles present in, potentially ...
Pina Gruden, Paul R. White
openaire +3 more sources
Active Sonar Target Tracking Based on the GM-CPHD Filter Algorithm [PDF]
Xibei Gongye Daxue Xuebao, 2018 The estimation of underwater multi-target state has always been the difficult problem of active sonar target tracking.In order to get the variable number of target and their state, the random finite set theory is applied to multi-target tracking system ...
doaj +1 more source
Arbitrary clutter extended target probability hypothesis density filter
IET Radar, Sonar & Navigation, 2021 Based on the random finite set (RFS) framework and the probability hypothesis density (PHD) filter, the extended target PHD (ET‐PHD) filter is proposed for multiple extended target tracking.
Xinglin Shen +4 more
doaj +1 more source
Multi-Feature Matching GM-PHD Filter for Radar Multi-Target Tracking
Sensors, 2022 Multi-target tracking (MTT) is one of the most important functions of radar systems. Traditional multi-target tracking methods based on data association convert multi-target tracking problems into single-target tracking problems.
Jin Tao +5 more
doaj +1 more source
Gaussian Process Gaussian Mixture PHD Filter for 3D Multiple Extended Target Tracking
Remote Sensing, 2023 This paper addresses the problem of tracking multiple extended targets in three-dimensional space. We propose the Gaussian process Gaussian mixture probability hypothesis density (GP-PHD) filter, which is capable of tracking multiple extended targets ...
Zhiyuan Yang +4 more
doaj +1 more source
Automated tracking of dolphin whistles using Gaussian mixture probability hypothesis density filters [PDF]
The Journal of the Acoustical Society of America, 2016 This work considers automated multi target tracking of odontocete whistle contours. An adaptation of the Gaussian mixture probability hypothesis density (GM-PHD) filter is described and applied to the acoustic recordings from six odontocete species.
Gruden, Pina, White, Paul R.
openaire +3 more sources
IET Radar, Sonar & Navigation, 2022 Non‐cooperative bistatic radar refers to the passive bistatic radar using a non‐cooperative radar as the illuminator of opportunity. Limited by the non‐cooperation and bistatic configuration, multi‐target tracking of the non‐cooperative bistatic radar is
Sen Wang, Qinglong Bao, Jiameng Pan
doaj +1 more source
Label GM-PHD Filter Based on Threshold Separation Clustering
Sensors, 2021 Gaussian mixture probability hypothesis density (GM-PHD) filtering based on random finite set (RFS) is an effective method to deal with multi-target tracking (MTT).
Kuiwu Wang, Qin Zhang, Xiaolong Hu
doaj +1 more source