Optimization design of global low-orbit satellite constellation for two-fold coverage

In recent years, the development of low-orbit satellite navigation enhancement systems has been rapid. Low-orbit navigation satellites have relatively low orbital altitudes, high signal landing power, and fast speed, which are expected to solve the problem of long convergence time for real-time precise single-point positioning of GNSS. This article evaluates and analyses the enhanced positioning performance of typical low-orbit satellite constellations. The study selected three representative low-orbit satellite constellations, combined with GPS, BDS, and GALILEO global satellite navigation systems. By establishing evaluation models and simulating data, a comprehensive evaluation was conducted on the coverage performance of precise point positioning. The results indicate that low-orbit satellite constellations have significant advantages in navigation enhancement and can effectively shorten the convergence time of GNSS precise point positioning. At the same time, the study also revealed the performance differences between different constellation systems, providing important references for the design and optimization of future low-orbit satellite navigation systems.

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 fundamental and significant stage of satellite networks which play an important role in global communications, a design of satellite constellations with inter-satellite links(ISLs) becomes necessary. An optimization method is proposed to determine both satellite elements and constellation elements using the multi-objective genetic algorithm(GA) in this paper. The objectives to be optimized, which are determined by the elements to be designed, are divided into performance objectives and cost objectives. The former consist of the coverage rate, the ISL range and the minimum elevation while the latter contain the total satellite count, the orbital altitude and the orbital inclination. With the aim of maximizing the performance minimizing the cost, the proposed method tries to achieve a balance among multi objectives and design specific satellite constellations considered in different conditions. Then the constellations designed in different schemes are compared with each other to demonstrate the correctness and effectiveness of the method.

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.

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.

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 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.

For many space missions using satellite constellations, symmetry of satellites distribution plays usually a key role. Symmetry may be considered in space and/or in time distribution. Examples of required symmetry in space distribution are in Earth observation missions (either, for local or global) as well as in navigation systems. It is intuitive that to optimally observe the Earth a satellite constellation should be synchronized with the Earth rotation rate. If a satellite constellation must be designed to constitute a communication network between Earth and Jupiter, then the orbital period of the constellation satellites should be synchronized with both Earth and Jupiter periods of revolution around the Sun. Another example is to design satellite constellations to optimally observe specific Earth sites or regions. Again, this satellites constellation should be synchronized with Earth’s rotational period and (since the time gap between two subsequent observations of the site should be constant) also implies time symmetry in satellites distribution. Obtaining this result will allow to design operational constellations for observing targets (sites, borders, regions) with persistence or assigned revisit times, while minimizing the number of satellites required. Constellations of satellites for continuous global or zonal Earth coverage have been well studied over the last twenty years, are well known and have been well documented [1], [2], [7], [8], [11], [13]. A symmetrical, inclined constellation, such as a Walker constellation [1], [2] provides excellent global coverage for remote sensing missions; however, applications where target revisit time or persistent observation are important lead to required variations of traditional designs [7], [8]. Also, few results are available that affect other figures of merit, such as continuous regional coverage and the systematic use of eccentric orbit constellations to optimize“hang time” over regions of interest. Optimization of such constellations is a complex problem and the general-purpose constellation design methodology used today is largely limited to Walker-like constellations. As opposed to Walker Constellations [1], [2], which were looking for symmetries in inertial reference frame, Flower Constellations [11] were devised to obtain symmetric distributions of satellites on rotating reference frames (e.g., Earth, Jupiter, satellite orbit). Since the theory of Flower Constellations has evolved with time the next section is dedicated to the summary of the theory up to the current status. The FCs solution space has been recently expanded with the Lattice theory [13], [14], encompassing all possible symmetric solutions.

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

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.

Large space-based communication networks have been growing in numbers of satellites, with plans to launch more than 10,000 satellites into Low Earth Orbit (LEO). While these constellations offer many advantages over ground-based communication systems, they pose a significant threat when they fail and generate space debris. Given the reliability of current satellites, engineers can use failure modeling to design satellite constellations that are more resilient to satellite failures. Several authors have analyzed the reliability of geostationary satellites, but few have expanded the work to multiple-satellite systems. To address this gap, we constructed a simulation model to show the performance of satellite constellations with different satellite reliability functions over time. The simulation model is broken down into four key parts: a satellite constellation model, a network model, a failure model, and a performance metric. We use a Walker star constellation, which is the most common constellation for LEO broadband satellite constellations. The network consists of satellite-to-satellite connections and satellite-to-groundstation connections, which routes data using a shortest-path algorithm. The failure model views satellites as either operational or failed (no partial failures) and considers the groundstation operator’s knowledge or lack thereof of the satellites’ operational status and uses satellite reliability to estimate the expected data throughput of the system. We also created a performance metric that measures how well the entire network is operating and helps us compare candidate constellations. We used the model to estimate performance for a range of satellite reliabilities, and for groundstations with different numbers of communication dishes (effectively, satellite-ground links). Satellite reliability is a significant contributing factor to the long-term constellation performance. Using the reliability of small-LEO satellites, we found that a constellation of 1,200 small-LEO satellites completely fails after less than 30 days, given that we do not consider partial failures. Satellite constellations with higher satellite reliability, such as large geostationary satellites, last less than 50 days. We expect the constellations in our model to perform worse than real satellite systems, since we are only modeling complete failures, however these findings provide a useful worst-case baseline for designing sustainable satellite constellations. We also found that the number of groundstation-to-satellite communication links at each groundstation is not a significant factor for more than five communication links, meaning that adding more communication antennas to existing satellite groundstations would not improve constellation performance significantly.

In this paper we analyze the coverage performance of satellite constellation in low earth orbit. First we analyze the various possible configurations of satellite failures in the same orbital plane or in different orbital planes when one satellite or a number of satellites are at fault. To evaluate the performance of each constellation we use one parameter, which is the maximum non-visibility time at one receiver position on Earth by using simulation software. We have also simulated the coverage performance variations depending on the receiver position on earth by varying the latitude of the receive position from 0 to 90 degrees. According to the results of the simulations we compare the maximum non-visibility time depending on the configuration of satellite and identify the worst case combination of satellite failures in satellite constellation. We also evaluate the performances the satellite constellations in 780 km orbit in case of a fault of some satellite in the same orbital plane or in different orbital plane. Finally we evaluate the some orbital manoeuvre strategy, (phase changing in the same orbital plane), to minimize the non-visibility time on Earth in case of failure of number of satellites.

With the rapid development of large-scale satellite constellations and the increasing demand for rapid communication and emergency rescue using global satellite-based Internet, there have been new requirements for efficient algorithms for inter-communication between satellites. As the constellations of low-orbit satellites become larger, the complexities of real-time inter-satellite calculation and path planning are becoming more complicated and are increasing geometrically. To address the bottlenecks in large-scale node space computing, we introduced a global space grid. Based on this grid, an efficient calculation method of spatial inter-connection between satellite constellations is proposed, according to the concept of “storage for computing” and the high computational efficiency of the spatial grid model. This strategy includes the following parts: (1) the introduction of the GeoSOT-3D global grid model into aerospace and the construction of the aerospace grid indexing BigTable; (2) a set of algorithms for satellite visibility analysis according to the visible grid look-up table and the secondary grid index; and (3) planning inter-satellite routing by querying the grid’s inherent visibility. The idea at the basis of this method is to employ the “space for time” concept to convert the high-dimensional floating operations into one-dimensional matching operations by querying the inherent “visible” attribute of the grid. In our study, we simulated thousands of satellites, discretized their trajectories into grids, and pre-calculated the visibility between grid cells to plan the routing path for the ground data transmission. The theoretical analysis and experimental verification show that the algorithm is feasible and efficient, and it can significantly improve the computational efficiency of inter-satellite connection. We hope that the method can be used in emergency communications, disaster warning, and maritime rescue, and can contribute to the next generation of satellite internet and “satellite-ground” integrated networks.

Mega low orbit satellite constellations are one of the largest commercial projects that will directly affect the daily lives of people. The most important achievement of these projects is inter alia the provision of internet access that could potentially cover the entire planet. However, despite these positive achievements, the challenges and environmental concerns pertaining to these projects should not be overlooked. These projects are typically carried on by private commercial companies. Furthermore, extensive international efforts have been made to ensure that these companies, in addition to their legally binding obligations, will behave in a socially responsible manner, which is referred to as “Corporate Social Responsibility”. Although the environmental dimension of corporate social responsibility is primarily considered to be the effects of the business on this planet, the interpretation used in this essay incorporates environmental effects in any place in which companies operate. While examining the principles governing corporate social responsibility, this article argues that the international space law is a good ground for the implementation of these principles by commercial companies operating in the mega satellite constellations industry.

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.