Satellite swarms and Satellite formation flying missions and technology

Rajesh Uppal April 30, 2023 AI & IT, Space Comments Off on Satellite swarms and Satellite formation flying missions and technology 648 Views

The increasing capability of small Micro, Nano and CubeSats satellites, besides its short development time, and launching cost, over traditional large satellites, leads to the trend of using MSM in Earth observation missions with different topology. These MSM topologies or categories can be classified as Satellite Constellation and satellite Formation Flying.

A satellite constellation (or swarm) is a network of identical or similar-type artificial units with the same purpose and shared control. Such groups communicate to worldwide-located ground stations and sometimes are inter-connected. They work as a system and are designed to complement each other. First, satellites in swarms revolve on several, usually similar orbits (orbital planes) ensuring uninterrupted or nearly uninterrupted global coverage. Second, individual constellation units can technically capture a vaster territory compared to a single remote sensing medium.

Swarms perform a number of tasks from fiber-like internet connectivity to multi-purpose Earth monitoring, obtaining quality imagery for subsequent AI-powered data procession by analytical platforms.

Satellite constellations

The number of satellites in a constellation depends on the purpose and varies from several to thousands of units. The largest satellite constellation is Starlink (2,146 active satellites). Examples of the smallest ones are Sentinel-1 and Sentinel-2, both containing two units.

This category includes the MSM that depends on several satellites that are flying in similar orbits without control of their relative position, but they are organized in time and space to achieve real-time full Earth coverage. Moreover, each satellite is controlled separately from ground control stations.

The most famous missions of satellite constellation are GPS (32 satellites distributed in 6 orbits (LiEmail, 2015), GLONASS (24 satellites distributed in 3 orbits, Galileo (24 operational satellites and 6 active spares satellites all of them are distributed in 3 orbits, and Iridium (66 operational satellites and 6 satellites as spare.

GEO vs. MEO vs. LEO Satellite Constellations

Depending on the orbital altitude, there are three different types of satellite constellations: GEO, MEO, and LEO.

Geostationary swarms derived their name from their Earth-rotation mode: they synchronize with our planet’s movement, thus hovering all the time over the same point. It happens because GEO swarms fly over the equator, and each rotation takes 24 hours. GEO is a typical orbit for weather satellite constellations. Others broadcast TV and provide low-speed communication services.

Thanks to the altitude of 36,000 km, an individual GEO satellite can capture 40% of the Earth’s surface. Thus, a group of three units 120 angular degrees apart is enough to keep an eye on the whole world.

MEO Satellite Constellations

MEO is an acronym for medium Earth (or mid-Earth) swarms operating at the altitude of 5,000 to 20,000 km and traditionally serving for navigation purposes. MEO constellations also provide high-bandwidth connectivity in locations where terrestrial infrastructure is poor or not feasible. This particularly refers to maritime and aerospace industries, offshore platforms, and rescue team operations in remote areas.

LEO Satellite Constellations

LEO swarms make the densest space population, operating at an altitude of 500 to 1,200 km. The derived data is widely used by governmental bodies, as well as commercial and non-commercial organizations. Low Earth orbit satellite constellations primarily support research, telecommunication, and Earth Observation needs of environmental monitoring, disaster response, forestry, and agri-sector.

Such swarms may have circular or elliptical orbits. Circular orbits are at the same altitude, while elliptical orbits contain the apogee (the highest point) and the perigee (the lowest one). Swarms with circular orbits revolve around our planet within 1.5 to several hours and typically fly nearly above the geographic poles. As for elliptical orbits, they are passed slower at the apogee and faster at the perigee points.

Satellite formation flying

This category includes the MSM that depends on multiple satellites with onboard control, which provides coordinated motion control for maintaining relative positions to preserve an appropriate topology. This topology is essential to achieve the mission objectives. Simply, it is several satellites arranged to achieve the function of a single, large, virtual instrument. Examples of formation flying are JC2Sat, FAST Microsatellite formation flying missions. Depending on the mission application, formation flying topology can be classified as Trailing formations or Swarm.

Swarm formations

The swarm formation consists of three or more satellites orbiting adjacent orbits. They form a virtual structure according to their mission. This topology can provide an image of the ground target from different angles at the same time moreover increasing the swath width. Each member determines and controls its positions. The concept of satellite swarms is still a new concept. Only a few missions were successfully demonstrated the swarm concept, such as ESA Swarm for Earth magnetic field monitoring and radio telescope based on Nano-satellites in moon orbit OLFAR mission.

Swarm Intelligence

Swarm intelligence is a branch of artificial intelligence that attempts to get computers and robots to mimic the highly efficient behavior of colony insects such as ants and bees. As a group, simple creatures following simple rules can display a surprising amount of complexity, efficiency, and even creativity. Across countless species, nature show us that social creatures, when working together as unified systems, can outperform the vast majority of individual members when solving problems and making decisions.

Swarm intelligence in the robotics domain has wide-ranging applications and benefits. The primary benefits of swarm intelligence include:

• Flexibility: The swarm system responds to internal disruptions and external challenges.

• Robustness: Tasks are finished regardless if some of the agents fail.

• Self-organizing: Roles are not predefined — they emerge.

• Flexibility: The swarm system responds to internal disruptions and external challenges.

• Robustness: Tasks are finished regardless if some of the agents fail.

• Self-organizing: Roles are not predefined — they emerge.

• Adaptation: The swarm can adapt to predetermined and new stimuli.

• Decentralized: There is no central control, allowing for rapid, local collaboration.

One main challenge in artificial swarming is the design of systems that, while maintaining decentralized control, have agents capable of (i) acquiring local information through sensing, (ii) communicating with at least some subset of agents, and (iii) making decisions based on the dynamically gathered sensed data.

Satellite swarm missions

The use of satellite swarm offers an interesting approach to Earth observation. While there are increasing demands for border monitoring, environment pollution control, and disasters monitoring (such as, earthquake, forest fire, and flood), the traditional systems (single satellite) can’t achieve the frequent images with desirable spatial/temporal resolution needed for the analysis or provide the necessary data for “Supporting the decision making” in almost real-time.

The spacecraft used for swarm applications should be simple, small, light and can carry the required payload (earth sensor). The current cost of putting a satellite into an earth orbit is between 15,000 and 30,000 $/Kg . Consequently, Nano- and Pico-satellite systems (1–10 kg) are perfect to meet these requirements.

Space ultra-low frequency radio observatory mission concept

Space Ultra-Low Frequency Radio Observatory mission proposed by the Chinese Academy of Science aims to launch a swarm of 13 satellites, a mother ship of Micro-Satellite class and 12 deputy satellites of Nano-satellite class, this swarm is orbiting the second Sun-Earth Lagrange point (L2). Each deputy satellite will have three dipole antennas that will enable observing “all the sky all the time” in the 1–100 MHz frequency range

Space autonomous mission for swarming and geo-locating nanosatellites

The Space Autonomous Mission for Swarming and Geo-Locating Nanosatellites mission is an experimental mission of Teknion institute, this mission is supported by the Israeli space program. The swarm consists of three CubeSats satellite. The mission has two main goals; (1) to determine the position of a cooperative terrestrial emitter using the concept of time difference of arrival and/or frequency difference of arrival. (2) to determine the long term autonomous operation of satellite swarm, an additional goal is to perform a space qualification of a Micro pulsed plasma thruster and a new space processor

EOS SAT Satellite Constellation As The First One To Meet Agribusiness Needs

Quite soon, EOSDA will also contribute to satellite constellation launches with its proprietary EOS SAT which is the first swarm so far specifically constructed to serve primarily agricultural purposes but it can be used in forestry and other industries as well. By providing accurate remote sensing data, EOS SAT will complete the full operational cycle of the company, including swarm assembly, imagery acquisition, and analytics delivery.

EOS SAT will include seven optical units operating at the LEO orbit. The units will rotate around the Earth sun-synchronically, meaning they will appear above a certain point at the same time.

The constellation is designed as a system of small satellites, with a unit weight of 170 kg. EOS SAT will be unique with 13 agri-related bands and will capture 8.6 to 12 million square kilometers per day.

Optical EOS SAT sensors will acquire panchromatic (1.4 m) and multispectral (2.8 m) imagery 50% of the revolving time due to a lack of illumination. SAR satellite constellations like Sentinel-1 retrieve imagery irrespective of the sunlight. For radar images from Sentinel-1, visit EOSDA LandViewer. EOS SAT-1 was set into orbit in the fourth quarter of 2022, and the other six units will be deployed in 2023-2024 (three units per year). The full operational capability will be achieved by 2025.

By launching the EOS SAT satellite constellation, EOSDA won’t simply obtain field monitoring data that will be useful for farmers, crop insurers, input supplies, agri-banks, traders, and other stakeholders. The company’s R&D experts provide comprehensive analytics with the possibility to develop custom solutions for different markets. Some of the most valuable insights on the crop state and the factors it is impacted including the soil moisture, vegetation indices, growth stages,
field boundary detection, change detection

A Hive Mind For Weather Data

NASA wants to push the concept of swarm intelligence to new heights, adding it to a network of small weather satellites that could coordinate their actions and even change their flight paths and altitudes as needed to study weather events from multiple angles. The program is being worked on at the Goddard Space Flight Center in Greenbelt, Maryland.

The program wants to use swarms of small satellites, called SmallSats or CubeSats, in order to observe related weather phenomena occurring simultaneously around the planet and determine how they influence one another. In that way, multiple satellites working together as a swarm may be able to piece a weather puzzle together in a way that no single satellite ever could.

“We already know that Saharan dust blowing over to the Amazon rainforests affects cloud formation over the Atlantic Ocean during certain times of the year,” said NASA Engineer Sabrina Thompson, who works at the Goddard Space Flight Center. “How do you capture that cloud formation? How do you tell a swarm of satellites what region and time of day is the best to observe that phenomenon?”

According to Thompson, the answer is that climate scientists should create a set of parameters for high profile weather events and general rules that a swarm of satellites would follow when gathering weather data. Then it would be up to the swarm AI to act however it thinks is best to collect that information, coordinating multiple satellites working together to capture the most useful data as quickly and efficiently as possible.

According to NASA, different swarm designs are being considered, but in all cases the swarm AI would have a lot of control over how it deploys its individual members, and how it coordinates coverage of weather events happening around the globe. In one possible configuration, individual satellites could even use the drag force of the earth to drop to lower altitudes, which might give them a different angle on important events like the formation of rain or storm clouds.

NASA Funds R&D Projects to Improve Operations of Satellite Swarms

NASA is funding a trio of research and development (R&D) projects by Nanoracks, Teltrium Solutions and Emergent Space Technologies aimed at enabling swarms of small satellites to better operate in Earth orbit and to explore other worlds.

The companies each received Small Business Innovation Research (SBIR) Phase II awards worth $750,000 to continue work on the their technologies. They each received smaller awards under the first phase of of the program.

Nanoracks, which is based in Houston, is focused on reusing spent rocket stages known as Outposts to help improve communications with satellite swarms exploring the moon and other planets.

“Distributed small space vehicles, cooperating in a dynamic environment, are critical for the success of planetary exploration within the next decade. However, the effectiveness of these distributed vehicle swarms will be limited by two factors – the size of the individual vehicles (which will determine onboard data relay capabilities) and their distance from the command and communications centers on Earth,” Nanoracks said in its proposal summary.

“The existence of flexible, low-cost Outposts – Nanoracks’ long-duration platforms created from repurposed upper stages – in the cislunar and translunar environments can increase the resiliency and effectiveness of exploratory mission designs by providing a localized area network capacity for communication, pointing, navigation, and timing (PNT), and data relay back to Earth,” the proposal added.

Emergent Space Technologies, which is based in Laurel, Md., is developing a software system called Adjutant that uses artificial intelligence and machine learning to allow satellite swarms to plan activities in a more autonomous manner, thus reducing the need for ground-based commands.

“Adjutant is directly relevant to applications identified in our subtopic, such as missions operating ‘autonomously and cooperatively at cislunar or more remote destinations’ by reducing and eventually eliminating the need for ‘ground-based semiautonomous scheduling’. Reducing the need for ground-based operations enables more efficient operation of near-Earth constellations, and can be extended to enable persistent remote operations in Cislunar or more remote environments,” the proposal summary said.

Teltrium Solutions is working on developing a system that would allow constellations of small satellites that have limited power and data rate transmission capabilities to better communicate with Earth.

“The traditional approach to this arraying concept is to pre-condition each node signal in phase and time prior to transmission such that all signals arrive at the receiver coherently. This phase adjustment is very burdensome and problematic for the space node. We refer to this arraying approach as spaced-based arraying’,” the proposal summary said.

“Our innovation performs this signal ‘arraying’ operation in a way that effectively eliminates all the node synchronization and coordination complexities noted above by implementing ground-based arraying. We denote our innovative arraying technology as “Swarm Array Coherent Combining” (SACC). SACC uses ground terminal signal processing to extract node phasing and timing for coherent combining allowing each node signal to be ‘uncoupled’ from each other and have significantly relaxed time and phase requirements,” the document added.