Ant Colony Optimization Algorithm GPS Clustering Approach

The geometry of the GPS satellite recipient (s), which reflects the recipient (s) of the satellites, has a major influence on the total positioning precision. The more precise the position, the stronger the geometry of the satellite. This article provides the geometry of satellite clustering for the...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. Conference series Vol. 2040; no. 1; pp. 12011 - 12016
Main Authors: Grace Mercy, M., Kamala Kumari, A., Bhujangarao, A., Nooka Raju, V.
Format: Journal Article
Language:English
Published: IOP Publishing 01.10.2021
Subjects:
ACO
Clustering
GDOP
GPS
ISSN:1742-6588, 1742-6596
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The geometry of the GPS satellite recipient (s), which reflects the recipient (s) of the satellites, has a major influence on the total positioning precision. The more precise the position, the stronger the geometry of the satellite. This article provides the geometry of satellite clustering for the selection of suitable satellite navigation subsets. This technique is based on the GDOP (Geometric Precision Dilution) satellite factor cluster with the Ant Colony Optimization (ACO) algorithm that has been created by simulating real and artificial ways to locate the quickest route between nesting resources and food. Pheromones are utilised in the suggested technique to assess the iterative outcome of single colonies. The ACO method can measure all subsets of satellites while reducing computer load by eliminating the need for a matrix inversion. Based on the simulation results, the GPS GDOP clustering technique is more efficient at achieving its optimum value.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2040/1/012011