Evidence map›Paper›PMID 36904753›Full record

ArticleSensors (Basel, Switzerland)2023

A Novel Approach for Direction of Arrival Estimation in Co-Located MIMO Radars by Exploiting Extended Array Manifold Vectors.

Sadiq Akbar, Muhammad Sohail, Fawad Zaman, Muhammad Abdul Rehman Khan, Nopdanai Ajavakom, Gridsada Phanomchoeng

Full text read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Sadiq AkbarDepartment of Mechanical Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Muhammad SohailSchool of Information Science and Technology, University of Science and Technology of China (USTC), Hefei 230026, China.
Fawad ZamanDepartment of Electrical & Computer Engineering, COMSATS University Islamabad, Islamabad 44000, Pakistan.
Muhammad Abdul Rehman KhanDepartment of Avionics Engineering, Institute of Space Technology Islamabad, Islamabad 44000, Pakistan.
Nopdanai AjavakomDepartment of Mechanical Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Gridsada PhanomchoengDepartment of Mechanical Engineering, Chulalongkorn University, Bangkok 10330, Thailand.ORCID 0000-0002-6518-0992

Funding

Second Century Fund (C2F), Chulalongkorn University NA
6 · The paper itself

Abstract

Multiple-input multiple-output (MIMO) radars enable better estimation accuracy with improved resolution in contrast to traditional radar systems; thus, this field has attracted attention in recent years from researchers, funding agencies, and practitioners. The objective of this work is to estimate the direction of arrival of targets for co-located MIMO radars by proposing a novel approach called flower pollination. This approach is simple in concept, easy to implement and has the capability of solving complex optimization problems. The received data from the far field located targets are initially passed through the matched filter to enhance the signal-to-noise ratio, and then the fitness function is optimized by incorporating the concept of virtual or extended array manifold vectors of the system. The proposed approach outperforms other algorithms mentioned in the literature by utilizing statistical tools for fitness, root mean square error, cumulative distribution function, histograms, and box plots.

Indexed as

co-located radardirection of arrival estimationflower pollination algorithmMIMO systems

Identifiers

PMID36904753
PMCPMC10007184

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read11
Read underepoch 390

Registered trials

None linked

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.