Satellite Based Command and Control (C2) UAV Communication

Methods, apparatus and systems for setting up and updating C2 (command and control) communication links between unmanned aerial vehicles (UAVs) and ground stations. The methods involve initial setup using on-demand connectivity or pre-established connectivity, updating links due to changes in UAV-C (UAV controller) IP addresses, switching links between direct and network-assisted modes, and handling link switches when using a UAV traffic management (UTM) system for navigation.

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Virtualized communication framework for vehicles like aircraft and UAS overlays multiple logical networks on a single physical infrastructure (e.g., cellular or satellite) to segregate data streams critical C2 links with <1s latency, ≥64-bit HMAC authentication, >99.999% continuity; non-critical telemetry; and ATC relays with <155ms latency. This enhances QoS prioritization without hardware changes, enabling secure BVLOS operations and urban air mobility.

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Procedures for setting up and switching C2 communication links between unmanned aerial vehicles (UAVs) and their ground control stations, with support from network infrastructure and UAV traffic management systems. The procedures allow efficient handover between direct and network-assisted links, as well as between network-assisted links using different networks, based on authorization and performance considerations.

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Enhancing reliability of wireless communications to/from drones operating beyond visual line of sight (BVLOS) to enable safe and regulatory-approved BVLOS flights. The technique involves modifying transmission parameters like modulation and coding scheme (MCS), transmit power, and retransmission count based on network conditions to increase the likelihood of accurate decoding at the drone receiver. This improves reliability of critical commands and control data over wide area networks for BVLOS drone operations.

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A short-range universal UAV ground command and control station and system that integrates command, control, communication, and intelligence functions into a compact, modular design. The system features a square cabin with separate compartments for maintenance, power supply, and communication control, enabling efficient operation and maintenance of UAVs. The communication control system employs dual-channel C+L band communication with the UAV, providing backup and redundancy capabilities for secure and high-bandwidth data transmission.

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A method for dynamically establishing an application layer communication link between an unmanned aerial vehicle (UAV) and a UAV controller (UAC) using a traffic management system as a relay. The method involves the UAC sending a command request to the traffic management system, which forwards it to the UAV. The UAV responds with a command response, and both the UAC and UAV establish an application layer tunnel based on indications in the request and response. This tunnel enables subsequent communication between the UAC and UAV while maintaining pairing and authorization.

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A method for seamlessly switching between direct and network-assisted communications for command and control (C2) of unmanned aerial vehicles (UAVs) to maintain reliability when the direct link degrades. The method involves detecting weak signal strength or deterioration in the C2 connection over the direct PC5 link between the UAV and its controller. If network connectivity is available, it switches to a C2 connection over the network. If network connectivity is not available, it notifies the application layer that a network switch is not possible. This allows the UAV to continue receiving C2 commands even if the direct link becomes weak.

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End-to-end Quality of Service (QoS) fulfillment for indirect Unmanned Aerial System (UAS) communications, particularly for Command-and-Control (C2) applications. The system ensures QoS across multiple networks and devices by dynamically adapting QoS parameters for each session based on changes in the other session's QoS, and communicating these changes to the respective networks.

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Managing Command-and-Control (C2) communication mode of operation for Unmanned Aerial Systems (UAS) by enabling dynamic switching between direct and indirect C2 modes while maintaining service continuity and minimizing impact on other UAS operations. The system includes a UAS server that receives application requests to manage C2 mode, monitors link conditions, and determines when to switch modes based on reports from UAS applications. The server transmits switching instructions to the UAS, which modifies its C2 communication session accordingly.

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A method for establishing end-to-end security for command and control (C2) communications between a UAV and a UAV controller (UAV-C) in a 3GPP system. The method involves a network-assisted C2 link establishment procedure where the network receives a request from the UAV, forwards it to the USS/UTM, and receives a response with a peer key and UAV-C IP address. The network then forwards this response to the UAV, enabling secure C2 traffic exchange. The UAV can also receive link update commands from the USS/UTM to modify the security association, generating new keys and sending an acknowledgement.

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Dynamic network slicing for unmanned aerial vehicles (UAVs) that enables seamless switching between diverse network configurations during flight operations. The system dynamically adapts network resources to support real-time applications, such as command and control, video streaming, and machine type communications, while maintaining optimal performance across varying network conditions. This enables UAVs to operate in multiple network slices, each optimized for specific applications and mission requirements, ensuring optimal network utilization and performance across diverse flight scenarios.

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Methods and apparatuses for pairing and authenticating unmanned aerial vehicles (UAVs) with UAV controllers (UAV-Cs) in cellular networks, enabling Beyond Visual Line of Sight (BVLOS) operations and secure communication for UAS applications. The pairing process involves exchanging identifiers between the UAV and UAV-C, authenticating with the network and UTM, and establishing a unique UAS identifier for authorization and command and control (C2) communications. The system supports multiple UTMs, PLMNs, and removable cellular modems for flexibility and scalability.

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A system for managing command and control (C2) datalinks for unmanned aircraft systems (UAS) operating beyond visual line of sight (BVLOS). The system includes a control station with multiple antenna elements that transmit C2 signals to UAS within a designated coverage volume. The control station dynamically manages the C2 spectrum to prevent interference between UAS and ensure reliable communication with each aircraft. When a UAS approaches the control station's geofenced area, the system automatically switches the UAS to a different control station or reallocates spectrum to maintain safe operations.

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Direct command and control communication between a UAV and a controller through a unified network architecture, enabling optimized QoS management for both uplink and downlink communications. The system leverages a group-based approach to manage QoS across both the UAV and controller, with separate groups for uplink and downlink communications. A centralized network resource manager coordinates QoS provisioning and adaptation based on group identifiers, ensuring consistent QoS levels across both communication paths. This unified approach enables efficient QoS management while maintaining separate control interfaces for the UAV and controller.

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Methods, apparatus, and systems for setting up and updating control and command (C2) communication links between unmanned aerial vehicles (UAVs) and ground control stations, particularly for UTM navigation, using wireless communication protocols such as 802.11ah. The systems enable C2 link setup and update procedures, including procedures for UAV-C setup, link switch, and IP address changes, as well as UTM-assisted UAV operations.

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A system and method for preventing inadvertent loss of command and control (C2) link in unmanned aerial systems (UAS/UAV). It generates a predictive C2 link quality model for planned routes using historical data and adjustments for conditions (weather, interference, traffic) during flight, acquires real-time link metrics, computes deviation (ΔC2 LQ) from model, and if exceeding threshold triggers autonomous maneuvers (e.g., backtracking, homing, hover-and-hold) to restore/maintain connectivity. Supports onboard/remote controllers, route adaptation, user alerts, and multi-UAV coordination for enhanced BVLOS safety and reliability.

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A method for enabling unmanned aerial system (UAS) services in a 3GPP cellular network, comprising: provisioning services for a UAS in the network; enabling communication for command and control in 5G systems; and enabling UAS service for identification and operation in the 3GPP system. The method includes network-assisted UAS discovery and identification, configuration for C2 monitoring in C2 communications, and support for UAV configuration for C2 monitoring in C2 communications.

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Reliable remote control of unmanned vehicles using multi-connectivity to multiple wireless networks. The vehicle simultaneously connects to multiple networks like cellular and satellite. A connectivity control function determines which network to use based on real-time quality monitoring and requirements. This avoids relying solely on one network and improves reliability compared to sending duplicate data over multiple networks. The function switches connections proactively as needed to maintain critical control data delivery.

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The article identifies that swarms of unmanned aerial vehicles (UAVs) have unique advantages in performing special tasks and can be effectively used various scenarios. Accurate navigation within the swarm is basis prerequisite for these tasks. Unlike localization a single UAV, allow exchange dissemination accurate information about positioning each which increases overall accuracy localization, but also creates problem uncertainty propagation. To eliminate uncertainty, an integrated method improved, reduces uncertainties. mathematical model normal gamma distribution. stages joint UAV defined as follows: first, robust filter based on distribution to estimate error states solve measurement caused by outliers external correction information; secondly, corrective INS resolution, performed determine positions statistical linearization distance model; thirdly, linearized model, augmented nonlinear least squares other UAVs, ultimately gives results entire when missions. Thus, missions which, unlike existing ones, integral approach eliminating uncertainties applying distribution, mutual UAVs... Read More

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Remote piloting system for vehicles like drones that allows pilots to operate the vehicles from a distance using wireless communications and displays. The system mitigates the limitations of remote piloting by using onboard digital controls, autonomous planning, and adaptive displays that adapt to the pilot's head movements. It combines multiple wireless links like satellites, direct radio, and terrestrial networks to provide redundancy and reliability. The pilot's displays show real-time video from vehicle cameras and adaptive views based on head movements. This allows remote pilots to have better situational awareness and control performance than an in-vehicle pilot. The system also manages communications links, mitigating bandwidth, latency, and intermittency challenges.

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A system for managing communications between a remote pilot and an uncrewed aircraft using satellite links with latency. The system uses an on-board computing system on the aircraft to monitor the radio frequency (RF) communication channel with air traffic control (ATC) and manage voice messages. When a remote pilot sends a voice command over satellite, the aircraft system buffers it until the RF channel is open. It then immediately transmits the voice message over RF. If the RF channel is busy, the aircraft system delays transmission until appropriate. This mitigates latency issues in satellite links by managing voice communications locally on the aircraft.

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This research derives the ground target tracking algorithm of a fixed-wing UAV equipped with gimballed camera. The camera is controlled to track moving independent motion, and this achieved by employing UKF estimate position velocity target. input bounding box target, which generated YOLO, deep neural network used detect estimated state essential for image control, it IBVS gimbal controller lock when in flight. Simulations are conducted through verify efficacy developed controller.

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In unmanned aerial vehicle (UAV)-mounted base station (MBS) networks, user equipment (UE) experiences dynamic channel variations because of the mobility UAV and changing weather conditions. order to overcome degradation in quality service (QoS) UE due variations, it is important appropriately determine three-dimensional (3D) position transmission power (BS) mounted on UAV. Moreover, also account for both geographical meteorological factors when deploying UAV-MBSs they ground various regions atmospheric environments. this paper, we propose an energy-efficient UAV-MBS deployment scheme multi-UAV-MBS networks using a hybrid improved simulated annealing-particle swarm optimization (ISA-PSO) algorithm find 3D each UAV-MBS. developed simulator UAV-MBSs, which took conditions into consideration. The proposed demonstrated superior performance, where achieved faster convergence higher stability compared with conventional approaches, making well suited practical deployment. integrates terrain data based geolocation real-time information produce more results.

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Introducing "Cosmic," an innovative modular drone delivery platform designed to autonomously transport payloads in environments where traditional logistics falter, such as disaster- stricken areas and rural locations. At its core lies the Cosmo v1 embedded flight controller based on STM32H7 microcontroller, which handles low-level sensor integration, motor control, stabilization. Accompanying it is a Raspberry Pi Compute Module 5 (CM5), enabling high-level autonomy, mission logic, edge processing. With dual-processor architecture, Cosmic bridges gap between reliable control adaptable decisionmaking, allowing autonomous aerial even under infrastructure constraints. This paper details system's hardware design, software implementation, comparative evaluation, future development roadmap

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Communication method and apparatus for network devices like satellites, drones, or aircraft that move and change positions. The method involves determining target bandwidth based on movement information, instead of fixed PCI planning. This reduces complexity and improves performance in dynamic networks. The target bandwidth is associated with movement direction and speed. When movement changes, the device uses different bandwidths. This allows optimizing bandwidths for each position without requiring stable cell assignments.

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For real-time detection scenarios such as battlefield reconnaissance and surveillance, where high positioning accuracy is required receiving station resources are limited, we propose an innovative distributed aerial target localization method with low degrees of freedom. This based on a hybrid measurement approach. First, model established using the spatial geometric relationship between node network configuration target, angle arrival (AOA) time difference (TDOA) measurements employed to estimate partial parameters. Then, frequency (FDOA) utilized enhance parameter estimation. Finally, inter-node measurements, pseudo-linear system equations constructed complete three-node localization. The uses satellites radiation sources transmit signals, unmanned vehicles (UAVs) acting nodes capture signals. It effectively utilizes information, enabling only three stations. Simulation results validate significant advantages proposed algorithm in enhancing accuracy, reducing costs, optimizing resource allocation. technology not provides efficient practical solution for surveillance systems but als... Read More

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Abstract: - Conventional tracking systems relying on GPS and cellular infrastructure are ineffective in environments with little or no connectivitysuch as remote wilderness, mountainous regions, disaster-affected areas. This paper introduces a hybrid architecture that integrates satellite communication, mesh networking, Radio Tomographic Imaging (RTI), signal jumping, drone-assisted relays, Low-Power Wide-Area Networks (LPWAN). The proposed system addresses loss challenges by utilizing AI-driven prediction autonomous drones to extend coverage improve real-time traceability. Performance is evaluated through simulations real-world case studies based key metrics including coverage, latency, energy efficiency, reliability. approach demonstrates strong potential for critical applications search rescue, defense operations, systems, contributing toward the development of resilient off-grid communication technologies. Keywords: Remote Tracking, Dead Zones, Mesh Networks, Satellite Communication, Drone Relays, RTI, LPWAN, Signal Prediction, Off-Grid Search Rescue.

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Enabling unmanned aerial vehicles (UAVs) to navigate autonomously without relying on cameras and compasses when environmental conditions like low light or magnetic interference impair their effectiveness. The UAV uses a global navigation satellite system (GNSS) to determine its position and velocity in a world frame of reference. It also measures acceleration and angular rate signals from onboard accelerometers and gyroscopes to determine acceleration and orientation in a navigation frame of reference. By combining GNSS positioning with inertial measurements, the UAV can navigate autonomously even when cameras and compasses are unreliable.

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<title>Abstract</title> This article presents an overview of issues related to the trials SW-4 SOLO helicopter in various configurations resulting from HELIMARIS and Remotely Piloted Aircraft System (RPAS) In Air projects. It covers a wide range activities carried out by Engineering Flight Line teams, both areas calculation analyses as result simulation studies, flight ground tests. The document findings two projects, which took part. One them is OCEAN2020 Project, particular part concerning stage with modification for needs over water operational capabilities. other RPAS where main configuration changes were innovative implementation system satellite communication, series tests demonstrating possibility controlling unmanned aerial vehicle use data link. Over operations include cooperation vessels, was facilitated present research project using T-23 class corvette. Numerical presented paper, followed simulator test campaigns, ensured that performance objectives met, well compliance safety required authorities. particular, mechanics platform positively evaluated terms control margins,... Read More

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The fixed time dynamic compensation based prescribed performance formation control is developed for the position of heterogeneous multi-agent systems consisting various unmanned aerial vehicles (UAVs) and surface (USVs). law construed by introducing two flexible functions in terms average limit upper lower along axis. To estimate uncertain dynamics systems, a fixed-time observer designed. At same time, controller designed with virtual speed controller. Through rigorous convergence analysis, resulting guarantees desired while velocity are introduced. Finally, through numerical simulation expected time-varying trajectory constant trajectory, validity prescribe performance.

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Optimizing communication in swarms of drones to enable efficient and reliable control of large numbers of drones. The optimization involves clustering the drones into groups with a master drone that communicates with a central server, and slave drones that relay messages from the master. This reduces the number of required communication channels compared to each drone directly connecting. Clustering also allows faster area coverage, obstacle avoidance, and resource sharing. If a master fails, another slave can be promoted. This enables robust swarm operation by minimizing communication breakdowns.

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Aerial network architecture using hybrid communication links like FSO and RF that allows simultaneous transmission and failover protection. The network nodes like drones have overlay networks with FSO transmitters/receivers and RF transmitters/receivers. A processor modulates data for both links and balances traffic preemptively based on mission planning and link conditions. This reduces congestion and packet loss during link failures. The processor also uses packet erasure coding to recover from spurious FSO link loss without needing error prediction. The hybrid links and techniques provide resilient and efficient networking for aerial platforms.

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Extending timing relationships in non-terrestrial networks like satellite communications to compensate for the longer propagation delays. It involves using scaling factors and offsets to adjust the timing gaps between downlink and uplink transmissions in NTN links. The scaling factors are determined based on factors like cell size and user capability. The offsets are calculated from timing advances. This allows extending the existing K1 and K2 time gaps to suit devices with lower timing accuracy in NTN.

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In the paper, an analysis is presented of existing methods for enhancing efficiency joint route planning process a group UAVs using well-known scientific research techniquesnamely systems analysis, object search theory methods, and mathematical modeling optimization techniques. It determined that Differential Evolution Algorithm (DEA) operates stably, exhibits high convergence rate normal parallelism, effectively solves global problems with continuous variables. However, involves certain specific tasks are difficult to address solely DEA as investigated in paper. article, it unmanned aerial vehicles complex task taking into account number constraints: variable dynamics UAV movement target point, maximum flight path length, minimum/maximum speed, time, payload, temporal sequence between key mission points, waiting time. The main ideas distinctions improved method article are: implementation procedure avoiding local optima, formation three-dimensional space admissible region, methods adaptability respect mutation strategies genetic algorithm. This eliminates limitations associate... Read More

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Path setting method for an unmanned aerial vehicle (UAV) that allows it to continue flying without interrupting GPS signal even when it loses line of sight with satellites. The method involves calculating the number of visible GPS satellites based on terrain elevation data, comparing it to a minimum required number for flight, and adjusting the UAV's vertical and horizontal positions if necessary to maintain enough satellite visibility. This prevents GPS signal loss and allows safe flight even over obstructed areas.

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Autonomous aerial delivery system with multiple drones that can operate fully autonomously to deliver items without human intervention. The system has a central management server that schedules flight plans for the drones. The drones can rotate 360 degrees and transition between vertical takeoff/landing and horizontal flight. They communicate with the server over a wireless network to receive flight plans and check for updates. This allows coordinated, autonomous delivery of multiple items using a fleet of drones.

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One-station dual-satellite communication system for unmanned aerial vehicles (UAVs) using two satellites in the same orbit to improve UAV satellite connectivity. It allows UAVs to simultaneously use a traditional wide-beam satellite system and a multi-spot beam high-throughput satellite system. This provides real-time transmission of UAV commands, telemetry, and mission data. The wide-beam satellite ensures reliability while the high-throughput satellite provides higher bandwidth. It allows dynamic resource allocation based on requirements, like critical commands using wide-beam and large data using high-throughput.

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Communication relay system for large and medium unmanned aerial vehicles (UAVs) that enables them to relay voice, data, and video between ground stations and other UAVs beyond visual range. The system involves loading a 4G broadband base station on the UAV to create a local wireless network. It also has an onboard video encoder, switches, and terminals for connecting to line-of-sight terminals and satellite terminals. This allows the UAV to relay signals between ground stations and other UAVs using its own base station instead of relying on ground stations. The UAV can also send reconnaissance video back to ground stations. The encoder compresses video to save bandwidth.

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A method to enable long-range communication between a UAV and ground station without using multiple ground stations. The method involves using multiple communication links like L-band, carrier, and satellite links in a redundant and adaptive manner. It allows reliable communication over long distances by intelligently switching between links based on signal quality. When a primary link fails, it switches to a secondary link. If both primary and secondary links fail, it uses a tertiary satellite link. This prevents the UAV from receiving multiple conflicting commands and simplifies flight tasks while extending range compared to using multiple ground stations.

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Method for improving the reliability and stability of beyond-visual-range (BVR) communication links for UAVs using redundant links. The method involves integrating a satellite communication main link with a backup Beidou short message link. If the main satellite link fails, the UAV switches to the Beidou link to maintain BVR communication. This allows the UAV to continue operating and returning according to its route. The backup link also allows active querying from the ground to locate the UAV in an emergency.

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Scheduling satellite communications for drones to enable real-time data transmission when ground stations are out of range. The method involves determining the drone's location based on its planned path, checking if it's at the edge of coverage for the current satellite, finding upcoming satellites within range, and switching to a new satellite to transmit data if needed. This allows drones to seamlessly switch between ground stations and satellites for uninterrupted real-time data transfer.

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Using drones and balloons as part of a communications system with satellites to provide global coverage. The drones and balloons are non-orbiting aerial nodes that can be used in local systems or in combination with satellites for wider area communications. They are deployed at altitudes of at least 10 miles to avoid interfering with commercial aviation. The drones can be lighter-than-air or heavier-than-air, and can be lift-assisted. This allows using drones closer to the ground to increase signal strength. The drones can transition to higher altitude satellite nodes for longer distance routes. The system uses multiple layers of aerial nodes at different altitudes for routing data and calls over long distances.

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A method to enable reliable and long-range communication for drones that can switch between different networks based on quality conditions. The method involves determining the current communication quality parameters of the drone, like signal strength, bit error rate, delay, and transmission rate. If the quality falls below thresholds, the drone switches to an alternate network like mobile or satellite instead of just dedicated frequency bands. This allows drones to maintain control and communication when wireless signals weaken or are blocked. The method also involves suspending data transfer and preloading maps when using satellite networks.

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Emergency communication system using drones for disaster areas that provides reliable, rapid networking and secure data transmission. The system combines drones with base stations and uses satellite communication to restore communication after infrastructure damage. Drones are hierarchically networked with cluster heads, masters, and slaves to expand coverage. They authenticate and securely communicate with each other and satellites. The system also manages drone endurance and handover to sustain networks. It mitigates limitations of fixed-wing drones and tethered drones for disaster comms.

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Communication system for drones that allows long-range, low-cost, and lightweight communication for cargo drones operating at high altitudes and long distances. The system uses low-orbit satellites for relaying instead of high-orbit satellites. The drone communicates directly with a gateway on the ground, which relays data to low-orbit satellites. The drone also communicates with the satellites directly. This allows using an omnidirectional antenna and reduced power since the satellites are closer. The satellites have wider bandwidth due to Doppler shift. It reduces drone equipment size, cost, and weight compared to high-orbit satellites. The ground station and satellites can provide telemetry and remote control, while images are only downloaded during landing.

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An L-band UAV remote communication circuit based on a star network platform to enable reliable and flexible long-range UAV communication using satellites. The circuit has components like power supply, baseband, main control, RF switch, and RF transceiver. The main control module connects to the UAV's flight control wireless and processes signals. It modulates/demodulates data using the baseband. The RF switch routes this to the low-orbit satellite. The satellite relays to a ground station. The RF switch also connects the RF transceiver for UAV-to-satellite links. This allows the UAV to communicate with the ground station using the satellite as a relay. The RF switch controls both connections.

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Emergency information service system using satellite-borne drones and high-throughput satellites to provide real-time perception, information support, and emergency communication command for soldiers in the rear based on high-throughput satellites. The system has a multi-node platform including satellite, space, and ground nodes, high-throughput satellite, and a satellite-ground integrated communication network. The drone carries an airborne satellite terminal and emergency base station. It connects to ground terminals using C/UHF and satellite using high-throughput. The drone sends video backhaul to ground, high-throughput satellite relays, and backhauls to command center. The drone also interacts with the satellite and ground network using fixed-wing drones.

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An unmanned aerial vehicle (UAV) system for beyond-view-range image transmission using a star network architecture. The system involves using a ground station, satellite communications, and image compression to extend UAV video range. The UAV captures video, which is compressed and modulated by a chip. It's then transmitted via satellite to the ground station where it's demodulated and converted back to digital. The compressed video is then sent to the UAV. This allows UAVs to transmit video over long distances using satellites instead of line-of-sight links.

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Target search system using UAVs equipped with satellite communication for wide-range search, rapid discovery, identification, tracking and location of targets in complex environments. The UAVs have a ground control station connected via ground antenna and data link. The UAVs can fly and search, while the ground station receives video, location data, etc. via satellite. It allows remote target search over large areas using UAVs with satellite connectivity.

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Real-time communication system for long range unmanned aerial vehicles (UAVs) that enables remote control and high bandwidth data transfer over satellite links when the UAV is far from the ground station. The system uses terrestrial cellular networks for initial short range control, and switches to satellite links when wireless packet loss exceeds a threshold. This allows the UAV to maintain real-time control and high bandwidth data transfer over satellite links when it is out of range of the ground station's radio. The ground station sends control signals via cellular, which are forwarded via satellite to the UAV. This expands UAV range and improves accuracy of human-machine task execution.

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