Evidence map›Paper›PMID 28846629›Full record

ArticleSensors (Basel, Switzerland)2017

A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory.

Wen Jiang, Ying Cao, Lin Yang, Zichang He

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2017. 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

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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.

Wen JiangSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China. jiangwen@nwpu.edu.cn.
Ying CaoSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China. caoyingnwpu@hotmail.com.
Lin YangChina Equipment System Engineering Company, Beijing 100039, China. yanglin61s@sina.com.
Zichang HeSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China. hezichang@mail.nwpu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven't taken into account the processing of uncertain information. Therefore, this paper proposes a time-space domain information fusion method based on Dempster-Shafer evidence theory, which has the ability to deal with uncertain information in the process of specific emitter identification. In this paper, radars will generate a group of evidence respectively based on the information they obtained, and our main task is to fuse the multiple groups of evidence to get a reasonable result. Within the framework of recursive centralized fusion model, the proposed method incorporates a correlation coefficient, which measures the relevance between evidence and a quantum mechanical approach, which is based on the parameters of radar itself. The simulation results of an illustrative example demonstrate that the proposed method can effectively deal with uncertain information and get a reasonable recognition result.

Indexed as

correlation coefficientDempster–Shafer evidence theoryquantum mechanical approachrecursive centralized modelspecific emitter identificationtime–space domain information fusion

Identifiers

PMID28846629
PMCPMC5621057

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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.