Evidence map›Paper›PMID 41012942›Full record

ArticleSensors (Basel, Switzerland)2025

Hierarchical Sectorized ANN Model for DoA Estimation in Smart Textile Wearable Antenna Array Under Strong Noise Conditions.

Zoran Stanković, Olivera Pronić-Rančić, Nebojša Dončov

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

3 authors.

Zoran StankovićFaculty of Electronic Engineering, University of Niš, A. Medvedeva 4, 18000 Niš, Serbia.ORCID 0000-0003-4419-1200
Olivera Pronić-RančićFaculty of Electronic Engineering, University of Niš, A. Medvedeva 4, 18000 Niš, Serbia.ORCID 0000-0001-6405-6597
Nebojša DončovFaculty of Electronic Engineering, University of Niš, A. Medvedeva 4, 18000 Niš, Serbia.ORCID 0000-0002-9057-6737

Funding

Ministry of Science, Technological Development and Innovation of the Republic of Serbia 451-03-137/2025-03/ 200102
6 · The paper itself

Abstract

A novel hierarchical sectorized neural network module for a fast direction of arrival (DoA) estimation (HSNN-DoA) of the signal received by a textile wearable antenna array (TWAA) under strong noise conditions is presented. The developed DoA module accounts for variations in antenna element gain, inter-element spacing, and resonant frequencies under the conditions of textile crumpling caused by the motion of the TWAA wearer. The proposed model consists of a sector identification phase, which aims to determine the spatial sector in which the radio gateway (RG) is currently located based on the elements of the spatial correlation matrix of the signal sampled by the TWAA, and a DoA estimation phase, which aims to accurately determine the angular position of the RG in the azimuthal plane. The architecture of the HSNN-DoA module, with different time window lengths in which angular position of RG is recorded, is investigated and compared with the DoA module based on a stand-alone MLP network and the corresponding Root-MUSIC DoA module in terms of accuracy and speed of DoA estimation under variable noise conditions.

Indexed as

artificial neural network (ANN)direction of arrival (DoA)multilayer perceptron (MLP)Root MUSICSNRtextile wearable antenna array (TWAA)

Identifiers

PMID41012942
PMCPMC12473620

What OpenQuestion holds

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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.