Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking

Existing extended target probability hypothesis density (ET-PHD) filters are insufficient in tracking weak extended targets. Hough transform-based track-before-detect methods are designed to detect the weak targets in a straight-line constant-velocity model. Therefore, this paper presents a novel me...

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Main Authors: Bo Yan, Na Xu, Guangmin Wang, Sheng Yang, L. P. Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8737730/
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author Bo Yan
Na Xu
Guangmin Wang
Sheng Yang
L. P. Xu
author_facet Bo Yan
Na Xu
Guangmin Wang
Sheng Yang
L. P. Xu
author_sort Bo Yan
collection DOAJ
description Existing extended target probability hypothesis density (ET-PHD) filters are insufficient in tracking weak extended targets. Hough transform-based track-before-detect methods are designed to detect the weak targets in a straight-line constant-velocity model. Therefore, this paper presents a novel method for detecting and tracking multiple maneuvering weak extended targets by a 3-dimensional Hough transform (3DHT) and multiple hypothesis tracking (MHT). The proposed method consists of two stages. In stage 1, the measurements in multiple scans are partitioned into overlapped time windows. The tracklets in each window can be detected by the 3DHT. In stage 2, the tracklets are associated to get the entire trajectories by the MHT. The tracklets of weak targets can be detected by the 3DHT in stage 1. Association in stage 2 is designed to detect maneuvering targets. Some false alarm tracklets could be built in stage 1. However, the false alarm tracklets are independent and unlikely to form a sequential trajectory in stage 2. Merely, the trajectories whose target likelihood ratio larger than a detection threshold can be confirmed as a target. Both the real data and the synthetic data are performed with the proposed approach and several existing algorithms. The result infers that the proposed approach is superior to the others with much less prior information that is necessary.
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spelling doaj.art-47d4d3e7a69a47bc811b17ea7f57f22d2022-12-21T23:26:05ZengIEEEIEEE Access2169-35362019-01-017807178073210.1109/ACCESS.2019.29233578737730Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis TrackingBo Yan0https://orcid.org/0000-0003-0759-0990Na Xu1Guangmin Wang2Sheng Yang3L. P. Xu4School of Aerospace Science and Technology, Xidian University, Xi’an, ChinaSchool of Life Sciences and Technology, Xidian University, Xi’an, ChinaSchool of Aerospace Science and Technology, Xidian University, Xi’an, ChinaSchool of Aerospace Science and Technology, Xidian University, Xi’an, ChinaSchool of Aerospace Science and Technology, Xidian University, Xi’an, ChinaExisting extended target probability hypothesis density (ET-PHD) filters are insufficient in tracking weak extended targets. Hough transform-based track-before-detect methods are designed to detect the weak targets in a straight-line constant-velocity model. Therefore, this paper presents a novel method for detecting and tracking multiple maneuvering weak extended targets by a 3-dimensional Hough transform (3DHT) and multiple hypothesis tracking (MHT). The proposed method consists of two stages. In stage 1, the measurements in multiple scans are partitioned into overlapped time windows. The tracklets in each window can be detected by the 3DHT. In stage 2, the tracklets are associated to get the entire trajectories by the MHT. The tracklets of weak targets can be detected by the 3DHT in stage 1. Association in stage 2 is designed to detect maneuvering targets. Some false alarm tracklets could be built in stage 1. However, the false alarm tracklets are independent and unlikely to form a sequential trajectory in stage 2. Merely, the trajectories whose target likelihood ratio larger than a detection threshold can be confirmed as a target. Both the real data and the synthetic data are performed with the proposed approach and several existing algorithms. The result infers that the proposed approach is superior to the others with much less prior information that is necessary.https://ieeexplore.ieee.org/document/8737730/Extended target trackingweak target detectionmaneuvering target trackingHough transformmultiple hypothesis tracking
spellingShingle Bo Yan
Na Xu
Guangmin Wang
Sheng Yang
L. P. Xu
Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
IEEE Access
Extended target tracking
weak target detection
maneuvering target tracking
Hough transform
multiple hypothesis tracking
title Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
title_full Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
title_fullStr Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
title_full_unstemmed Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
title_short Detection of Multiple Maneuvering Extended Targets by Three-Dimensional Hough Transform and Multiple Hypothesis Tracking
title_sort detection of multiple maneuvering extended targets by three dimensional hough transform and multiple hypothesis tracking
topic Extended target tracking
weak target detection
maneuvering target tracking
Hough transform
multiple hypothesis tracking
url https://ieeexplore.ieee.org/document/8737730/
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