Evidence map›Paper›PMID 40363090›Full record

ArticleSensors (Basel, Switzerland)2025

A Uniform Funnel Array for DOA Estimation in FANET Using Fibonacci Sampling.

Siwei Huo, Ming Zhang, Yongxi Liu, Shitao Zhu

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

4 authors.

Siwei HuoSchool of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Ming ZhangSchool of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0002-5796-4754
Yongxi LiuSchool of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0002-9164-5247
Shitao ZhuSchool of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Funding

Key Research and Development Program of Shaanxi 2024GX-ZDCYL-05-09Shaanxi Key Laboratory of Deep Space Exploration Intelligent Information Technology 2021SYS-04
6 · The paper itself

Abstract

The Flying Ad-Hoc Network (FANET) is an important component of the 6G communication system. In order to achieve the precise positioning of unmanned aerial vehicle (UAV) nodes in a FANET when satellite navigation signals are unavailable, simple and accurate direction-of-arrival (DOA) estimation methods are required. In this paper, we propose an improved correlative interferometer method to estimate the DOAs of the UAVs in a FANET. This method adopts a uniform funnel array (UFA) configuration, which consists of a uniform circular array (UCA) and an additional element located above the center. This configuration improves the estimation accuracy for DOAs with large polar angles because it utilizes the degree of freedom in the vertical aperture. In addition, the Fibonacci sampling strategy is employed to overcome the polar clustering phenomenon exhibited by latitude-longitude sampling. Furthermore, in the interferometer, only partial phase differences are used to reduce the storage burden. When calculating the similarity function, we adopt the triangular function instead of the cosine function to improve computational efficiency. The simulation results show that the proposed UFA improves the DOA estimation accuracy by 65.56% over the planar UCA for signals with large polar angles. Moreover, Fibonacci sampling improves the DOA estimation accuracy by 11.54% as compared to the latitude-longitude sampling.

Indexed as

correlative interferometerdirection-of-arrival (DOA) estimationFibonacci samplingphase differencessimilarity function

Identifiers

PMID40363090
PMCPMC12074189

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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.