Route Satellite Constellations for Earth Discontinuous Coverage and Optimal Solution Peculiarities

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.

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.

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.

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.

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.

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

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.

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.

This work presents a new evolutionary algorithm that searches over the space of satellite constellations to optimize coverage-related metrics (e.g. minimizing average revisit time or maximizing daily visibility time) while simultaneously minimizing the number of satellites and their semi-major axes. It utilizes a variable-length chromosome to represent a satellite constellation, two specialized operators to handle the variable-length chromosomes, and an adaptive operator selector that adjusts the search strategy during the optimization. The proposed chromosome encodes an m satellite constellation with m n-tuples, where each satellite is defined by an n-tuple (e.g. a subset of the orbital elements). Currently, evolutionary algorithms that optimize constellations employ a fixed-length chromosome where either 1) the maximum number of satellites in the constellation is pre-specified and each satellite has an extra Boolean variable that dictates whether to manifest the satellite in the constellation or 2) the algorithm is run several times, each time exploring constellations with a specific number of satellites. The chromosome representation in the former method has low-locality and is redundant, both of which makes the search more difficult for an evolutionary algorithm. The latter method does not take advantage of good partial solutions or schemata discovered for a constellation of a given size that could inform the design of another constellation with a different number of satellites. In contrast, a variable-length chromosome grows and contracts as the algorithm explores constellations with different numbers of satellites and significantly reduces the redundancy in the chromosome representation. The efficacy and efficiency of an optimization run using the proposed variable-length chromosome representation is benchmarked against a fixed-length chromosome on a multiobjective constellation design problem whose goal is to simultaneously minimize the global average revisit time, the number of satellites in the constellation, and the average semi-major axis of the satellites. Results show that the search conducted with the variable-length chromosome reaches a high-quality solution set using thousands of fewer function evaluations than a search with a fixed-length chromosome.

Fundamentals of the route theory for satellite constellation design for Earth discontinuous coverage. Part 3: Low-cost Earth observation with minimal satellite swath

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 the framework of the Global Navigation Satellite System, European industries are identifying and studying new satellite constellations able to cope with required navigation performance for terrestrial, maritime, air, and space users. Alenia Aerospazio has identie ed many new satellite constellations. (Some of them are constituted by low Earth orbits or intermediate circular orbits for global coverage; others consider satellites in high elliptical orbits or geosynchronous orbits for regional coverage. ) All of them have been compared in terms of navigation performance, e.g., accuracy, availability, continuity, and integrity. The best one is a constellation of 27 satellites located in intermediate circular orbits at a common altitude of 10,389 km and a common inclination of 57 deg. This constellation has been identie ed by the Walker method to e nd a space system able to guarantee a global and continuous coverage with low positioning dilution of precision values (always less than 4 )and with a coverage level equal to 6, i.e., from each point of the Earth surface it is always possible to see at least six of the satellites. After both thepayload design and thebudget have been identie ed and analyzed,thesatellite platform hasbeen designed, obtaining, in this way, mass, power, and propellant budgets. The launch strategy and the orbit acquisition phase have been dee ned.

Satellite navigation and positioning have become an indispensable component of smart devices and applications. In order to avoid signal interference in L1 frequency and provide novel services, Global Positioning System III (GPS III) updated a modern signal named L1C and tested in three Quasi-Zenith Satellite System (QZSS) satellites launched in 2017. In December 2018, the first GPS III satellite was launched, which implies the joint positioning using QZSS and GPS L1C signal is improved. L1C signal offers a series of advanced designs in signal modulation, message structure and coding, etc. In this regard, this paper presents complete methodologies for L1C signal joint receiving processing. For the on-air signals, this paper presents a methodology and results from collecting and assessing binary offset carrier (BOC) modulation and time-multiplexed BOC (TMBOC) modulation used in L1C signal. Using the same omnidirectional antenna and the test-equipment, the L1C signal was collected in Xi’an and Sanya, China, respectively. Experiments in Xi’an verified the joint positioning method to complement the GPS III and QZSS satellite constellations. The methodology in this paper evaluates the positioning error of BOC(1,1) and TMBOC(6,1,4/33) under the same environment and satellite constellation in Sanya. It is also verified that the joint positioning error is less than the QZSS-only positioning due to the optimization of the satellite constellation.

For a long time, the optimization of satellite constellations has been formulated as the minimization of the number of satellites which satisfy a given geometrical coverage criterion (eg: continuous coverage of the Earth above a given minimum elevation threshold). Many authors theoretically solved this problem for single and multiple satellite coverage but without considering any other criterion. With the advent of large navigation and commercial telecommunication satellite constellations, cost considerations have become mandatory for any constellation designer eager to achieve the best global cost/efficiency trade-offs between the user requirements and the services provided by the operator. The paper proposes and discusses a multi-criteria approach that is highlighting and simultaneously handling three driving criteria in any constellation optimization process: coverage performances, operational availability and life-cycle costs of the system. A reference telecommuniction mission is taken as a case study to illustrate the power of the proposed approach with respect to the classical optimization process.