Ant Colony Optimization Algorithm GPS Clustering Approach - Grace Mercy, M.; Kamala Kumari, A.; Bhujangarao, A.; Nooka Raju, V. (Journal of physics. Conference series, 2021)
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.