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doctoral thesis
Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:822654
Vondra, Bojan
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Communication and Space Technologies

Institutional repository: FER Repository

Cite this document

Vondra, B. (2021). Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:822654

Vondra, Bojan. "Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:822654

Vondra, Bojan. "Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:822654

Vondra, B. (2021). 'Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 13 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:822654

Vondra B. Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 December 13] Available at: https://urn.nsk.hr/urn:nbn:hr:168:822654

B. Vondra, "Pridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:822654

Metadata
TitlePridruživanje radarskih podataka manevrirajućem cilju uz smetnje uzrokovane odjekom od mora
Title (english)Manoeuvring target radar data association in presence of sea clutter
AuthorBojan Vondra
MBZ: -331061
MentorDavor Bonefačić (mentor)
Committee memberDavor Bonefačić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Communication and Space Technologies)
Zagreb
Defense date and country2021, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Različitost Jadranskog mora u odnosu na otvoreno more, ocean, najviše se reflektira u specifi-čnoj gustoći valne energije, specifičnom odnosu brzine vjetra prema efektivnoj visini valova, malom privjetrištu, velikom broju otoka. U dostupnoj literaturi ne postoje zapisi o elektromag-netskom raspršenju od morske površine za specifične uvjete Jadrana, pa nije poznata razina točnosti klasičnih parametarskih modela, razvijenih na temelju mjerenja na otvorenom moru, oceanu. Alternativno se statistika odjeka smetnje (i cilja) može ekstrahirati iz estimirane razdi-obe, isključivo na temelju uzoraka (otisaka) u okolici praćenog cilja. Tretiranje mjerenja otisaka kao bešumnih, otvara prostor estimaciji razdiobe primjenom neuronskih mreža, pri čemu se iskorištava svojstvo njihove univerzalne aproksimativnosti. U estimaciji amplitudne razdiobe, radijalne mreže pokazuju najpovoljniji omjer točnosti i računalnog opterećenja, važnog za stvarnovremensku aplikaciju. U scenariju praćenja male gumene brodice maskirane valovima, tradicionalni parametarski Swerlingov model ne opisuje dovoljno točno odjek cilja kontamini-ran odjecima valova. Djelovanje neuronske mreže kao estimatora razdiobe u scenariju smetnje izrazito teškog repa, rezultira vjerojatnošću zadržavanja staze od 0,3, u odnosu na vjerojatnost 0,02 ostvarene primjenom parametarskog Swerlingovog modela. Minimalno 64 kvantizacijskih razina potrebno je za prijenos amplitudne informacije iz udaljenog radarskog senzora bez zna-čajnih gubitaka.
Abstract (english)
In comparison with open seas, properties of Adriatic Sea are distinct wave spectrum, specific ratio of wind velocity to effective wave height, limited fetch, large number of islands. Data of electromagnetic scattering from sea surface in Adriatic basin does not exist in open literature, so accuracy of employing traditional parametric models developed on the basis of measure-ments under condition of open and fully developed seas, is not known. Alternatively, statis-tics of clutter (and target) returns can be extracted from estimated probability density, exclu-sively on the basis of radar return samples (signatures), taken in the vicinity of tracked target. Treating measurements as noiseless opens up possibility of their probability density estimation by means of a neural network, employing property of universal approximation. Radial basis function network exhibits favorable ratio of estimation accuracy to computing time which is important for real-time application. In scenario of tracking a small rubber boat masked with waves, traditional Swerling model does not describe target echo, contaminated with echoes from waves, well. Neural network as density estimator employed in scenario of heavy-tailed clutter results in probability of tracking true target of 0.3, in comparison with 0.01 which re-sults from employment of parametric Swerling model. Minimum of 64 quantization levels are needed for amplitude information transfer from remote radar sensor without significant losses.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:822654
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Catalog URLhttp://lib.fer.hr/cgi-bin/koha/opac-detail.pl?biblionumber=52326
Type of resourceText
Extentiii, 455 str.
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-03-09 14:08:05