Distributed LEO Satellite Virtual Swarm

Global Navigation Satellite Systems (GNSSs) are by far the most widespread technology for Position Navigation and Timing (PNT). They have been traditionally deployed exploiting Medium Earth Orbit (MEO) or Geostationary Earth Orbit (GEO) satellite constellations. To meet future demands and overcome MEO and GEO limitations, GNSSs based on Low Earth Orbit (LEO) constellations have been investigated as a radical system change. Although characterized by a higher Doppler effect, a PNT service supplied by means of LEO satellites can provide received signals that are about 30 dB stronger. Moreover, existing LEO constellations and the forthcoming mega-constellations, which are designed for broadband internet coverage, can be exploited to provide a piggybacked PNT service. With this cost-effective solution, a secondary PNT service might be subject to an economical use of resources, which may result in substantial bandwidth limitations. At the same time, the introduction of meta-signals in the GNSS literature has brought a new receiver signal processing strategy, particularly effective in terms of available bandwidth exploitation. It allows to increase the positioning accuracy exploiting a wideband processing approach, which might be challenging under severe Doppler conditions. A narrowband implementation of the meta-signal concept, namely Virtual Wideband (VWB) can tolerate harsh Doppler conditions while also reducing the processed bandwidth. It is thus more effective when addressing a secondary PNT service, where a limited frequency occupation might be an essential requirement. The aim of this work is to show the applicability of a VWB receiver architecture on signals provided by a piggybacked PNT service, hosted on a broadband LEO constellation. We demonstrate the capability of this implementation to bear high Doppler conditions while empowering the potential of LEO PNT.

A non-terrestrial system that uses Terahertz (THz) frequencies is a potential solution to achieving equal access to the Internet worldwide. This paper describes a non-terrestrial system that consists of a Low Earth Orbit (LEO) constellation, Earth Stations in Motion (ESIMs) and standard Earth stations. We examine the effects of rain, fog, clouds and atmospheric gases for this non-terrestrial system for frequencies between 100-300 GHz. The research findings suggest that the frequency bands between 102 - 109.5 GHz are rather suitable for communication between Earth stations and satellites, including ESIMs, reaching in a critical scenario uplink data rates of up to 2.6 Gbits/s with 0.5 GHz of bandwidth or up to 12 Gbits/s with 5 GHz of bandwidth in uplink. For the downlink, we can reach up to 6 Mbits/s with a transmitted power of 29 dBW, but if we increase the power transmitted by satellites, it is possible to reach up to 25 Gbits/s with 2.5GHz of bandwidth. Under clear, blue-sky conditions, we can achieve a maximum data rate of 17.3 Gbits/s for downlink and uplink. For inter-satellite links (communications between satellites in the same orbit or between different orbits), the frequency bands between 111.8 - 114.25 GHz, 116 - 123 GHz, 174.5 - 182 GHz, 185 - 190 GHz are viable, offering speeds from 1.5 to 2.51 Gbits/s when using a uniform rectangular array with 625 radiating elements. This research provides new findings from the amalgamation of existing literature, which is crucial for the future allocation of optimal frequencies between 100 - 300 GHz for satellite services.

In mega low Earth orbit (LEO) satellite constellations, guaranteeing deterministic communication performance is essential for mission-critical applications and reliable service delivery. Unlike terrestrial networks, these large-scale satellite networks present unique challenges: highly dynamic topologies, significant propagation delays, limited on-board processing capabilities, and cumulative jitter uncertainty that increases with hop count. In this case, traditional deterministic mechanisms, i.e., Time-sensitive networking (TSN), become ineffective due to their inability to handle both the scale and dynamics of mega constellations. To address this issue, we propose a TSN-enabled LEO satellite network, whereby we derive single-hop delay upper bounds using network calculus, specifically accounting for high-priority preemption and dynamic satellite characteristics. Then we propose DomainR, a novel domain-based deterministic routing framework that effectively manages large-scale satellite networks through strategic network decomposition and adaptive routing. DomainR consists of two phases: first, a domain-based network compression phase that partitions mega constellations into manageable domains while preserving path continuity and routing efficiency, and, second, a delay budget-aware dynamic routing phase that adaptively allocates delay budgets based on aforementioned delay upper bounds and real-time network conditions. Through rigorous mathematical analysis, we derive the optimal domain sizing rules and establish a theoretical minimum domain count. Comprehensive simulations demonstrate that DomainR significantly reduces end-to-end jitter, improves network resource utilization, and capacity in mega LEO constellations.

The precise orbit determination (POD) accuracy of the Chinese BeiDou Navigation Satellite System (BDS) is still not comparable to that of the Global Positioning System because of the unfavorable geometry of the BDS and the uneven distribution of BDS ground monitoring stations. Fortunately, low Earth orbit (LEO) satellites, serving as fast moving stations, can efficiently improve BDS geometry. Nearly all studies on Global Navigation Satellite System POD enhancement using large LEO constellations are based on simulations and their results are usually overly optimistic. The receivers mounted on a spacecraft or an LEO satellite are usually different from geodetic receivers and the observation conditions in space are more challenging than those on the ground. The noise level of spaceborne observations needs to be carefully calibrated. Moreover, spaceborne observational errors caused by space weather events, i.e., solar geomagnetic storms, are usually ignored. Accordingly, in this study, the actual spaceborne observation noises are first analyzed and then used in subsequent observation simulations. Then, the observation residuals from the actual-processed LEO POD during a solar storm on 8 September 2017 are extracted and added to the simulated spaceborne observations. The effect of the observational errors on the BDS POD augmented with different LEO constellation configurations is analyzed. The results indicate that the noise levels from the Swarm-A, GRACE-A, and Sentinel-3A satellites are different and that the carrier-phase measurement noise ranges from 2 mm to 6 mm. Such different noise levels for LEO spaceborne observations cause considerable differences in the BDS POD solutions. Experiments calculating the augmented BDS POD for different LEO constellations considering spaceborne observational errors extracted from the solar storm indicate that these errors have a significant influence on the accuracy of the BDS POD. The 3D root mean squares of the BDS GEO, IGSO, and MEO satellite orbits are 1.30 m, 1.16 m, and 1.02 m, respectively, with a Walker 2/1/0 LEO constellation, and increase to 1.57 m, 1.72 m, and 1.32 m, respectively, with a Walker 12/3/1 constellation. When the number of LEO satellites increases to 60, the precision of the BDS POD improves significantly to 0.89 m, 0.77 m, and 0.69 m for the GEO, IGSO, and MEO satellites, respectively. While 12 satellites are sufficient to enhance the BDS POD to the sub-decimeter level, up to 60 satellites can effectively reduce the influence of large spaceborne observational errors, i.e., from solar storms.

This paper presents a theoretical analysis of the potential risk posed by artificial debris clouds in low Earth orbit (LEO) from mega-constellations, modeled after current communication constellations such as Starlink and OneWeb with 750 satellites each. The analysis examines three different constellation designs: a low-altitude LEO, a high-altitude LEO, and a medium Earth orbit (MEO) constellation, which will be positioned using the Walker-Delta design. The study is based on physics-based digital mission engineering and a Monte Carlo simulation framework. The simulation involves debris generated from a single breakup of one randomly selected satellite per run, but does not consider cascading debris events. This debris cloud is propagated for 1 week and how it interacts with the mega-constellation is recorded. The results show an average of 705.65 potential conjunctions within the LEO constellation, with 14.40% of those being considered catastrophic, and an average of 165.5 conjunctions in the MEO constellation, with 0.72% considered catastrophic.

Navigation resource allocation for low-earth-orbit (LEO) constellations refers to the optimal allocation of navigational assets when the number and allocation of satellites in the LEO constellation have been determined. LEO constellations can not only transmit navigation enhancement signals but also enable space-based monitoring (SBM) for real-time assessment of GNSS signal quality. However, proximity in the frequencies of LEO navigation signals and SBM can lead to significant interference, necessitating isolated transmission and reception. This separation requires that SBM and navigation signal transmission be carried out by different satellites within the constellation, thus demanding a strategic allocation of satellite resources. Given the vast number of satellites and their rapid movement, the visibility among LEO, medium-earth-orbit (MEO), and geostationary orbit (GEO) satellites is highly dynamic, presenting substantial challenges in resource allocation due to the computational intensity involved. Therefore, this paper proposes an optimal allocation algorithm for LEO constellation navigation resources based on dynamic programming. In this algorithm, a network model for the allocation of navigation resources in LEO constellations is initially established. Under the constraints of visibility time windows and onboard transmission and reception isolation, the objective is set to minimize the number of LEO satellites used while achieving effective navigation signal transmission and SBM. The constraints of resource allocation and the mathematical expression of the optimization objective are derived. A dynamic programming approach is then employed to determine the optimal resource allocation scheme. Analytical results demonstrate that compared to Greedy and Divide-and-Conquer algorithms, this algorithm achieves the highest resource utilization rate and the lowest computational complexity, making it highly valuable for future resource allocation in LEO constellations.

The improvement of BDS Observation Geometry with LEO constellations in Orbit Determination

Low-cost and fast-response LEO(Low-Earth orbit) satellite network is an important technical means to meet the needs of communication and transmission services with periodic continuous coverage in specific regions. Aiming at this kind of problem, a method of LEO(Low-Earth orbit) constellation design combining analytical method and optimization method is proposed in this paper. Firstly, a regression orbit model and a typical sensor coverage model are established. Secondly, taking the optimal coverage effect of a specific region as the performance index, particle swarm optimization (PSO) was used to optimize and solve the orbit parameters of a single satellite. Finally, the orbit parameters of the constellation are solved by analytical method. This method can take into account the computational efficiency of analytical method and the universality of optimization method, and can realize the rapid solution of low-earth orbit constellation with periodic continuous coverage in local region, which has good engineering application value.KeywordsLEO (Low-Earth orbit)Periodic continuous coverageConstellationParticle swarm optimization (PSO)

The fast motion of low earth orbit (LEO) satellite contributes to the geometric diversity, allowing for rapid convergence of precise point positioning (PPP). In this contribution, we investigate the PPP performance of the LEO constellation-augmented full operational capability (FOC) multi-GNSS. We design six LEO constellations with different satellite numbers, orbit altitudes and orbit types, together with the FOC multi-GNSS constellations, and then simulate both the onboard LEO and ground-based observations. The multi-GNSS POD result shows much better orbit accuracy of 3.3, 2.7 and 2.6 cm in radial, along-track and cross-track components, respectively, compared with that of 10.3, 9.2 and 8.9 cm for GPS-only POD. Furthermore, the performance of LEO-augmented multi-GNSS PPP is evaluated. With the augmentation of 60-, 96-, 192- and 288-satellite LEO constellation, the multi-GNSS PPP convergence time can be shortened from 9.6 to 7.0, 3.2, 2.1 and 1.3 min, respectively, in midlatitude region. For LEO-augmented GPS- and BDS-only PPP, the improvement is more significant with the convergence time dramatically shortened by 90% from about 25 to within 3 min with 192- or 288-satellite constellation. The augmentation capability is also found to be associated with station latitude, and the higher latitude, the better performance. To enable about more than 70% significant reduction on convergence time, as well as considering the cost, the 192-satellite LEO constellation scheme is suggested. In terms of orbit altitude, the scheme of 1000 km presents better performance than that of 600 km. As for orbit type, the performances are comparable for polar and sun-synchronous orbits. Additionally, LEO-only PPP can be achieved with the convergence time of about 6.5 min.

This paper presents a lightweight satellite visualisation and simulation tool developed to support research and teaching related to Low Earth Orbit (LEO) systems. The simulator displays satellite orbits, city locations, visibility relationships between cities and satellites, a novel pathfinding algorithm to determine optimal routes between cities via LEO satellites with inter-satellite links, and caching functionality and visualisation. The simulator allows users to identify coverage areas and connectivity in LEO constellations, and supports faster-than-real-time simulation. Unlike many existing tools, it is optimised to run on low-end or general-purpose hardware, addressing a gap in accessible simulation platforms. The simulator can be integrated into broader research workflows or used as a standalone visual demonstration tool. The present paper’s authors demonstrate its capabilities through several use cases, including caching schemes and inter-satellite routing.

A new space race for low earth orbit (LEO) mega-constellation enabled internet services is imminent, with several commercial companies, e.g., SpaceX, Amazon, OneWeb, working forward to high speed LEO constellation with optical inter-satellite link (ISL). Grid-mesh topology is commonly utilized for LEO constellation, even if it is not the best topology. But constellation structure design, as a more fundamental work than topology design, has not been investigated thoroughly. For a given LEO mega-constellation with a fixed amount of satellite, this paper explores the impact of constellation structure on network performance by adjusting the number of orbital planes. Simulation results show that under the inclined walker-delta model, the optimal network performance in terms of average/maximum hops is achieved while the difference value between the number of orbital plane and satellites per orbital plane is minimal. In addition, link congestion under shortest path routing scheme is also optimized with the proposed mega-constellation structure.

This work develops an analytical framework for downlink low Earth orbit (LEO) or medium Earth orbit (MEO) satellite communications, leveraging tools from stochastic geometry. We propose a tractable approach to the analysis of such satellite communication systems, accounting for the fact that satellites are located on circular orbits. We accurately incorporate this geometric property of LEO or MEO satellite constellations by developing a Cox point process model that jointly produces orbits and satellites on these orbits. Our work contrasts with previous modeling studies that presumed satellite locations to be entirely random, thereby overlooking the fundamental fact that satellites are jointly positioned on orbits. Employing this Cox model, we analyze the network performance experienced by users located on Earth. Specifically, we evaluate the no-satellite probability of the proposed network and the Laplace transform of the interference created by such a network. Using it, we compute its SIR (signalto-interference) distribution, namely its coverage probability. By presenting fundamental network performance as functions of key parameters, this model allows one to assess the statistical properties of downlink LEO or MEO satellite communications and can thus be used as a system-level design tool to operate and optimize forthcoming complex LEO or MEO satellite networks.

As small satellites become more capable through miniaturized electronics and on-board processing, constellations of low-cost satellites lunched in Low-Earth Orbit (LEO) become feasible. The increase in the number of LEO satellites drives the need for frequency coexistence between the LEO constellation systems with the already existing geostationary (GSO) satellite networks. In this context, it is crucial to design the communication links paying special attention to interference analysis. This is particularly true when the LEO satellite constellation exploit inter-satellite communication links (ISL). In this paper, a radio frequency interference analysis based on simulation of the dynamic satellite constellation is presented and the design parameters of the inter-satellite links are analyzed. The results suggest that carefully choosing the design parameters of the intersatellite links, spectrum coexistence of LEO and GSO networks may be possible.

In recent years, low earth orbit (LEO) satellite constellation systems have been developed rapidly. However, the scarcity of satellite spectrum resources has become one of the major obstacles to this trend. LEO satellite constellation communication systems sharing the spectrum of incumbent geostationary earth orbit (GEO) satellite system is a feasible way to alleviate spectrum scarcity. Therefore, it has practical significance to study the optimization of satellite resources allocation (RA) in a spectrum sharing scenario. This paper focuses on the RA problem that LEO satellites share a GEO high throughput satellite’s spectrum in a beam-hopping (BH) manner. The GEO satellite system is served as the primary system and the LEO satellite constellation system is served as the secondary system whose frequency bands and transmitting power are strictly limited. Compared with conventional multibeam satellites, BH satellites have the advantage of flexibility in the time dimension. Therefore, we make full use of the flexibility of LEO BH satellites to realize the matching of traffic demand and traffic supply. The RA problem is decomposed into three sub-problems, namely, frequency band selection (FBS) problem, illuminated cell selection (ICS) problem, and transmitting power allocation (TPA) problem. We solve each sub-problem in order and finally form a complete RA scheme. The performance evaluation of the proposed RA scheme is carried out in real-time and simulation results show that the LEO BH satellite paired with the RA scheme we proposed has good adaptability to the uneven distribution of traffic demand in the spectrum sharing scenario.

The Global Navigation Satellite System (GNSS) is strongly dependent on the choice of the satellite constellation. At the present time, the GNSS space segment is made by the following satellite constellations: GPS, GLONASS and a set of geostationary satellites. In a medium-long term future, a new GNSS could substitute the existing satellite navigation system, or, in any way, there will be an overlapping and an integration between the current system and the next one.Alenia Aerospazio, is studying, since 1990, the possibility to identify new navigation satellite constellations able to verify the Required Navigation Performance (RNP) for all users. Particular attention has been focused on airspace users, due to the fact that the accuracy requirements during the aircraft landing phases are very stringent, and the existing GPS system is not able to guarantee the desired RNP.In this paper a new satellite constellation with 75 satellites in Low Earth Orbit (LEO) at a common altitude of 2700 Km, and a common inclination of about 66°, has been identified. It is able to comply with the RNP (i.e. accuracy, availability, continuity, and integrity) up to CAT I landing.The transition phase between the co-existence of the current GNSS space segment and the evolving LEO constellation is discussed and analysed in this paper, outlining the advantages, with respect to the previous system, coming from the progressive implementation, in a step-wise fashion, of this LEO space segment, until its completion.KeywordsGlobal Navigation Satellite SystemGlobal Navigation Satellite SystemOrbital PlaneTime PercentageSatellite ConstellationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.