scholarly journals Forecasting Methods of Battery Charge and Discharge Current Profile for LEO Satellites

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2999
Author(s):  
Seok-Teak Yun ◽  
Seung-Hyun Kong
Keyword(s):  
Discharge Current ◽  
Short Term Memory ◽  
Low Earth Orbit ◽  
Mission Design ◽  
Access Time ◽  
Current Profile ◽  
Satellite Systems ◽  
Battery Charge ◽  
Leo Satellites ◽  
Leo Satellite

The orbital characteristics of low Earth orbit (LEO) satellite systems prevent continuous monitoring because ground access time is limited. For this reason, the development of simulators for predicting satellite states for the entire orbit is required. Power-related prediction is one of the important LEO satellite simulations because it is directly related to the lifespan and mission of the satellite. Accurate predictions of the charge and discharge current of a power system’s battery are essential for fault management design, mission design, and expansion of LEO satellites. However, it is difficult to accurately predict the battery power demand and charging of LEO satellites because they have nonlinear characteristics that depend on the satellite’s attitude, season, orbit, mission, and operating period. Therefore, this paper proposes a novel battery charge and discharge current prediction technique using the bidirectional long short-term memory (Bi-LSTM) model for the development of a LEO satellite power simulator. The prediction performance is demonstrated by applying the proposed technique to the KOM-SAT-3A and KOMSAT-5 satellites operating in real orbits. As a result, the prediction accuracy of the proposed Bi-LSTM shows root mean square error (RMSE) within 2.3 A, and the prediction error well outperforms the most recent the probability-based SARIMA model.

SUPPORTING DISTRESS SIGNALS OVER LOW EARTH ORBIT MOBILE SATELLITE SYSTEMS FOR EMERGENCY INFORMATION ACQUISITION

2013 ◽  
Vol 09 (03n04) ◽  
pp. 1350018
Author(s):  
GAMAL A. HUSSEIN ◽  
MOSTAFA A. NOFAL ◽  
MOAWAD I. DESSOUKY ◽  
OSAMA ALY ORABY ◽  
WALEED AL-HANAFY ◽  
...  
Keyword(s):  
Information Acquisition ◽  
Low Earth Orbit ◽  
Earth Orbit ◽  
Rescue Operation ◽  
Satellite Systems ◽  
Leo Satellites ◽  
Mobile Satellite ◽  
Voice Data ◽  
Leo Satellite ◽  
Service Priority

Low earth orbit (LEO) satellite systems allow a broad range of services to be provided using small, lightweight, cellular-like portable telephones. Exploiting LEO satellites to support distress signals for aircrafts, ships and international travelers is explored in the current paper. A multi-service priority-oriented algorithm is proposed for handling voice, data and emergency signals over LEO satellites. The emergency signal is privileged with service priority so that rescue operation can be carried out as soon as possible. The priority mechanism includes channel reservation as well as joining a queue if no free channel is available as long as the request is roaming in the handover area. In addition, a simplified but efficient approach is suggested for locating the object of an imminent danger situation. As LEO satellites are non-geostationary, the visible period of each spot-beam is small. Consequently, a teletraffic model, that accommodates the mobility of spot-beams as well as the resulting handover rate, is developed in order to gauge the performance of the proposed algorithm. Numerical results for access denying and service-dropping rates are presented for nominal system parameters.

scholarly journals GNSS RTK Positioning Augmented with Large LEO Constellation

2019 ◽  
Vol 11 (3) ◽  
pp. 228 ◽  
Author(s):  
Xingxing Li ◽  
Hongbo Lv ◽  
Fujian Ma ◽  
Xin Li ◽  
Jinghui Liu ◽  
...  
Keyword(s):  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
Convergence Time ◽  
Current Status ◽  
Initial Assessment ◽  
Satellite Systems ◽  
Long Baseline ◽  
Leo Satellites ◽  
Global Navigation Satellite ◽  
Long Baselines

It is widely known that in real-time kinematic (RTK) solution, the convergence and ambiguity-fixed speeds are critical requirements to achieve centimeter-level positioning, especially in medium-to-long baselines. Recently, the current status of the global navigation satellite systems (GNSS) can be improved by employing low earth orbit (LEO) satellites. In this study, an initial assessment is applied for LEO constellations augmented GNSS RTK positioning, where four designed LEO constellations with different satellite numbers, as well as the nominal GPS constellation, are simulated and adopted for analysis. In terms of aforementioned constellations solutions, the statistical results of a 68.7-km baseline show that when introducing 60, 96, 192, and 288 polar-orbiting LEO constellations, the RTK convergence time can be shortened from 4.94 to 2.73, 1.47, 0.92, and 0.73 min, respectively. In addition, the average time to first fix (TTFF) can be decreased from 7.28 to 3.33, 2.38, 1.22, and 0.87 min, respectively. Meanwhile, further improvements could be satisfied in several elements such as corresponding fixing ratio, number of visible satellites, position dilution of precision (PDOP) and baseline solution precision. Furthermore, the performance of the combined GPS/LEO RTK is evaluated over various-length baselines, based on convergence time and TTFF. The research findings show that the medium-to-long baseline schemes confirm that LEO satellites do helpfully obtain faster convergence and fixing, especially in the case of long baselines, using large LEO constellations, subsequently, the average TTFF for long baselines has a substantial shortened about 90%, in other words from 12 to 2 min approximately by combining with the larger LEO constellation of 192 or 288 satellites. It is interesting to denote that similar improvements can be observed from the convergence time.

Simplest Flow Queuing Models for LEO Satellite System

2022 ◽  
pp. 61-70
Author(s):  
S.B. Pichugin
Keyword(s):  
Communication System ◽  
Communication Systems ◽  
Satellite System ◽  
Low Earth Orbit ◽  
Analytical Models ◽  
Mathematical Apparatus ◽  
Satellite Systems ◽  
Ground Station ◽  
Queuing Models ◽  
Leo Satellite

The relevance of the work is associated with the active deployment of low-orbit communication systems and the expansion of research in the field of corresponding satellite systems. A promising low-orbit communication system based on relay satellites with the function (RSRFs) of routing message packets is considered. The low earth orbit communications systems use the BGP protocol and the AAA functionality at the ground station. For assessing the characteristics of RSRF inter-satellite paths, a scenario was created for the message packets arrival from a group of inter-satellite paths to one subscriber path. The corresponding analytical models have been developed using the mathematical apparatus of queuing systems with the simplest flows of requests and exponential distribution of the service time. The RSRF characteristics of a promising low-orbit communication system are predicted. It is proposed to make the mathematical apparatus of analytical models more complicated to take into account the dynamics of displacements and failures of the RSRF in a low-orbit communication system.

scholarly journals Improved PPP Ambiguity Resolution with the Assistance of Multiple LEO Constellations and Signals

2019 ◽  
Vol 11 (4) ◽  
pp. 408 ◽  
Author(s):  
Xin Li ◽  
Xingxing Li ◽  
Fujian Ma ◽  
Yongqiang Yuan ◽  
Keke Zhang ◽  
...  
Keyword(s):  
Ambiguity Resolution ◽  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
Observation Data ◽  
Dual Frequency ◽  
Satellite Systems ◽  
Triple Frequency ◽  
Leo Satellites ◽  
Fixed Solution ◽  
Global Navigation Satellite

The fusion of low earth orbit (LEO) constellation and Global Navigation Satellite Systems (GNSS) can increase the number of visible satellites and optimize spatial geometry, which is expected to improve the performance of precise point positioning (PPP) ambiguity resolution (AR). In addition, the multi-frequency signals of LEO satellites can bring a variety of observation combinations, which is potential to further improve the efficiency of PPP AR. In this contribution, multi-frequency PPP AR was achieved with the augmentation of different LEO constellations. Three types of LEO constellations were designed with 60, 192, and 288 satellites. Moreover, the corresponding observation data were simulated with the GNSS observations over the ground stations. The LEO constellations were designed to transmit navigation signals on three frequencies: L1, L2, and L5 at 1575.42, 1227.6, and 1176.45 MHz, respectively, which are consistent with the GPS signals. For PPP AR, the uncalibrated phase delay (UPD) products of GNSS and LEO were estimated first. Furthermore, the quality of UPD products was also analyzed. The research findings show that the performance of estimated LEO UPD is comparable to that of GNSS UPD. Based on the UPD products, LEO-augmented multi-GNSS PPP AR can be achieved. Numerous results show that the performance of single-system and multi-GNSS PPP AR can be significantly improved by introducing the LEO constellations. The augmentation performance is more remarkable in the case of increasing LEO satellites. The time to first fix (TTFF) of the GREC fixed solution can be shortened from 7.1 to 4.8, 1.1, and 0.7 min, by introducing observations of 60-, 192-, and 288-LEO constellations, respectively. The positioning accuracy of multi-GNSS fixed solutions is also improved by about 60%, 80%, and 90% with the augmentation of 60-, 192-, and 288-LEO constellations, respectively. Compared to the dual-frequency solutions, the triple-frequency LEO-augmented PPP fixed solution presents a better performance. The TTFF of GREC fixed solutions is shortened to 33 s with the augmentation of 288-LEO constellation under the triple-frequency environment. It is worth indicating that the 288-satellite LEO-only PPP AR was conducted in dual-frequency and triple-frequency modes, respectively. The averaged TTFFs of both modes are 71.8 s and 55.2 s, respectively. It indicates that LEO constellation with 288 satellites is capable of achieving high-precision positioning independently and shows an even better performance than GNSS-only solutions.

Position and velocity estimation with a low Earth orbit regional navigation satellite constellation

2021 ◽  
pp. 095441002110313
Author(s):  
Tomer Shtark ◽  
Pini Gurfil
Keyword(s):  
Low Earth Orbit ◽  
Velocity Estimation ◽  
Global Navigation Satellite Systems ◽  
Dynamical Model ◽  
Earth Orbit ◽  
Navigation Satellite ◽  
Satellite Systems ◽  
Satellite Constellation ◽  
Leo Satellites ◽  
Order Of Magnitude

Position and velocity estimation using Global Navigation Satellite Systems (GNSS) has been widely studied and implemented. In contrast to existing GNSS, the idea of using low Earth orbit (LEO) satellites for position and velocity determination is relatively new. On one hand, the launch to LEO is more affordable compared to GNSS orbits. On the other hand, LEO satellites provide reduced coverage and suffer from orbit determination uncertainties. In this article, we study position and velocity estimation for an aerial platform using signals from a LEO satellite constellation, designed to produce a relatively long coverage duration, while minimizing the geometric dilution of precision. We determine the receiver’s position by using the trilateration method and the velocity by using Doppler estimation, and improve the accuracy thereof by utilizing an Extended Kalman Filter (EKF). We suggest a solution for the trilateration initialization problem, which arises for LEO navigation satellites, which relies on averaging the Earth projection of all the satellites within sight. We examine two scenarios, one wherein the EKF’s dynamical model matches the reference dynamical model, and another with a model mismatch. When the dynamical model is approximated, the EKF reduces the position and velocity errors considerably. When the dynamical model is known, the position and velocity errors can be reduced by an order of magnitude.

Millimeter-accuracy SLR bias determination using independent multi-LEO DORIS and GNSS-based orbits

2021 ◽  
Author(s):  
Daniel Arnold ◽  
Alexandre Couhert ◽  
Eléonore Saquet ◽  
Heike Peter ◽  
Flavien Mercier ◽  
...  
Keyword(s):  
Center Of Mass ◽  
Global Scale ◽  
Terrestrial Reference Frame ◽  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
Laser Ranging ◽  
Bias Estimation ◽  
Satellite Systems ◽  
Leo Satellites ◽  
Orbit Errors

<p>Satellite Laser Ranging (SLR), i.e., the optical distance measurement to satellites equipped with laser retro-reflectors, has become an invaluable core technique in numerous geodetic applications. For instance, SLR measurements to spherical geodetic satellites, such as LAGEOS-1/2 or Etalon-1/2, form an essential contribution for the determination of geocenter coordinates and global scale in the International Terrestrial Reference Frame (ITRF) realizations.</p><p>SLR measurements to active satellites in Low Earth Orbit (LEO) are, on the other hand, up to now mostly used for an independent validation of orbit solutions, usually derived by microwave tracking techniques based on Global Navigation Satellite Systems (GNSS) or <span>Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS). This allows for the analysis of systematic orbit errors (e.g., originating from poorly known satellite center of mass locations or sensor offsets) not only in radial direction, but in t</span><span>h</span><span>ree dimensions. A high level of radial orbit reliability is, e.g., key to satellite altimetry applications.</span></p><p><span>For many of these geodetic SLR applications a mm accuracy and 0.1 mm/year stability is required or at least desired. Unavoidable SLR station biases are a major error source and obstacle to reach the aforementioned accuracy and stability goals. Among the stations of the International Laser Ranging Service (ILRS) there is a large diversity of biases and measurement qualities, and the calibration of these biases for all stations is key to further exploit SLR data for present and future geodetic applications.</span></p><p><span>In this presentation we demonstrate that the analysis of SLR data to active LEO satellites equipped with GNSS or DORIS receivers is a promising means to analyze SLR biases and their stability. </span><span>Using three independent selections of Earth observation missions in LEOs with three different SLR analysis software packages (Bernese GNSS Software, Zoom, Napeos), we estimate SLR range biases for all involved tracking stations on a yearly basis. We find that for many of the stations the three independently estimated sets of biases agree on a few-mm level</span><span> and that the inclusion of satellites from multiple missions allows to render the bias estimation more robust and in particular less prone to geographically correlated orbit errors. This shows that microwave-derived orbits of active LEO satellites, nowadays of very high quality due to numerous advances in modeling and an</span><span>alysis</span><span> techniques, can serve as interesting source</span><span>s</span><span> for SLR station calibration in </span><span>demanding</span><span> geodetic applications like, e.g., future ITRF realizations.</span></p>

scholarly journals Caching-Aware Intelligent Handover Strategy for LEO Satellite Networks

2021 ◽  
Vol 13 (11) ◽  
pp. 2230
Author(s):  
Tao Leng ◽  
Yuanyuan Xu ◽  
Gaofeng Cui ◽  
Weidong Wang
Keyword(s):  
Failure Rate ◽  
High Mobility ◽  
Low Earth Orbit ◽  
Satellite Networks ◽  
Call Blocking ◽  
Communication Services ◽  
Satellite Systems ◽  
Leo Satellite Networks ◽  
Scenarios Simulation ◽  
Leo Satellite

Recently, many Low Earth Orbit (LEO) satellite networks are being implemented to provide seamless communication services for global users. Since the high mobility of LEO satellites, handover strategy has become one of the most important topics for LEO satellite systems. However, the limited on-board caching resource of satellites make it difficult to guarantee the handover performance. In this paper, we propose a multiple attributes decision handover strategy jointly considering three factors, which are caching capacity, remaining service time and the remaining idle channels of the satellites. Furthermore, a caching-aware intelligent handover strategy is given based on the deep reinforcement learning (DRL) to maximize the long-term benefits of the system. Compared with the traditional strategies, the proposed strategy reduces the handover failure rate by up to nearly 81% when the system caching occupancy reaches 90%, and it has a lower call blocking rate in high user arrival scenarios. Simulation results show that this strategy can effectively mitigate handover failure rate due to caching resource occupation, as well as flexibly allocate channel resources to reduce call blocking.

scholarly journals The Sentinel-3 SLSTR Atmospheric Motion Vectors Product at EUMETSAT

2021 ◽  
Vol 13 (9) ◽  
pp. 1702
Author(s):  
Kévin Barbieux ◽  
Olivier Hautecoeur ◽  
Maurizio De Bartolomei ◽  
Manuel Carranza ◽  
Régis Borde
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Forecast Model ◽  
Low Earth Orbit ◽  
Reference Image ◽  
Motion Vectors ◽  
Infrared Imager ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Leo Satellite

Atmospheric Motion Vectors (AMVs) are an important input to many Numerical Weather Prediction (NWP) models. EUMETSAT derives AMVs from several of its orbiting satellites, including the geostationary satellites (Meteosat), and its Low-Earth Orbit (LEO) satellites. The algorithm extracting the AMVs uses pairs or triplets of images, and tracks the motion of clouds or water vapour features from one image to another. Currently, EUMETSAT LEO satellite AMVs are retrieved from georeferenced images from the Advanced Very-High-Resolution Radiometer (AVHRR) on board the Metop satellites. EUMETSAT is currently preparing the operational release of an AMV product from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellites. The main innovation in the processing, compared with AVHRR AMVs, lies in the co-registration of pairs of images: the images are first projected on an equal-area grid, before applying the AMV extraction algorithm. This approach has multiple advantages. First, individual pixels represent areas of equal sizes, which is crucial to ensure that the tracking is consistent throughout the processed image, and from one image to another. Second, this allows features that would otherwise leave the frame of the reference image to be tracked, thereby allowing more AMVs to be derived. Third, the same framework could be used for every LEO satellite, allowing an overall consistency of EUMETSAT AMV products. In this work, we present the results of this method for SLSTR by comparing the AMVs to the forecast model. We validate our results against AMVs currently derived from AVHRR and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The release of the operational SLSTR AMV product is expected in 2022.

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