Melola Discovery

← Melola Discovery

Journal SINTA 3

MISSILE POSITION ESTIMATION USING UNSCENTED KALMAN FILTER

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 1 (2022) · pp. 207–216

DOI
10.30598/barekengvol16iss1pp205-214
ISSN
2615-3017, 1978-7227
Published
2022-03-21
Publisher
PATTIMURA UNIVERSITY
Language
eng

Abstract

Missiles are military rocket weapons having an automatic control system to locate its targets or adjust its direction. Indonesia itself, which is a country of archipelago, covers air area of its largest territory, followed by sea area and land area. Logically, the existence of missile defense equipment (the main weapon system) or precisely the type of long-range missile is acceptable to support the defense and security of the Republic of Indonesia, but its consequences to be operated in the territory of Indonesia itself, in case of an occufanct of an error in targeting the target, will fall on of harm to its own national territory. Therefore, trajectory estimation for guided missiles is the basic requirement for guided missiles to be aimed at the precise targets. The trajectory is used as a guide to direct that the missile reach the target by following the given path. To maintain the accuracy of the trajectory continuously, the missile trajectory estimation was made by using Unscented Kalman Filter (UKF) Algorithm. This algorithm was used to estimate nonlinear dynamic models The simulation results showed that the UKF method was effective, showing the accuracy of 97% by the UKF method

Collaboration network of the authors

40 authors · 128 co-authorship links · 84 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Institut Teknologi Sepuluh Nopember
  • Universitas Nahdlatul Ulama Surabaya
  • Institut Teknologi Adhi Tama Surabaya
  • Darul Ulum Islamic University
  • Universitas Airlangga
  • Universitas Pattimura
  • University of Malaya
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Hendro NurhadiInstitut Teknologi Sepuluh Nopember7
Berny Pebo TomasouwUniversitas Pattimura6
Andy SuryowinotoInstitut Teknologi Adhi Tama Surabaya5
Dinita RahmaliaDarul Ulum Islamic University4
Fajar Annas SusantoUniversitas Nahdlatul Ulama Surabaya4
Dieky AdzkiyaInstitut Teknologi Sepuluh Nopember3
Hamzah ArofUniversity of Malaya3
Sari CahyaningtiasArizona State University2
Firman YudiantoUniversitas Nahdlatul Ulama Surabaya2
Katherin IndriawatiInstitut Teknologi Sepuluh Nopember2
Reza Maliki AkbarInstitut Teknologi Sepuluh Nopember2
Aji Akbar FirdausUniversitas Airlangga2
Vaizal Asy’ariUniversity of Pembangunan Nasional Veteran Jawa Timur2
Erna AprilianiInstitut Teknologi Sepuluh Nopember1
Mayga KikiInstitut Teknologi Sepuluh Nopember1
Thomy Eko SaputroUniversitas Muhammadiyah Malang1
Tahiyatul AsfihaniAffiliation unknown1
Irma FitriaInstitut Teknologi Kalimantan1
Talitha B AtlantaInstitut Teknologi Sepuluh Nopember1
Nadia AzahraInstitut Teknologi Sepuluh Nopember1
Choiriyah Sapta AgustinaInstitut Teknologi Sepuluh Nopember1
Moch ZakariaInstitut Teknologi Adhi Tama Surabaya1
Abdul MuhithDarul Ulum Islamic University1
Dian AdriantoPusat Hidro-Oseanografi Angkatan Laut1
Muhammad Sawal BaitalDiponegoro University1
Angga Adhitya WidjanarkoInstitut Teknologi Adhi Tama Surabaya1
Yuliyanto Agung PrabowoInstitut Teknologi Adhi Tama Surabaya1
Nyoman JuniartaUniversité de Lorraine1
Ragil Puji RahayuUniversitas Nahdlatul Ulama Surabaya1
Dina NovitaUniversitas Muhammadiyah Surabaya1
Arasy AlimudinUniversitas Narotama1
Akas Yekti Pulih AsihUniversitas Nahdlatul Ulama Surabaya1
Puguh TriwinantoNational Research and Innovation Agency1
Rachman Sinatriya MarjiantoUniversitas Airlangga1
Hendro NurhadiInstitut Teknologi Sepuluh Nopember1
Mohamad Yusak AnshoriAffiliation unknown1
Teay ShawyunAffiliation unknown1
Dennis V. MadrigalAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">MISSILE POSITION ESTIMATION USING UNSCENTED KALMAN FILTER</dc:title>
	<dc:creator>Herlambang, Teguh</dc:creator>
	<dc:creator>Subchan, Subchan</dc:creator>
	<dc:description xml:lang="en-US">Missiles are military rocket weapons having an automatic control system to locate its targets or adjust its direction. Indonesia itself, which is a country of archipelago, covers air area of its largest territory, followed by sea area and land area. Logically, the existence of missile defense equipment (the main weapon system) or precisely the type of long-range missile is acceptable to support the defense and security of the Republic of Indonesia, but its consequences to be operated in the territory of Indonesia itself, in case of an occufanct of an error in targeting the target, will fall on of harm to its own national territory. Therefore, trajectory estimation for guided missiles is the basic requirement for guided missiles to be aimed at the precise targets. The trajectory is used as a guide to direct that the missile reach the target by following the given path. To maintain the accuracy of the trajectory continuously, the missile trajectory estimation was made by using Unscented Kalman Filter (UKF) Algorithm. This algorithm was used to estimate nonlinear dynamic models The simulation results showed that the UKF method was effective, showing the accuracy of 97% by the UKF method</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-03-21</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4922</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss1pp205-214</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 207-216</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss1year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>info:eu-repo/grantAgreement/EC/FP7/123456</dc:relation>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4922/4023</dc:relation>
	<dc:rights xml:lang="en-US">info:eu-repo/semantics/openAccess</dc:rights>
</oai_dc:dc>