Evidence map›Paper›PMID 35270948›Full record

ArticleSensors (Basel, Switzerland)2022

A New Coarse Gating Strategy Driven Multidimensional Assignment for Two-Stage MHT of Bearings-Only Multisensor-Multitarget Tracking.

Zheng Wei, Zhansheng Duan, Yina Han, Mahendra Mallick

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zheng WeiCenter for Information Engineering Science Research, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0002-2293-6438
Zhansheng DuanCenter for Information Engineering Science Research, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0001-7366-5984
Yina HanSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.ORCID 0000-0001-9713-1821
Mahendra MallickIndependent Researcher, Anacortes, WA 98221, USA.ORCID 0000-0002-4836-4431

Funding

National Key Research and Development Plan under Grants 2021YFC2202600National Key Research and Development Plan under Grants 2021YFC2202603National Natural Science Foundation of China 61673317National Natural Science Foundation of China 61773147National Natural Science Foundation of China 62033010
6 · The paper itself

Abstract

The problem of two-dimensional bearings-only multisensor-multitarget tracking is addressed in this work. For this type of target tracking problem, the multidimensional assignment (MDA) is crucial for identifying measurements originating from the same targets. However, the computation of the assignment cost of all possible associations is extremely high. To reduce the computational complexity of MDA, a new coarse gating strategy is proposed. This is realized by comparing the Mahalanobis distance between the current estimate and initial estimate in an iterative process for the maximum likelihood estimation of the target position with a certain threshold to eliminate potential infeasible associations. When the Mahalanobis distance is less than the threshold, the iteration will exit in advance so as to avoid the expensive computational costs caused by invalid iteration. Furthermore, the proposed strategy is combined with the two-stage multiple hypothesis tracking framework for bearings-only multisensor-multitarget tracking. Numerical experimental results verify its effectiveness.

Indexed as

Algorithmsbearings-only multisensor-multitarget trackingcoarse gatingMahalanobis distancemaximum likelihood estimationmultidimensional assignment (MDA)multiple hypothesis tracking

Identifiers

PMID35270948
PMCPMC8915076

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.