Low Earth Orbit Satellite Research Articles

Self‐similar traffic prediction for LEO satellite networks based on LSTM

AbstractTraffic prediction serves as a critical foundation for traffic balancing and resource management in Low Earth Orbit (LEO) satellite networks, ultimately enhancing the efficiency of data transmission. The self‐similarity of traffic sequences stands as a key indicator for accurate traffic prediction. In this article, the self‐similarity of satellite traffic data was first analyzed, followed by the construction of a satellite traffic prediction model based on an improved Long Short‐Term Memory (LSTM). An early stopping mechanism was incorporated to prevent overfitting during the model training process. Subsequently, the Diebold‐Mariano (DM) test method was applied to assess the significance of the prediction effect between the proposed model and the comparison model. The experimental results demonstrated that the improved LSTM satellite traffic prediction model achieved the best prediction performance, with Root Mean Squared Error values of 18.351 and 8.828 on the two traffic datasets, respectively. Furthermore, a significant difference was observed in the DM test compared to the other models, providing a solid basis for subsequent satellite traffic planning.

Online Service Function Chain Planning for Satellite–Ground Integrated Networks to Minimize End-to-End (E2E) Delay

The combination of software-defined networking (SDN) and satellite–ground integrated networks (SGINs) is gaining attention as a key infrastructure for meeting the granular quality-of-service (QoS) demands of next-generation mobile communications. However, due to the unpredictable nature of end-user requests and the limited resource capacity of low Earth orbit (LEO) satellites, improper Virtual Network Function (VNF) deployment can lead to significant increases in end-to-end (E2E) delay. To address this challenge, we propose an online algorithm that jointly deploys VNFs and forms routing paths in an event-driven manner in response to end-user requests. The proposed algorithm selectively deploys only the essential VNFs required for each Service Function Chain (SFC), focusing on minimizing E2E delay—a critical QoS parameter. By defining a minimum-hop region (MHR) based on the geographic coordinates of the routing endpoints, we reduce the search space for candidate base stations, thereby designing paths that minimize propagation delays. VNFs are then deployed along these paths to further reduce E2E delay. Simulations demonstrate that the proposed algorithm closely approximates the global optimum, achieving up to 97% similarity in both E2E delay and CPU power consumption, with an average similarity of approximately 90%.

Evaluation of Himawari-8/AHI land surface reflectance at mid-latitudes using LEO sensors with off-nadir observation

Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (r) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher r values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.

Statistical Analysis of LEO and GEO Satellite Anomalies and Space Radiation

Exposure to space radiation substantially degrades satellite systems, provoking severe partial or, in some extreme cases, total failures. Electrostatic discharges (ESD), single event latch-up (SEL), and single event upsets (SEU) are among the most frequent causes of those reported satellite anomalies. The impact of space radiation dose on satellite equipment has been studied in-depth. This study conducts a statistical analysis to explore the relationships between low-Earth orbit (LEO) and geostationary orbit (GEO) satellite anomalies and particle concentrations, solar and geomagnetic activity in the period 2010–2022. Through a monthly and daily timescale analysis, the present work explores the temporal response of space disturbances on satellite systems and the periods when satellites are vulnerable to those disturbances.

Measuring the radiation hardness of terahertz devices for space applications

The application of terahertz technology in space is frontier for the development of 6G technologies. Terahertz transceiver devices based on gallium arsenide Schottky barrier diodes (GaAs SBDs) have the characteristics of small size, light weight and low power consumption, making them suitable for application on spacecraft. However, there is currently a lack of experimental assessments on their space adaptability. Here, we study the radiation hardness of terahertz devices to determine their adaptability in complex space environments. We exposed GaAs SBDs and terahertz multipliers as typical terahertz devices to gamma rays and protons. The experimental results showed that the terahertz devices exhibited good tolerance to protons, but prolonged exposure to gamma rays could significantly increase the leakage current of the GaAs SBDs and alter its C-V characteristics, leading to the failure of the terahertz multiplier. Nevertheless, the terahertz devices maintained a good level of radiation hardness, making them highly suitable for use in Low Earth Orbit (LEO) satellites. The comparison between the results of proton and gamma ray tests indicated that the terahertz devices exhibited high inherent radiation hardness against displacement damage but were more sensitive to ionization damage, requiring higher shielding requirements.

Single laser based novel wavelength shift keying scheme for ground to satellite bidirectional links

Abstract Laser communication in space is gaining more recognition due to its ability to provide a much broader and unregulated data transmission capacity compared to traditional radio frequency systems, while also significantly decreasing the size, power requirements, and weight of the communication system. In this work, a novel technique for the generation of a wavelength shift keying (WSK) signal for the bidirectional transmission of 10 Gbps data between the ground station and low Earth orbit (LEO) satellite is presented. Our proposed scheme requires a single laser source to transmit WSK signal, that generally requires two wavelength sources to transmit the binary data bits. Furthermore, the scheme allows us to remodulate the optical signal received at the LEO satellite for downlink signal transmission. Therefore, the requirement of a laser source at the LEO satellite is eliminated, achieving the much desirable goals of low power consumption, weight and cost. The free space optical (FSO) channel is modelled using the gamma-gamma channel model. The performance of the proposed link is also compared with a conventional On-Off keying (OOK) based modulation scheme by using bit-error-rate (BER) as the performance metric.

Quantifying the Environmental Impacts of Manufacturing Low Earth Orbit (LEO) Satellite Constellations

Quantifying the Environmental Impacts of Manufacturing Low Earth Orbit (LEO) Satellite Constellations

Utility optimization for computation offloading and splitting in time-varying HAP and LEO satellite integrated MEC networks

To provide ubiquitous and low-latency communication and computation services for remote and disaster areas, high altitude platform (HAP) and low earth orbit (LEO) satellite integrated multi-access edge computing (HLS-MEC) networks have emerged as a promising solution. However, most current studies directly assume that the number of connected satellites is fixed and neglect the modeling of the time-varying multi-satellite computing process. Motivated by this, we establish an M/G/K(t) queuing model to illustrate task computation on satellites. To evaluate the efficiency and quality of computation offloading and splitting, we develop a utility model. This model is defined as a difference between a value function that assesses the trade-offs of task offloading, considering latency reductions and energy savings, and a cost function that quantifies expenses related to latency and energy consumption. After formulating the utility maximization problem, we propose the deep reinforcement learning-based offloading and splitting (DBOS) scheme that can overcome the time-varying uncertainties and high dynamics in the HLS-MEC network. Specifically, the DBOS scheme can learn the best computation offloading and splitting policy to maximize the utility by sensing the number of connected satellites, the distance between the HAP and satellites, the available computing resources, and the task arrival rate. Finally, we evaluate and validate the computational complexity and convergence property of the DBOS scheme. Numerical results show that the DBOS scheme outperforms the other three benchmarks and maximizes the utility under time-varying dynamics.

Optimal design of the long-term LEO almanac by considering the atmosphere drag effects

ABSTRACT Almanac is an elegant design to help Global Navigation Satellite Systems (GNSS) signal acquisition, which has been adopted by all global satellite navigation systems. For the future low Earth orbit (LEO) navigation constellation, the almanac will be more critical due to larger constellation and signal Doppler variation, while the LEO orbit prediction is more challenging due to complex perturbation forces, especially atmospheric drag. This study introduces a novel 9-parameter almanac model for LEO constellation, leveraging the Empirical Mode Decomposition (EMD) method. Our innovative approach uniquely balances almanac accuracy and simplicity by considering the atmosphere drag effects, addressing a critical gap in existing models. The proposed almanac model is validated with four in-orbit LEO satellites at various altitudes. For the LEO with a 600 km orbit or lower, our model achieves a 50% improvement in 23-day orbit prediction accuracy compared to the classical GPS almanac model. This significant enhancement extends to visibility prediction and signal acquisition performance. Our design limits the maximum elevation angle error to less than 1.5 degrees, efficiently excluding invisible satellites during LEO navigation signal acquisition. Furthermore, for visible satellite, the proposed LEO almanac reduces the signal frequency searching range by about 20 times during acquisition, with Doppler prediction errors better than 0.5 kHz/0.3 kHz for 95% of cases. These advancements represent a substantial leap in LEO navigation technology, offering improved efficiency and accuracy for future satellite systems.

Inter-beam handover schemes for LEO satellites in 5G satellite–terrestrial integrated networks

Unlike terrestrial handover schemes, the handover schemes in 5G satellite–terrestrial integrated network (STIN) face several challenges, such as large propagation delay, complex channel environment, and fast satellite movement. Therefore, the handover schemes designed in the 5G terrestrial network is not suitable for the 5G STIN. In view of this, this paper considers the inter-beam handover problem for the 5G STIN with a low earth orbit satellite and a ground user. We establish the satellite channel model, which includes path loss, rain attenuation, and multi-beam antenna gain. To model the mobile feature of the user, we consider a two-dimensional random walk model. Then, we propose A5 event-based conditional handover (CHO) scheme, time factor-based CHO scheme, and load factor-based CHO scheme to achieve efficient inter-beam handover. Considering that there may be multiple beams that meet the triggering condition in each handover scheme, we also propose three kinds of beam selection schemes, namely random beam selection scheme, maximum power-based beam selection scheme, and minimum distance-based beam selection scheme. To evaluate the performance of the proposed handover schemes, key performance indicators, such as handover frequency, ping-pong handover rate, unnecessary handover rate, handover failure rate, and average transmission rate are analyzed. Simulation results verify the superiority of the proposed handover schemes by comparing them with the benchmark scheme.

Enhancing Satellite Link Security Against Drone Eavesdropping Through Cooperative Communication

ABSTRACTIntegrated satellite terrestrial networks (ISTNs) are emerging as a promising next‐generation communication technology, for example, B5G and 6G, with low‐earth orbit (LEO) satellites playing a growing role. However, the complex and unique characteristics of ISTNs make them more susceptible to cyberattacks. Recently, the use of drones for public and private services has increased the risk of eavesdropping on LEO satellite links. Such scenario presents an extremely challenging environment due to dynamic nature of LEO satellite and drone along with atmospheric attenuation at sub‐THz frequencies. This study proposes a novel adaptive power‐bandwidth cooperative scheme designed to mitigate the likelihood of eavesdropping attacks on LEO satellite links communicating with a ground station when a drone is within the line of sight. The mathematical algorithm dynamically adapts the resources to maximize the normalized secrecy capacity in this challenging scenario while maintaining a reasonable signal‐to‐noise ratio (SNR) at the legitimate receiver. The adaptive scheme involves strategic cooperation with a nearby terrestrial third party to amplify and forward the satellite signal to the ground station receiver. The simulation results demonstrate the effectiveness of the proposed algorithm, showing significant improvements (> 70%) compared to the non‐adaptive scheme over a wide range of elevation angles.

Ionospheric TEC and its irregularities over Egypt: a comprehensive study of spatial and temporal variations using GOCE satellite data

Abstract This study delves into ionospheric characteristics during solar cycle 24 using data from the Global Positioning System (GPS) and Low Earth Orbit (LEO) satellites, GOCE. The present study fills the gap of not assessing and studying GOCE satellite data before in Egypt. Focusing on spatial and temporal variations of ionospheric Total Electron Content (TEC) over Egypt and the Middle East across a 4-year dataset, monthly average Vertical Total Electron Content (VTEC) variations are scrutinized, emphasizing extremes during heightened and reduced solar and geomagnetic activities. Results TEC typically decreases with latitude’s increase, with peak ionization during equinoxes and troughs during solstices. Notably, VTEC values consistently reach maximum values on days of heightened solar and geomagnetic activities. GOCE data is evaluated against International Reference Ionosphere (IRI) model and NeQuick2 model by selecting 10 days from all data by using a statistical comparison via t-tests. There is not significant difference between them except for two days between GOCE-IRI. The values of Root Mean Square Error (RMSE) are 3.7403 and 4.4655 for GOCE – NeQuick2 model and GOCE – IRI model, respectively. Ionospheric scintillation, signifying rapid electron density fluctuations, is assessed through amplitude scintillation index (S4), S4 proxy, and Rate Of TEC Index (ROTI). A robust correlation between S4 and S4 proxy is noted, thus scintillation can be studied by using S4 proxy instead of S4. Temporal variations indicate heightened scintillation during geomagnetic storms and peak solar activity, contrasting with reduced activity during solar minimum. Throughout the study period the maximum scintillation index values for ROTI, S4, and S4 proxy are 0.3, 0.15, and 0.05, indicating minimal scintillation. This comprehensive analysis, rooted in GOCE data, illuminates spatial and temporal dynamics of ionospheric TEC and elucidates ionospheric scintillation characteristics in the Egypt region. These findings are crucial for refining ionospheric models, improving scintillation prediction, and enhancing satellite communication and navigation systems, especially in the study region.

Decision Transformer-Based Efficient Data Offloading in LEO-IoT.

Recently, the Internet of Things (IoT) has witnessed rapid development. However, the scarcity of computing resources on the ground has constrained the application scenarios of IoT. Low Earth Orbit (LEO) satellites have drawn people's attention due to their broader coverage and shorter transmission delay. They are capable of offloading more IoT computing tasks to mobile edge computing (MEC) servers with lower latency in order to address the issue of scarce computing resources on the ground. Nevertheless, it is highly challenging to share bandwidth and power resources among multiple IoT devices and LEO satellites. In this paper, we explore the efficient data offloading mechanism in the LEO satellite-based IoT (LEO-IoT), where LEO satellites forward data from the terrestrial to the MEC servers. Specifically, by optimally selecting the forwarding LEO satellite for each IoT task and allocating communication resources, we aim to minimize the data offloading latency and energy consumption. Particularly, we employ the state-of-the-art Decision Transformer (DT) to solve this optimization problem. We initially obtain a pre-trained DT through training on a specific task. Subsequently, the pre-trained DT is fine-tuned by acquiring a small quantity of data under the new task, enabling it to converge rapidly, with less training time and superior performance. Numerical simulation results demonstrate that in contrast to the classical reinforcement learning approach (Proximal Policy Optimization), the convergence speed of DT can be increased by up to three times, and the performance can be improved by up to 30%.

An improved analytical method for rarefied aerothermodynamics on a complex geometry in free-molecular flows

A numerical method for high altitude aerothermodynamic analysis code for Very Low Earth Orbit (VLEO) satellite and spacecraft, named as HACS, is presented in this article. HACS is a computational tool that addresses the challenges by integrating the free-molecular gas kinetic model with novel particle sampling method and robust particle tracing algorithm to predict the shadow region on surfaces. To ensure the reliability and accuracy of the HACS, a rigorous verification and validation process has been systematically conducted by comparing the aerothermodynamic properties of forces, moments, and heat flux with the direct simulation Monte-Carlo (DSMC) results. The HACS is applied to the realistic geometries of VLEO satellite, the Apollo re-entry module, and spacecraft including fin and wing shapes. Results demonstrate that HACS provides the aerothermodynamic properties within the time frame of 60 seconds for the complex geometries and the accuracy of the HACS is guaranteed above 120 km altitude. The maximum relative error of the aerothermodynamic properties is less than 5% compared to the DSMC results at the lowest altitude of about 120 km, and has smaller relative errors as the altitude increases.

Orbit Determination Method for BDS-3 MEO Satellites Based on Multi-Source Observation Links

Research on augmentation and supplement systems for navigation systems has become a significant aspect in comprehensive positioning, navigation and timing (PNT) studies. The BeiDou-3 navigation satellite system (BDS-3) has constructed a dynamic inter-satellite network to gain more observation data than ground monitoring stations. Low Earth orbit (LEO) satellites have advantages in their kinematic velocity and information carrying rate and can be used as satellite-based monitoring stations for navigation satellites to make up for the distribution limitation of ground monitoring stations. This study constructs multi-source observation links with satellite-to-ground, inter-satellite and satellite-based observation data, proposes an orbit synchronization method for navigation satellites and LEO satellites and verifies the influence thereof on orbit accuracy with different observation data. The experimental results under conditions of real and simulated observation data showed the following: (1) With the support of satellite-based observation links, the orbit accuracy of the BDS-3 MEO satellites could be improved significantly, with a 78% improvement with the simulation data and a 76% improvement with the real data. When the navigation satellites leave the monitoring area of the ground monitoring stations, the accuracy reduction tendency of the orbit prediction could also be slowed down with the support of the LEO satellites and the accuracy could be maintained within centimeters. (2) Comparing the orbit accuracy with the support of the satellite-to-ground observation links, the orbit accuracy of the MEO satellites could be improved by 65.5%, 73.7% and 79.4% with the support of the 6, 12 and 60 LEO satellites, respectively. When the observation geometry and the covering multiplicity meet the basic requirement of orbit determination, the improvements to the orbit accuracy decrease with the growth of LEO satellite numbers. (3) The accuracy of orbit determination with the support of the LEO satellites or the inter-satellite links was at the centimeter level for both, verifying that inter-satellite links and satellite-based links can be used as each other’s backups for navigation satellites. (4) The accuracy of orbit determination with the multi-source observation links was also at the centimeter level, which was not better than the results with the support of the satellite-to-ground and inter-satellite links or the satellite-to-ground and satellite-based links.

Robustness of LEO satellite hypernetworks under different network topologies and attack strategies

The development of low earth orbit (LEO) satellites has become a crucial and essential component with the advancement of digitalization. However, LEO satellites also face various security challenges within their networks, and the failure of certain satellites may trigger cascading failures. To gain a deeper understanding of cascading failure process in LEO satellite networks and enhance its robustness, this letter proposes a novel satellite network model by combining complex network and hypernetwork theories. By altering the network structure and model parameters, the robustness performance of the LEO satellite network under three types of attacks and two different load distribution methods is thoroughly investigated. The results indicate that satellite networks with varying structures are distinct and exhibit different robustness characteristics under specific attack types. Furthermore, the robustness of satellite networks in multiple attack scenarios can be significantly enhanced by implementing improved load allocation strategies. These findings not only provide a theoretical foundation for the design and optimization of satellite networks but also ignite new perspectives and ideas for future research on their robustness.

LEO satellite clock modeling and its benefits for real-time LEO PPP timing

In the kinematic Precise Orbit Determination (POD) process for low earth orbit (LEO) satellites, a significant correlation exists between the orbital and clock parameters. Here, a LEO satellite clock model is proposed to enhance the Precise Point positioning (PPP) timing and time synchronization during the LEO orbit/clock determination. The GRACE-FO satellite was utilized to achieve PPP timing and time transfer for LEO satellites with the real-time (RT) products provided by three analysis centers, namely Centre National d’Etudes Spatiales (CNES), GMV Aerospace and Defense (GMV), and Wuhan Technical University (WHU). For the frequency stability of the PPP timing for LEO satellites, the short-term stability (1280 s) is about 10−13 level, and the long-term stability (10,240 s) is about 10−14 level. Compared with the traditional PPP method (Scheme1), the LEO satellite clock model (Scheme2) is capable of significantly reducing the noise, regardless of whether it is PPP timing or PPP time synchronization. The frequency stability of Scheme 1 shows an improvement in short-term stability (1280 s) by about 8 %-72 % and the max improvement of the long-term stability (10240 s) by approximately 39 %, the result also shows a better improvement in LEO time synchronization.

UAV clusters information geometry fusion positioning method with LEO satellite system

The existing Low-Earth-Orbit (LEO) positioning performance cannot meet the requirements of Unmanned Aerial Vehicle (UAV) clusters for high-precision real-time positioning in the Global Navigation Satellite System (GNSS) denial conditions. Therefore, this paper proposes a UAV Clusters Information Geometry Fusion Positioning (UC-IGFP) method using pseudo-ranges from the LEO satellites. A novel graph model for linking and computing between the UAV clusters and LEO satellites was established. By utilizing probability to describe the positional states of UAVs and sensor errors, the distributed multivariate Probability Fusion Cooperative Positioning (PF-CP) algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster. Criteria to select the centroid of the cluster were set. A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory, which overcomes the discontinuity problem caused by the change of cluster centroids. Finally, the UC-IGFP method achieves the LEO continuous high-precision positioning of UAV clusters. The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster. It significantly improves the accuracy and reliability of LEO-UAV cluster positioning. The results of comprehensive simulation experiments show that the proposed method has a 30.5% improvement in performance over the mainstream positioning methods, with a positioning error of 14.267 m.

Analysis of multipath effects on Low Earth Orbit navigation satellites

Abstract With the large-scale emergence of Low-Earth Orbit (LEO) internet constellations, the direct or indirect utilization of LEO communication constellations for navigation and positioning has become a hot topic of current research. However, the multipath effect remains a critical factor influencing positioning accuracy. Compared to traditional Medium-Earth Orbit (MEO) satellites, LEO satellites move swiftly, resulting in faster multipath variations, which renders traditional multipath envelope analysis methods inapplicable. This study proposes a novel analytical model tailored to the multipath effect characteristics of LEO satellites. Through this model, we have observed that the multipath variations of high-frequency signals in LEO rapidly fluctuate near zero, offering the potential to reduce errors through smoothing methods. Furthermore, the study reveals that the impact of the multipath effect is positively correlated with orbital altitude and inversely correlated with carrier frequency. This study provides a new perspective for understanding the multipath effect characteristics of LEO satellites and offers necessary theoretical support and practical guidance for improving the accuracy of navigation and positioning systems based on LEO satellites. Future research can further explore multipath suppression methods and promote the widespread application of LEO satellites in the field of navigation and positioning.

Based on coverage evaluation design method study of factor low-orbit infrared remote sensing constellation configuration

Abstract To satisfy the infrared detection coverage demands of Low Earth Orbit (LEO) satellites in global missile surveillance, we have devised a comprehensive evaluation system for global missile infrared remote sensing coverage performance. By referencing Walker’s extensive and uninterrupted global coverage constellation layout, we conducted a thorough analysis of various constellation configuration parameters. This analysis aimed to assess the coverage efficiency of differently configured LEO networking satellites. Following a detailed comparative analysis, we settled on an LEO infrared remote sensing constellation configuration featuring an orbit height of 1150 km and an orbit inclination of 60°. After an in-depth examination of the capabilities of the infrared remote sensing constellation and the characteristics of the detection zone, we constructed a Blind Spot Compensation Constellation. This was achieved by integrating four additional LEO satellites with a 0° orbit inclination to bolster coverage in low-latitude regions. Using our comprehensive coverage evaluation system, we rigorously evaluated the ground coverage capabilities of multiple constellations. Notably, the Blind Spot Compensation Constellation achieved impressive coverage, reaching 100%, and excelled particularly in the latitude belt of 20° or less. Although the Original Constellation performed better in the 40° latitude belt compared to the Blind Spot Compensation Constellation, it showed some deficiencies in coverage at a 50 km altitude. Specifically, it averaged 18.417 gaps per day, with a coverage rate slightly below 100%. However, it achieved full coverage at other altitudes. To validate our findings, we conducted scenario simulations. For missile targets, the Original Constellation offered a maximum coverage multiplicity of 6, with a total access duration of 4539.1 seconds. On the other hand, the Blind Spot Compensation Constellation boasted a maximum coverage multiplicity of 8, with a total access duration of 5465.9 seconds. Importantly, both constellations fully covered the missile’s entire 1056-second lifecycle, showcasing commendable performance. In conclusion, the LEO infrared remote sensing constellation and its complementary counterpart, developed and rigorously tested in this study, not only meet the demands of continuous global detection but also cater to the priority detection needs of diverse geographical regions.