Design of satellite constellation with inter-satellite links for global communication using genetic algorithm

The paper describes optimization Non-GEO satellite constellation design with satellite diversity using genetic algorithm. This algorithm is called as genetic satellite constellation algorithm. A rank fitness assignment method of multiobjective optimization is proposed to capture a number of solutions simultaneously. The non-dominated in GA’s is sorted to find the multiple Pareto optimal points. The genetic satellite constellation algorithm is investigated to produce the optimum satellite constellation design with the minimum number of satellites while minimizing the maximum orbit’s altitude, to minimize the angle shift between satellites, to maximize the angle between planes and the inclination angle with satellite diversity. Illustrative results of satellite constellation components and dual satellite diversity statistics for LEO and MEO constellation are presented. The simulation results are compared to ICO for MEO constellation and to Globalstar for LEO constellation. Using genetic algorithm, satellite constellation design can be achieved the visibility of dual satellite diversity statistics whilst reducing the total number of satellites. Genetic algorithm is a robust method ideally suited for satellite constellation design.

Novel strategies for automatic satellite constellation design with satellite diversity and radio resource management are proposed. The automatic satellite constellation design means that some parameters of satellite constellation design can be determined simultaneously. The total number of satellites, the altitude of a satellite, the angle between planes, the angle shift between satellites and the inclination angle are considered in the design. Satellite constellation design is modelled using a multiobjective genetic algorithm. This method is applied to low Earth orbit (LEO), medium Earth orbit (MEO) and hybrid constellations. The use of a genetic algorithm allows automatic satellite constellation design while achieving dual satellite diversity statistics. Furthermore, a strategy for dynamic channel allocation is proposed that uses a genetic algorithm for use in mobile satellite systems (MSS) networks. The main idea behind this algorithm is to use the minimum cost as a metric to provide optimum channel solutions for specified interference constraints. The simulation is designed for a MEO satellite constellation. Using this algorithm, the proposed model outperforms conventional dynamic channel assignment (DCA) schemes in terms of call blocking and call dropping probability. Generally, genetic algorithms are robust to dynamic variations in satellite constellation design and provide resource allocation improvements in DCA in MSS networks.

Satellite constellation designers take into consideration the entire telecommunication network and their design choices are influenced by many factors including: number of satellites, orbital characteristics, coverage area, network interconnections, system cost, and complexity. When the satellite constellation design method does not include a large number of possible configurations, then the final result of the design process is a suboptimal solution. Flower Constellation (FC) design provides a relatively new design approach which can overcome this problem. The time evolution of the FC theory is here summarized and the fundamental mathematics allowing the constellation design is provided. In particular, the theory is applied to the design and optimization of constellations maximizing the global coverage and the network connectivity via intersatellite links. Performance results are compared to the classical type of satellite constellations, i.e., the Walker Constellations. The performance improvement provided by FC design with respect to Walker Constellation design is shown. Finally, considerations regarding the cost for deployment and orbital control are also provided.

The wireless satellite communication system is considered to be the most promising new communication method to achieve the coverage of heaven, earth and sea. Satellite constellation design is the most important stage before the actual deployment of satellites. It will determine the number of satellites and orbit related parameters. We aim to study the constellation design of 5G low-orbit satellites. At present, some advanced research results have been proposed, providing important theory and experience for in-depth exploration and improvement of satellite constellation structure. We proposed a method based on the multi-objective particle swarm optimization (PSO) algorithm for designing low-orbit 5G satellite constellation. The method takes the number of satellites and orbit related parameters as the limit, and take the coverage of a specific area as the objective function. The results showed that the PSO algorithm can meet the full-time and full-area coverage low-orbit 5G constellation design for a specific area, and verified the effectiveness of the PSO algorithm for the coverage low-orbit 5G constellation design for the target area. We provided satellite constellation coverage guarantee for link-level simulation of 5g LEO satellite communication system in the next step.

The analytical model for Earth coverage by the satellites’ swath conforming to essential of discontinuous coverage, in contrast to continuous coverage, is presented. The analytic relations are consecutively derived for calculation of singleand multi-satellite Earth surface latitude coverage as well as for generating full set of typical satellite visibility zone time streams realized in the repeating latitude coverage pattern for given arbitrary satellite constellation. The analytic relations mentioned are used for developing the method for analysis of discontinuous coverage of fixed arbitrary Earth region for given satellite constellation using both deterministic and stochastic approaches. The method provides analysis of the revisit time for given satellite constellation, as a result of high speed (fractions of a second or seconds) computer calculations in a wide range of possible revisit time variations for different practical purposes with high accuracy which is at least on par with that provided by known numerical simulating methods, based on direct modelling of the satellite observation mission, or in a number of cases is even superior to it (due to the fact that when using the analytic procedures observation sessions cannot be missed). The method for synthesis of satellite orbits and constellations, optimized by given criterion (minimum of required number of satellites in the constellation, or minimum revisit time, or minimum of the satellites’ swath width required) for fixed parameters of on-board satellite equipment and constraints for unused criterion parameters of a list of mentioned above is presented. The numerical results demonstrate the possibilities of the methods developed for analyzing the given satellite constellation revisit time values distributed on the fixed Earth coverage area, and for synthesizing the satellite constellations in comparison with the traditional approaches based on constellation design in a priori fixed classes used for continuous coverage. Particularly, it is shown that the suggested method for synthesis of Secure Route Constellations, using deterministic and stochastic basis, directly leads to the optimized satellite constellations which provide consistently high performance and are at least on the same level, or better, in comparison with the best Walker constellations for discontinuous coverage.

As a huge space system, satellite constellation is developing rapidly. Satellite constellation design is a basic problem in the design of multi spacecraft space system. It is the premise of building constellation of earth observation, satellite navigation, satellite communication and various scientific exploration satellites. According to the characteristics of modern satellite constellation design, this paper investigates the design and application of particle swarm optimization algorithm in satellite constellation, and the latest research progress of various research institutions in satellite constellation maintenance and control, autonomous navigation and space real-time monitoring, and discusses the latest strategies and technical methods of satellite constellation operation and management.KeywordsSatellite constellationParticle Swarm OptimizationLocalizationMappingPosition precision

The way to solve the problem of satellite constellation design was outlined in the 1960s, recognizing the importance of satellite coverage (continuous or periodic) function and allowing interpretation of the operation of different types of space systems. Due to the fact that Earth periodic coverage optimization is extremely complex, for many years, the solutions of this problem have been searched for among a priori fixed constellation types successfully implemented before for continuous coverage, with continuous coverage seeming to be much easier than periodic coverage. In this study, it is shown that the technological advance in satellite constellation design for periodic coverage could be achieved by considering it as a unique and separate problem. The introduction in the route theory for satellite constellation design for Earth periodic coverage that aims at creating methods for optimization of arbitrary constellations, which is an alternative to the traditional approach that considers narrow classes of constellations to be analyzed, is described. The so-called route constellation is presented as a mathematical abstraction for approximation of arbitrary satellite constellation. The theory elements of the optimization procedure in the infinite domain of route constellations are introduced. Previously unknown regularities in Earth periodic coverage and in localization of optimal low-Earth-orbit satellite constellation parameters are presented and illustrated.

In recent years, the low-orbit satellites constellation has developed rapidly at home and abroad, involving navigation, remote sensing, communications, the internet and other fields. The performance of constellations will be influenced by multi-fold coverage heavily. For instance, remote sensing satellite constellations can improve the resolution of ground imaging through double coverage that two satellites can take ground photos get together at adjacent positions. There are more scholars studying continuous global coverage constellation, but less two-fold coverage or more. This article proposes the two-fold coverage width based on this hot demand about remote sensing satellite constellations, and proposes a constellation optimization design process. Then initial constellation parameters will be obtained from the single continue global coverage satellite constellation designed by the SOC method. The constellation will be optimized by the method proposed multiple iterations in this paper. Finally, the optimized constellations satisfied the function of two-fold coverage width and has better performance of the digital transmission opportunities to ground. The designed constellation satisfies the demand of two-fold coverage and has certain reference significance for engineering practice.

Frequent and reliable observation of ground targets is critical for an Earth observation satellite constellation. Limited satellite numbers often result in long revisit intervals. This study aims to minimize the worst-case revisit time in satellite constellation design. The paper proposes an integer linear programming (ILP)-based framework under common ground track constraints. The framework optimizes seed orbital elements and discretizes possible satellite phases for inclusion in the ILP. In a low-Earth orbit case study, the approach reduces the worst-case revisit time by over 60% compared to a symmetric constellation. The ILP-based method provides a systematic, computationally efficient solution for minimizing worst-case revisit time in constellation pattern design. Future work can extend the framework to account for multiple ground targets and incorporate additional measures of effectiveness.

In this study, single and also multi-objective (MO) genetic algorithms (GAs) were used for optimisation of performance and emissions of a diesel engine. Population space and initial population of both GAs were obtained by Artificial Neural Network (ANN). Specific fuel consumption (Sfc), NOx, power (P), torque (Tq) and air-flow rate (Afr) were reduced to %7.7, %8.51, %30, %4 and %7.4 respectively whereas HC increased at the rate of %10.5 by traditional single objective GA. HC, CO2, P and Sfc were reduced to %17.6, %30.05, %31.8 and %14.5 respectively whereas NOx increased at the rate of %13 by using multi-objective GA with Nondominated Sorting Genetic Algorithm II (NSGA II). %14.5 fuel reduction against %31 power reduction have never been obtained in the previous studies. This shows the effective usage of MOGA with NSGA II in optimisation of fuel diesel engine performance parameters.

A method of autonomous orbit determination for a satellite constellation using a star sensor combined with inter satellite links (ISLs) is studied. Two types of simulated observation data, Three-Satellite Constellation ISLs and background stellar observations by a CCD star sensor, are first produced. Based on these data, an observation equation is built for the constellation joint autonomous orbit determination, in which the simulations are run. The accuracy of this method with different orbital determination models are analyzed and compared with regard to the effect of potential measurement errors. The results show that autonomous satellite constellation orbit determination using star sensor measurement and ISLs data is feasible. Finally, this paper arrives at several conclusions which contribute to extending this method to a more general satellite constellation.

Topological dynamics and periodicity are two of the major differences between LEO satellite networks and terrestrial networks. In this work, we first propose MAPSS (Method to Analyze Periodicity of Satellite System) to obtain the system period of satellite networks based on spectral analysis. Then the topological dynamics of satellite networks, including the number of snapshots in one system period, is characterized by using this new method. Our method could be used in the development of routing algorithms as well as the design of satellite constellation.

The radiated signal of user equipment enters into the station effectively only with the proper power, so effective isotropic radiated power (EIRP) is the main factor for design of user equipment. The precise value of EIRP is measured in the two dimensional plane condition of darkroom. While in outside circumstance, ERIP is calculated complicatedly by many parameters of communication route, but the final result is not right. In this paper, to satisfy the operation need of Comprehensive Radio Navigation Satellite Service (CRDSS), emission route is abstracted into mathematical models, apart from the circumstance, distance and device factor, the angle formed by antenna and satellite is taken and the right valve of EIRP of multiple satellites is got simultaneously by the geometry relation of solid space. EIRP measurement is executed on the GEO and IGSO satellite by this way, it is useful for evaluation of effective entrance range to the station and design of satellite constellation. On the basis, the concept of extended angle is proposed to testify the practicableness of satellite. Experiment data in the east and west polar region of china proves out this measurement way. The conclusion is that ERIP of 4dBw is proper lower limit for signal to enter into the station in the condition of satellite constellation and signal processing.KeywordsCRDSSEIRPEffective extended angleLink calculation

This paper investigates UAV conceptual design using optimization methods. The conceptual design of a Medium Altitude Long Endurance (MALE) UAV is formulated as two different optimization problems. The optimization problems use a single objective and dual objective functions. For the single objective case, endurance maximization of the UAV is taken as the objective function with aspect ratio and wing loading as design variables. Wing weight, stall speed, maximum speed and rate of climb are taken as constraints. In the dual objective case, minimizing weight is removed from the constraint set and added as the second objective and four more design variables namely taper ratio, thickness to chord ratio, loiter velocity and loiter altitude are added. In the single objective case, both conventional optimization algorithm and genetic algorithm are used to solve the problem and identical results are obtained. A newly developed multi-objective evolutionary algorithm named NSGA-II (non-dominated sorting genetic algorithm) is used to capture the full Pareto front for the dual objective problem. For the dual objective case, numerical results show that several useful Pareto optimal designs exist for the conceptual design of UAV. These Pareto points are thoroughly analyzed for use in detailed design.

This paper discusses the effectiveness and/or usefulness of the inter-satellite link (ISL) in a global gigabit satellite communications system, in terms of technology and applications. In order to make such a discussion easy, first, work statement of this study is discussed. Second, a gigabit information space corridor is assumed to be a satellite communications infrastructure that a satellite constellation having a orbit of 15,500 km altitude on the equatorial plane is linked up via a gigabit (approximately 10 Gbps) ISL to provide a continuous communications and global connection as a competitive communications system with a terrestrial optical fiber cable system. Third, tile effectiveness of the ISL for the gigabit information space corridor in the global area is discussed. Finally, the technical aspect of ISL and its related technology are discussed and traded-off briefly. this system as Space Information Super Corridor on an Equatorial Orbit (SISCEO). Third,