Design Coverage Optimization Based on Position of Constellations and Cost of the Launch Vehicle

This research will analyze the tradeoffs between coverage optimization based on Position dilution of precision (PDOP) and cost of the launch vehicle. It adopts MATLAB and STK tools along with multiple objective genetic algorithms (MOGA) to explore the trade space for the constellation designs at different orbital altitudes. The objective of optimal design solutions is inferred to determine the economic and efficient LEO, MEO, HEO or hybrid constellations and simulation results are presented to optimize the design of satellite constellations. The benefits of this research are the optimization of satellite constellation design, which reduces costs and increases regional and global coverage with the least number of satellites. The result of this project is the optimization of the number of constellation satellites in several orbital planes in LEO orbit. Validations are based on reviewing the results of several simulations. The results of graphs and tables are presented in the last two sections and are taken from the results of several simulations.

Cost-Efficient LEO Navigation Augmentation Constellation Design under a Constrained Deployment Approach

The advantages of the Low Earth Orbit (LEO) satellite include low-latency communications, shorter positioning time, higher positioning accuracy, and lower launching, building, and maintenance costs. Thus, the introduction of LEO satellite constellation as a regional navigation augmentation system for the current navigation constellations is studied in this paper. To achieve the navigation performance requirement with the least system cost, a synthetic approach is presented to design and deploy a cost-efficient LEO navigation augmentation constellation over 108 key cities. To achieve lower construction costs, the constellation is designed to be deployed by constrained piggyback launches, which brings additional complexity to the constellation design. Two optimization models with discrete and continuous performance indices are established. They are solved by the genetic algorithm and differential evolution algorithm, and both Walker and Flower constellations are adopted. Results for 77 and 70 satellites are obtained. During the construction phase, a synthesis procedure containing five impulses is proposed by utilizing natural drift under J 2 perturbation. This work presents a method for designing the optimal LEO navigation constellation under a constraint deployment approach with the lowest construction cost and a strategy to deploy the constellation economically.

Effects of Staged Deployment on the Economics of Global Broadband Internet Satellite Constellations

Historically constellations of communication satellites were designed to function optimally for a specific expected global demand. This estimation is based on assumptions of the number of users and the average activity per user, both of which are highly uncertain. This uncertainty can cause deployed constellations having a capacity far lower than demand, lowering performance and creating opportunity cost, or far higher than demand, potentially bankrupting the company that owns the system as income cannot recoup the initial investment. An approach has previously been proposed wherein a satellite constellation is deployed in stages with each stage increasing the capacity of the constellation through reconfiguration of on-orbit satellites and launch of new satellites. This method has been previously demonstrated to significantly reduce the lifecycle cost of low-earth orbit communication satellite constellations. Recent proposals for satellite constellations to support global broadband internet providers have introduced new technologies as well as new methods of constellation design resulting in far larger constellations than previously envisioned (mega-constellations). Renewed interest and investment in the development global broadband networks demand a return to this topic to investigate its impact in this space.