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Darius Andriukaitis
Kaunas University of Technology, Lithuania

Radu Arsinte
Technical University of Cluj Napoca, Romania

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Slovak University of Technology, Slovakia

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The University of Texas at Arlington, United States

Mohamed El Hachemi Benbouzid
University of Brest, France

Dalibor Biolek
University of Defence, Czech Republic

Klara Capova
University of Zilina, Slovakia

Ray-Guang Cheng
National Taiwan University of Science and Technology, Taiwan, Province of China

Erik Chromy
UPC Broadband Slovakia, Slovakia

Milan Dado
University of Zilina, Slovakia

Petr Drexler
Brno University of Technology, Czech Republic

Eva Gescheidtova
Brno University of Technology, Czech Republic

Gokhan Hakki Ilk
Ankara University, Turkey

Janusz Jezewski
Institute of Medical Technology and Equipment, Poland

Rene Kalus
VSB - Technical University of Ostrava, Czech Republic

Ivan Kasik
Academy of Sciences of the Czech Republic, Czech Republic

Jan Kohout
University of Defence, Czech Republic

Ondrej Krejcar
University of Hradec Kralove, Czech Republic

Zbigniew Leonowicz
Wroclaw University of Science and Technology, Poland

Miroslaw Luft
Technical University of Radom, Poland

Stanislav Marchevsky
Technical University of Kosice, Slovakia

Jerzy Mikulski
University of Economics in Katowice, Katowice, Poland

Karol Molnar
Honeywell International, Czech Republic

Thang Trung Nguyen
Ton Duc Thang University, Viet Nam

Miloslav Ohlidal
Brno University of Technology, Czech Republic

Neeta Pandey
Delhi Technological University, India

Alex Noel Joseph Raj
Shantou University, China

Marek Penhaker
VSB - Technical University of Ostrava, Czech Republic

Wasiu Oyewole Popoola
The University of Edinburgh, United Kingdom

Roman Prokop
Tomas Bata University in Zlin, Czech Republic

Karol Rastocny
University of Zilina, Slovakia

Marie Richterova
University of Defence, Czech Republic

Gheorghe Sebestyen-Pal
Technical University of Cluj Napoca, Romania

Sergey Vladimirovich Serebriannikov
National Research University "MPEI", Russian Federation

Yuriy Shmaliy
Guanajuato University, Mexico

Vladimir Schejbal
University of Pardubice, Czech Republic

Bohumil Skala
University of West Bohemia in Plzen, Czech Republic

Lorand Szabo
Technical University of Cluj Napoca, Romania

Adam Szelag
Warsaw University of Technology, Poland

Ahmadreza Tabesh
Isfahan University of Technology, Iran, Islamic Republic Of

Mauro Tropea
DIMES Department of University of Calabria, Italy

Viktor Valouch
Academy of Sciences of the Czech Republic, Czech Republic

Jiri Vodrazka
Czech Technical University in Prague, Czech Republic

Miroslav Voznak
VSB - Technical University of Ostrava, Czech Republic

He Wen
Hunan University, China

Otakar Wilfert
Brno University of Technology, Czech Republic


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Position Estimation Bias Analysis of a Multilateration System with a Reference Station Selection Technique

Abdulmalik Shehu Yaro, Ahmad Zuri Sha'ameri, Nidal Kamel

DOI: 10.15598/aeee.v16i3.2776


Abstract

Multilateration (MLAT) system estimates the position of an aircraft using Time Difference of Arrival (TDOA) measurements estimated at spatially located Ground Receiving Station (GRS) pairs with a lateration algorithm. The Position Estimation (PE) accuracy of an MLAT system depends on several factors, one of which is the choice of reference station used to generate the TDOA estimations for use with the lateration algorithm. Furthermore, the closed-form lateration algorithm is known to introduce bias in the PE process. Thus, a bias analysis and improvement in the PE accuracy of an MLAT system with a reference selection technique is presented in the paper. The analysis is carried out for a square GRS configuration with each GRS equipped with a receiver whose Time of Reception (TOR) error Standard Deviation (SD) is assumed 1 nsec. Monte Carlo simulation result of lateration algorithm with reference selection technique shows a reduction of at least 75% in both the overall PE Mean Square Error (MSE) and bias. Furthermore, the PE Root Mean Square Error (RMSE) obtained by the lateration algorithm is reduced by at least 50% out of which 36% of the reduced PE RMSE is contributed only by the TOR estimation error.

Keywords


Bias analysis; MLAT; PE error; reference selection; TDOA.

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