Evidence map›Paper›PMID 34451037›Full record

ArticleSensors (Basel, Switzerland)2021

Distinguishing Drones from Birds in a UAV Searching Laser Scanner Based on Echo Depolarization Measurement.

Jacek Wojtanowski, Marek Zygmunt, Tadeusz Drozd, Marcin Jakubaszek, Marek Życzkowski, Michał Muzal

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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.

Jacek WojtanowskiInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.ORCID 0000-0002-2771-4471
Marek ZygmuntInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.ORCID 0000-0001-9058-9178
Tadeusz DrozdInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.
Marcin JakubaszekInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.ORCID 0000-0001-9157-6627
Marek ŻyczkowskiInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.ORCID 0000-0003-2116-6969
Michał MuzalInstitute of Optoelectronics, Military University of Technology, 00908 Warsaw, Poland.ORCID 0000-0003-4779-3397

Funding

Narodowe Centrum Badań i Rozwoju DOB-BIO9/21/01/2018
6 · The paper itself

Abstract

Widespread availability of drones is associated with many new fascinating possibilities, which were reserved in the past for few. Unfortunately, this technology also has many negative consequences related to illegal activities (surveillance, smuggling). For this reason, particularly sensitive areas should be equipped with sensors capable of detecting the presence of even miniature drones from as far away as possible. A few techniques currently exist in this field; however, all have significant drawbacks. This study addresses a novel approach for small (<5 kg) drones detection technique based on a laser scanning and a method to discriminate UAVs from birds. The latter challenge is fundamental in minimizing the false alarm rate in each drone monitoring equipment. The paper describes the developed sensor and its performance in terms of drone vs. bird discrimination. The idea is based on simple cross-polarization ratio analysis of the optical echo received as a result of laser backscattering on the detected object. The obtained experimental results show that the proposed method does not always guarantee 100 percent discrimination efficiency, but provides certain confidence level distribution. Nevertheless, due to the hardware simplicity, this approach seems to be a valuable addition to the developed anti-drone laser scanner.

Indexed as

BirdsLasersAnimalsanti-drone systemdrone detectiondrone monitoringdrone vs. bird discriminationlaser scannerUAV detection

Identifiers

PMID34451037
PMCPMC8402287

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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.