Yüksek Lisans Tezi Görüntüleme

Student: Barış Metin TÜZÜNER
Supervisor: Dr. Öğr. Üyesi Oğuzhan ÇAKIR
Department: Elektrik-Elektronik Müh.
Institution: Fen Bilimleri Enstitüsü
University: Karadeniz Teknik Üniversitesi
Title of the Thesis: TIME DIFFERENCE OF ARRIVAL BASED TARGET POSITIONING WITH INTUITIVE OPTIMIZATION METHODS
Level: Yüksek Lisans
Acceptance Date: 17/11/2021
Number of Pages: 78
Registration Number: i3953
Summary:

      Precise location determination is possible using electromagnetic, acoustic, or seismic signals emanating from a target or source and spatially separated receivers. When the strength of the received signal and the ambient attenuation are known, the location circles, which are the central receivers, can be defined and the target can be located at the intersection of these circles. There is no need for transmitter-receiver or receiver-receiver synchronization in position detection with received signal strength (RSS). However, the positioning accuracy of the method is not high. When there is synchronization between the target and the receivers or when the signal emitted from the source is known on the receiving side, it is possible to determine the position of the target with the arrival times. In this technique, the intersection point of the location circles with the receivers in the center gives the transmitter coordinates, as in the location determination with the ASG. The accuracy of the method is high, and it cannot be used in passive radar applications because it requires transmitter-receiver synchronization. On the other hand, target coordinates can be found passively using the time difference of arrivals (TDOA) of the emitted signal from the synchronous receivers located spatially apart from each other. In this masters thesis, the position of a fixed or moving target is passively found by using independent (spherical) and full TDOA sets based fitness functions and heuristic optimization methods. For the first time in this thesis, position detection with independent and full VZF sets was performed using krill herd optimization (KHO), and the quadratic positioning error of KHO was compared with particle swarm optimization and Cramer-Rao lower bound (CRLB). In addition, simulation studies have shown that the convergence speed of the KHO algorithm is higher than PSO, and it has been revealed that the theoretical limit (CRLB) defined for the independent TDOA set can be exceeded with KHO when the full TDOA set is used.