Earth Orbit Satellite Research Articles

Sensor Data Fusion using Kalman Filter for LAPAN-A2 Satellite Attitude Estimation

LAPAN A2 is a Low Earth Orbit (LEO) satellite with the primary mission to monitor the area. In order to fulfil the mission’s objectives, the Satellite attitude must be controlled properly. One of the control processes under consideration is the output attitude estimation. Attitude estimation processes in satellites mostly use satellite sensor output transformation. The estimation process, however, cannot be carried out with only one sensor where the generated transformation does not represent the satellite actual attitude. Thus, a fusion of two or more attitude sensors is needed. However, measurement noise, such as the effect of the Earth's albedo on the sun sensor and the interference of the Earth's magnetic field on the magnetometer, is incorporated into the estimation process. Thus, a filtering process is needed. Hence, this study aims to investigate the utilization of the sensor output raw data fusion combined with the Kalman Filter algorithm to estimate the LAPAN-A2 satellite attitude in the form of Euler angle.

Airborne Internet: An Ultradense LEO Networks Empowered Satellite-to-Aircraft Access and Resource Management Approach

With the rapid development of low earth orbit (LEO) satellite technologies and constellation projects (like Starlink, OneWeb), the ongoing ultra-dense LEO satellite networks can provide an efficient solution to ubiquitous connection of aircraft. It is urgent to design the ultra-dense LEO network enabled satellite-to-aircraft communication for in-cabin users with high-speed Internet connectivity requirements. In this paper, we investigate the resource scheduling of ultra-dense LEO network enabled satellite-to-aircraft communication and the in-cabin communication inside aircraft in civil aviation. First, we adopt the Lyapunov optimization framework to tackle the high dynamic and fast mobility of satellites and aircraft. For the satellite-to-aircraft access and subchannel assignment, we propose a dynamic access and subchannel allocation algorithm based on matching theory, which can converge to a stable matching within a finite iterations. To guarantee customized needs of in-cabin users, we propose a power control algorithm based on the successive convex approximation technology to optimize the power allocation of satellites on each subchannel and the transmit power of aircraft for each in-cabin user, which is proven to obtain a saddle point or a local minimum with low complexity. Extensive simulations have been carried out to validate the effectiveness of the proposed resource allocation method.

Coverage and Rate Analysis of LEO Satellite-to-Airplane Communication Networks in Terahertz Band

The low Earth orbit (LEO) satellite constellation in the terahertz (THz) band is one of the promising technologies to provide global coverage and high-rate transmission to the airplane, whose key performance evaluation is required before realistic deployment. In this paper, we consider a downlink THz LEO satellite-airplane network with directional antennas, where the satellites follow a binomial point process on a spherical surface. Incorporating the distinctive THz propagation properties and directional beams in the two scenarios with/without molecular absorption noise, we propose an analytical framework to evaluate the coverage probability and average achievable rate of an arbitrary airplane. The analytical results are expressed in terms of the Laplace transforms of the interference-plus-molecular absorption noise and interference. Specifically, considering a frequency reuse strategy, we first provide the probability distributions of the distances from an arbitrary satellite, the serving satellite and any non-serving satellite to the target airplane, and calculate the probabilities of whether an interfering satellite is blocked by the Earth. Numerical results verify the accuracy of the analytical expressions and show that fewer orthogonal channels and lower LEO satellite altitude lead to better coverage and rate performance. As a key parameter in network design, the number of satellites has two competing effects on coverage and rate, and an optimum satellite number exists. Overall, this study provides theoretical guidance for deploying and planning THz satellite constellations.

Satellite–Terrestrial Collaborative Object Detection via Task-Inspired Framework

Recently, buoyed by advances in the space industry, low Earth orbit (LEO) satellites have become an important part of the Internet of Things (IoT). LEO satellites have entered the era of a big data link with IoT, how to deal with the data from the satellite IoT is a problem worthy of consideration. Conventional object detection method in optical remote sensing simply transmits the raw data to the ground. However, it ignores the properties of the images and the connection with the downstream task. To obtain efficient data transmission and accurate object detection, we propose a task-inspired satellite-terrestrial collaborative object detection framework called STCOD. It detects regions of interest (ROIs) and adopts a block-based adaptive sampling method to compress the background (BG) in optical remote sensing images by introducing satellite edge computing (SEC) on satellites. The STCOD framework also sets the transmission priority of image blocks according to their contributions to the task and uses fountain code to ensure the reliable transmission of important image blocks. We build a whole software simulation framework to validate our method, including the satellite module, the transmission module, and the terrestrial module. Extensive experimental results show that the STCOD framework can reduce the amount of downlink data decreased by 50.04% while losing the detection accuracy by 0.54%. In our simulated satellite-terrestrial link, the STCOD framework can reduce the number of satellite-to-terrestrial transmissions by half. When the packet loss rate is between 5% and 20%, the detection accuracy is lost only 0.05% to 0.5%.

Multiagent Reinforcement Learning-Based Orbital Edge Offloading in SAGIN Supporting Internet of Remote Things

We investigate a computing task scheduling problem in space-air-ground integrated network (SAGIN) for Internet of remote Things (IoRT). In the considered scenario, the unmanned aerial vehicles (UAVs) collect computing tasks from IoRT devices and make offloading decisions, in which the tasks can be computed at the UAVs or offloaded to the low earth orbital (LEO) satellite. The optimization objective is to design offloading strategies for each UAV that maximum the number of tasks satisfies delay constraint and reduces the energy consumption of UAVs. We formulate this problem as a nonlinear integer optimization problem, and remodel it as a stochastic game to solve it. To copy with the dynamic and complexity environment, we propose a learning-based orbital edge offloading (LOEF) approach which can coordinate all UAVs to learn the optimal offloading strategies. This method is based on the Actor-Critic framework of multi-agent reinforcement learning, the Actor observes the environment and output the current offloading decision, the Critic evaluates the action of the Actor and coordinate the actions of all UAV to increase the reward of system. The simulation results show that the proposed offloading strategy converges fast, increases the number of satisfying the delay constraints tasks and the energy utilization of UAVs compared with the baseline strategies.

Establishing “norms of behavior” for satellite collision avoidance maneuver planning

Several commercial companies, as well as various nations, have proposed to deploy or are deploying many satellites in Low Earth Orbit (LEO). These large constellations will greatly increase the number of satellites operating in relatively narrow altitude regions of space. The added space traffic in these regions will create many close approaches between the members of the large constellations and other space operators. These close approach situations can necessitate maneuver(s) to avoid a potential collision. Should both satellites have maneuvering capability, the question of how the overall collision avoidance procedures should be executed is raised. Some constellations may employ automated collision avoidance systems which interact differently than conventional human-in-the-loop systems. Interactions between an automated system and another operational satellite, between two automated systems or two nonautonomous systems present new challenges for executing effective collision avoidance. Additionally, the existence of non-maneuverable satellites and space debris continues to pose additional challenges. This paper is the first of several papers that will be documenting an International Academy of Astronautics study on this topic.

Starlink: A Revolution in Global Satellite Internet Communication

Abstract: The evolution of global communication infrastructures is entering a new phase with the introduction and development of Starlink, a satellite constellation project by SpaceX. Due to the [COVID-19], people all over the world need high-speed Internet connections, and India is one of the world's best copied consumer markets. Starlink has advised its customers around the world, including India, to allow all schools and organizations to access high-speed internet over the 'distance' of satellites and in the nature layer. Daily tasks are done online, and they urgently need high-speed Internet connection. There are demands, there are solutions directly from Sky, but Reliance JIO, Vodafone-Idea, Airtel etc. There are other service providers such as. Use FTTH, mobile networks Road and satellite internet, people are already using the internet, but the speed of the internet could be the turning point. Another point to consider is the price of $99 and $499, which may create some problems in the market because the Indian market is price sensitive. Starlink's architecture consists of low Earth orbit (LEO) satellites, which aim to minimize latency and maximize throughput, representing a significant departure from traditional geostationary satellites. In this research article, the author tries to find out what people think about Starlink's other business activities such as announcing products that start providing internet from SKY and competing with manufacturers in the market

Satellite to buoy IoT communications in the Arctic Ocean

Internet of things (IoT), to Arctic Ocean areas using Low Earth Orbit (LEO) satellites for communication to and from sensor units on the sea, has become increasingly important. It is challenging to close the link budget from a buoy on sea to a LEO satellite due to restrictions on the availability of power in such installations. Phenomena as scattering from the sea surface and small-scale fading, ionospheric scintillations, diffraction loss at low elevation angles, and power availability in small LEO satellites and models for analysis are described. It is of great importance to have a radio wave propagation model that accurately predicts path loss between an installation on the sea and a LEO satellite taking all loss mechanisms into account. In this paper, a path-loss model for satellite to buoy communications over the sea is described. In this model, maritime propagation phenomena in the radio link include free space loss, scintillation loss caused by the ionosphere, diffraction loss at low elevation angle, and scattering at the sea surface depending on the wave height and small-scale fading. Furthermore, a buoy on the sea surface with strong angular movement will cause a varying receive signal level depending on the antenna diagram. These phenomena are assessed. A link budget for the frequencies 433, 868, and 3,400 MHz is calculated for a LEO satellite at a height of 800 km.

Study of the image motion compensation method for a vertical orbit dynamic scanning TDICCD space camera

In this study, a collaborative compensation method for low-dimensional attitude maneuvering and time delay integration charge-coupled device (TDICCD) line-frequency matching is proposed. The method is combined with the validation and analysis of the coordinate system transformation model to address the mismatch between the TDI charge transfer speed and the speed of the target. This mismatch is caused by the inconsistency between the rotational scanning direction of the double-sided mirror used for dynamic vertical orbit scanning imaging in low Earth-orbit satellites and the direction of the satellite along its orbit. The image motion per unit exposure time is decreased from 0.619µm to 0.023µm compared with the uncompensated maneuver mode, and the image quality is noticeably higher.

Prediction and ephemeris fitting of LEO navigation satellites orbits computed at the antenna phase center

Nowadays, Low Earth Orbit (LEO) satellites are proposed to augment the Positioning, Navigation and Timing (PNT) service of the GNSS satellites by directly transmitting navigation signals. In such cases, the users eventually need the orbits at the Antenna Phase Center (APC) of the antenna broadcasting navigation signals toward the Earth instead of those at the satellite Center of Mass (CoM). Using real attitudes of Sentinel satellites and simulated attitudes of different source types with enlarged instabilities, the influences of the attitude instability on the prediction and ephemeris fitting of the APC orbits are studied. It was found that different scenarios of attitude stabilities could lead to prediction degradations with a 3D RMS from a few millimeters to more than 4 cm. The study also showed that the ephemeris fitting errors of the APCs are not significantly impacted, considering both the real attitudes of Sentinel-6A and the simulated attitude instabilities.

Divided at the Edge - Measuring Performance and the Digital Divide of Cloud Edge Data Centers

Cloud providers are highly incentivized to reduce latency. One way they do this is by locating data centers as close to users as possible. These “cloud edge” data centers are placed in metropolitan areas and enable edge computing for residents of these cities. Therefore, which cities are selected to host edge data centers determines who has the fastest access to applications requiring edge compute — creating a digital divide between those closest and furthest from the edge. In this study we measure latency to the current and predicted cloud edge of three major cloud providers around the world. Our measurements use the RIPE Atlas platform targeting cloud regions, AWS Local Zones, and network optimization services that minimize the path to the cloud edge. An analysis of the digital divide shows rising inequality as the relative difference between users closest and farthest from cloud compute increases. We also find this inequality unfairly affects lower income census tracts in the US. This result is extended globally using remotely sensed night time lights as a proxy for wealth. Finally, we demonstrate that low earth orbit satellite internet can help to close this digital divide and provide more fair access to the cloud edge.

Enhanced precise orbit determination for GPS and BDS-2/3 with real LEO onboard and ground observations

Due to the current geographical situation in China that it is difficult to achieve globally well distributed ground monitoring stations for Chinese BeiDou Navigation System (BDS), the BDS Medium Earth Orbit (MEO) satellite orbital accuracy can be seriously affected by the insufficient length of continuous observation arc based on regional ground network. What is more, the highly static characteristics of BDS Geosynchronous Orbiting (GEO) satellites resulting in meter-level orbit determination accuracy is far from satisfactory for precise positioning services. In order to overcome these problems, the low Earth orbit (LEO) satellites serving as fast-moving space monitoring stations can be used as a good supplement for the current BDS ground monitoring stations layout. In this study, real measured spaceborne data from two LEO satellites, namely Fengyun-3D (FY-3D) and Tianjin University No. 1 (TJU-01), are collected and studied for the augmentation of BDS precise orbit determination (POD). The multipath errors of spaceborne code observations are comprehensively analyzed. It is found that not only BDS-2 relevant satellite-induced code bias but also near-field multipath errors, especially distinct in GPS, exist in a spaceborne environment. The piece-wise linear model is therefore established and applied to correct the code observations to reduce the multipath errors in the integrated POD processing. The GPS and BDS-2/3 POD solutions are compared with orbital overlapping differences and Satellite Laser Ranging (SLR) residuals validation. It is demonstrated that including the two LEO satellites can improve the orbit determination accuracy of GPS and BDS-2/3 significantly under a regional ground network, especially in the along component. The average overlapping orbital Root Mean Square (RMS) is decreased by 18.4 %, 34.3 %, 24.9 %, 21.4 %, and 7.8 % for the GPS, GEO, Inclined Geosynchronous Orbit (IGSO), BDS-2 MEO, and BDS-3 MEO satellites, respectively, in the along component. The RMS of SLR residuals is decreased from 37.1 cm to 17.8 cm for the GEO satellites, and the overall improvement is about 8 %-12 % for the BDS MEO satellites. There has also been a slight improvement under a global network, with an average improvement of 2–3 cm in the SLR residuals RMS. However, significant systematic errors are also observed in the SLR residuals in BDS GEO, IGSO, and MEO satellites, and are expected to be improved with refined observation models based on more LEO satellites, i.e., the phase center variation (PCV).

Spacecraft and optics design considerations for a spaceborne lidar mission with spatially continuous global coverage

The regular acquisition and delivery of high-resolution, accurate elevation data has historically been provided by airborne lidar (light detection and ranging) solutions, which are costly and highly localised. Providing similar data sets globally has notable scientific and commercial applications, but comes with challenges around scale. In this work, an investigation into such a service, from low Earth orbit satellites, is presented. The suitability of different space mission architectures is analysed based on platform size and optics mirror design, with the aim of providing true global, high-resolution (5-30 m sample resolution) lidar data, annually. The technical challenges, cost implications and feasible solution sets are presented, suggesting that a small number of large platforms offers a cost-effective solution, with the optimal design (of those evaluated) being that of a micro-satellite (∼150 kg class) constellation with deployed optics capability. Solutions offering relatively low spatial resolution (30 m) are lower cost, with the cost rising as a square law with increasing resolution. As platform size continues to decrease, the number of satellites required to maintain global coverage scales exponentially, demanding prohibitively large constellations to ensure global coverage with smaller satellites.

Deep Learning-Based Small Target Detection for Satellite–Ground Free Space Optical Communications

Free space optical (FSO) channels between a low earth orbit (LEO) satellite and a ground station (GS) use a highly directional optical beam that necessitates a continuous line-of-sight (LOS) connection. In this paper, we propose a deep neural network (DNN)-based small target detection method that detects the position of a LEO satellite in an infrared image, which can be used to determine the receiver alignment for establishing the LOS link. For the infrared small target detection task without excessive down-sampling, we design a target detection model using a modified ResNest-based feature extraction network (FEN), a custom feature pyramid network (FPN), and a target determination network (TDN). ResNest utilizes the feature map attention mechanism and multi-path propagation necessary for robust feature extraction of small infrared targets. The custom FPN combines multi-scale feature maps generated from the modified ResNest to obtain robust semantics across all scales. Finally, the semantically strong multi-scale feature maps are fed into the TDN to detect small infrared targets and determine their location in infrared images. Experimental results using two widely used point spread functions (PSFs) demonstrate that the proposed algorithm outperforms the conventional schemes and detects small targets with a true detection rate of 99.4% and 94.0%.

Evaluation of atomic oxygen fluences by analyzing transmitted light images of polyimide obtained at SLATS/MDM

Expectations for high-resolution observations by very low Earth orbit (VLEO, below 300 km) satellites are growing. However, the density of atomic oxygen (AO) is much higher in VLEO than in LEO (300 km or higher), so severe degradation of materials is a concern due to high-flux AO collisions. To clarify the degradation, we developed and deployed the material degradation monitor (MDM) mission onboard the super-low altitude test satellite (SLATS). In the MDM, several materials were exposed to the environment at 160–560 km from 23 December 2017 to 1 October 2019 and observed optically by a CCD camera. In general, AO fluence is evaluated by measuring the volume or mass loss of a polyimide, but this was difficult to do because the samples could not be returned to the ground in this mission. This study evaluated AO fluences using the CCD images of a polyimide, Vespel. The sample had nine non-penetrating holes with different bottom-plate thicknesses and was monitored by the CCD while being illuminated by LED light from the back. The CCD images reveal the intensity of the light transmitted through the holes in the bottom plate. The erosion depths of the polyimide, corresponding to the AO fluences, can be evaluated from the pixel values at the hole positions on the images. Here, the correlation between the pixel values and thickness was investigated for pristine and AO-exposed Vespel samples using the MDM engineering models. The total green pixel values followed the Beer-Lambert law for the bottom-plate thicknesses, regardless of AO exposure. Applying the correlation to the MDM flight images, we found that the AO fluence increased significantly after the end of March 2019, finally reaching (6.5–9.8) × 1021 atoms/cm2. This optical imaging method would be useful for evaluating the AO effects on the other MDM samples and high AO fluences in future VLEO missions.

Minimize average tasks processing time in satellite mobile edge computing systems via a deep reinforcement learning method

Recently, the development of Low Earth Orbit (LEO) satellites and the advancement of the Mobile Edge Computing (MEC) paradigm have driven the emergence of the Satellite Mobile Edge Computing (Sat-MEC). Sat-MEC has been developed to support communication and task computation for Internet of Things (IoT) Mobile Devices (IMDs) in the absence of terrestrial networks. However, due to the heterogeneity of tasks and Sat-MEC servers, it is still a great challenge to efficiently schedule tasks in Sat-MEC servers. Here, we propose a scheduling algorithm based on the Deep Reinforcement Learning (DRL) method in the Sat-MEC architecture to minimize the average task processing time. We consider multiple factors, including the cooperation between LEO satellites, the concurrency and heterogeneity of tasks, the dynamics of LEO satellites, the heterogeneity of the computational capacity of Sat-MEC servers, and the heterogeneity of the initial queue for task computation. Further, we use the self-attention mechanism to act as a Q-network to extract high-dimensional dynamic information of tasks and Sat-MEC servers. In this work, we model the Sat-MEC environment simulation at the application level and propose a DRL-based task scheduling algorithm. The simulation results confirm the effectiveness of our proposed scheduling algorithm, which reduces the average task processing time by 22.1%, 30.6%, and 41.3%, compared to the genetic algorithm(GA), the greedy algorithm, and the random algorithm, respectively.

Thermal control of a small satellite in low earth orbit using phase change materials-based thermal energy storage panel

Thermal control of small satellites in low earth orbit (LEO) is not easy due to the intermittent heating conditions. The satellites in LEO are sometimes present in the illumination zone and other times in the eclipse zone, which imposes difficulties keeping their temperatures within the safe range. The present study investigates a thermal energy storage panel (TESP) integrated with phase change materials (PCM) to control the temperatures of satellite subsystems. The TESP was made of aluminium with outer dimensions of 100 mm long, 71 mm wide, and 25 mm high. The PCMs used were organic-based materials, which were RT 12, RT 22, and RT 31. The TESP was tested under two thermal powers of 11 W and 14 W. These powers are typical of satellite subsystems. The finite volume method was adopted for thermal analysis of the TESP. The significance of this study is that it provides a detailed computational analysis of the TESP for microsatellites' temperature management under typical LEO conditions. The research outcomes show a significant advancement in the thermal managing performance of PCM-based TESP. RT 22 could reduce the highest temperature by 4.7 % and raise the lowest by 9.5 %. It was observed from the analysis that the PCM with intermediary melting temperature provided better thermal control efficiency. RT 12 reported a lower extreme temperature difference (ETD) and could decrease it by 63.9 % relative to the case with no PCM. At the same time, RT 22 reported an ETD of 23 min and could reduce it by 63 % relative to the case with no PCM at 14 W. The present study concluded that PCMs show great potential as a viable approach for effectively thermally managing devices that experience cyclic thermal fluctuations, such as the subsystems of satellites operating in LEO.

Long‐Term In Situ Performance Comparison of Si and GaAs Solar Arrays in Medium Earth Orbit

The present work analyzes the long‐term in situ comparison of Si and GaAs solar array based on two BeiDou Navigation Satellite System satellites in medium Earth orbit (MEO). From the 6 year long‐term perspective, both Si and GaAs solar arrays exhibit significant yearly periodic variations in remote sensing current and temperature due to periodic variations in the Sun–satellite distance. The practical in situ photogenerated current degradation of Si and GaAs solar arrays in MEO orbits is analyzed by the light intensity and working temperature after calibrating. The annual degradation coefficients of Si and GaAs solar arrays are calculated to be 0.986 and 0.990, respectively, which means 13.2% and 9.6% current degradation for Si and GaAs solar arrays at the end of the 10 year life MEO satellite. Also, this article examines the temperature of the MEO orbit, with the working temperature ranging from −144.7 to 56.3 °C for Si solar array and −136.9 to 60.9 °C for GaAs solar array. The present work provides a critical accurate degradation parameter for the MEO satellite's precise design and the space application of the low‐cost silicon solar cell.

Estimation and evaluation of hourly Meteorological Operational (MetOp) satellites' GPS receiver differential code biases (DCBs) with two different methods

Abstract. Differential code bias (DCB) is one of the Global Positioning System (GPS) errors, which typically affects the calculation of total electron content (TEC) and ionospheric modeling. In the past, DCB was normally estimated as a constant in 1 d, while DCB of a low Earth orbit (LEO) satellite GPS receiver may have large variations within 1 d due to complex space environments and highly dynamic orbit conditions. In this study, daily and hourly DCBs of Meteorological Operational (MetOp) satellites' GPS receivers are calculated and evaluated using the spherical harmonic function (SHF) and the local spherical symmetry (LSS) assumption. The results demonstrated that both approaches could obtain accurate and consistent DCB values. The estimated daily DCB standard deviation (SD) is within 0.1 ns in accordance with the LSS assumption, and it is numerically less than the standard deviation of the reference value provided by the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) Data Analysis and Archive Center (CDAAC). The average error's absolute value is within 0.2 ns with respect to the provided DCB reference value. As for the SHF method, the DCB's standard deviation is within 0.1 ns, which is also less than the standard deviation of the CDAAC reference value. The average error of the absolute value is within 0.2 ns. The estimated hourly DCB with LSS assumptions suggested that calculated results of MetOpA, MetOpB, and MetOpC are, respectively, 0.5 to 3.1 ns, −1.1 to 1.5 ns, and −1.3 to 0.7 ns. The root mean square error (RMSE) is less than 1.2 ns, and the SD is under 0.6 ns. According to the SHF method, the results of MetOpA, MetOpB, and MetOpC are 1 to 2.7 ns, −1 to 1 ns, and −1.3 to 0.6 ns, respectively. The RMSE is under 1.3 ns and the SD is less than 0.5 ns. The SD for solar active days is less than 0.43, 0.49, and 0.44 ns, respectively, with the LSS assumption, and the appropriate fluctuation ranges are 2.0, 2.2, and 2.2 ns. The variation ranges for the SHF method are 1.5, 1.2, and 1.2 ns, respectively, while the SD is under 0.28, 0.35, and 0.29 ns.

Analysis of Collision Avoidance Manoeuvres Using Aerodynamic Drag for the Flying Laptop Satellite

Collision avoidance is a topic of growing importance for any satellite orbiting Earth. Especially those satellites without thrusting capabilities face the problem of not being able to perform impulsive collision avoidance manoeuvres. For satellites in low Earth orbits, though, perturbing accelerations due to aerodynamic drag may be used to influence their trajectories, thus offering a possibility to avoid collisions without consuming propellant. Here, this manoeuvring option is investigated for the satellite Flying Laptop of the University of Stuttgart, which orbits the Earth at approximately 600km\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${600}\\,{\ extrm{km}}$$\\end{document}. In a first step, the satellite is aerodynamically analysed making use of the tool ADBSat. By employing an analytic equation from the literature, in-track separation distances can then be derived following a variation of the ballistic coefficient through a change in attitude. A further examination of the achievable separation distances proves the feasibility of aerodynamic collision avoidance manoeuvres for the Flying Laptop for moderate and high solar and geomagnetic activity. The predicted separation distances are further compared to flight data, where the principle effect of the manoeuvre on the satellite trajectory becomes visible. The results suggest an applicability of collision avoidance manoeuvres for all satellites in comparable and especially in lower orbits than the Flying Laptop, which are able to vary their ballistic coefficient.