Solutions for Global Drone Regulatory Compliant

Centralized management of a plurality of unmanned aerial vehicles (UAVs) of different types for preventing complications of processing related to information acquisition from each UAV, even in a case where flight management of a plurality of types of UAVs different from each other is performed. The technique involves using an information communication device attached to the UAVs that acquires flight status information and transmits it wirelessly in a predetermined data format. A centralized management device receives and monitors the UAVs using the flight status information transmitted from the information communication device. This standardized format allows uniform acquisition of flight status from different UAV types.

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An air traffic control system for managing unmanned aerial vehicles (UAVs) uses existing wireless networks like cell networks to enable safe drone delivery operations. The system monitors and controls UAV flights and provides navigation assistance, collision avoidance, switchover between networks, and airspace coordination. The system uses wireless networks to communicate with UAVs and leverages network coverage, bandwidth, and redundancy for air traffic management.

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Wirelessly detecting, identifying, locating, and neutralizing unauthorized unmanned aerial vehicles (UAVs) within a predetermined area. It uses a distributed network of radio nodes that passively fingerprint the UAV's RF signals to identify it. By detecting the signals at multiple nodes, they can triangulate the UAV's location. The network can then generate and transmit control signals on the same frequency to take over control of the UAV.

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Manage and restrict drone operations and equipment to prevent unauthorized use and avoid bad actors gaining access to restricted capabilities. It involves an off-board computer that checks user licenses and selectively provides equipment control software to the drone based on the license. If a license authorizes certain equipment, it will transmit the proper software to operate it. This ensures the drone cannot operate unauthorized equipment.

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Aerial unmanned vehicle privacy breach defense infrastructure that can detect drones within a threshold distance of an individual, alert them, track the drones, and execute countermeasures. The system includes a mobile app with detection, alert, tracking, and countermeasure modules. It uses sensors like microphones, cameras, radar, or radio frequency detectors to identify nearby drones. Countermeasures can involve disabling drones with electromagnetic signals or lasers or deploying other drones for interception.

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Controlling aerial vehicle communication to optimize data transfer and reliability between aerial vehicles. The control involves dynamically setting the operating mode of each aerial vehicle based on flight plan and network quality information. The operating modes are: 1) sending data between vehicles through the communication network and 2) sending data directly between vehicles without using the network.

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Efficiently intercepting unmanned aerial vehicles (UAVs) that enter restricted airspace without the expense and complexity of fighter jets or high-powered countermeasures like nets, lasers, or jammers. The interception method involves launching a cloud of small objects into the projected path of the target UAV to disable it. The objects ensnare propellers or block airflow to disrupt lift and cause an automatic landing. Probability analysis of the UAV's projected path determines when and where to launch the intercepting objects.

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System and methods for managing unauthorized airborne drones communicating with cellular networks. The system detects unauthorized drone operations and restricts its network access, preventing wasted resources. The network node can also send a message indicating the connection will be released, with conditions for reconnection, or perform a forced detach procedure.

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Detecting connectivity anomalies in a flight area to ensure the safe operation of unmanned aerial vehicles (UAVs) in beyond-line-of-sight applications. The method involves acquiring actual connectivity measurements at various locations within the flight area, comparing them against predicted connectivity data, and identifying deviations as anomalies. These anomalies are reported to aviation control centers so that UAV guidance can be adjusted.

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Geofence management for unmanned aerial vehicles (UAVs) to enhance safety and regulation. The system uses sensor data from in-flight UAVs to detect objects and create geofences around them. This allows UAVs to detect and avoid objects not visible to their own sensors. The geofence management uses data from multiple UAVs to improve accuracy and reliability. It can create geofences around objects detected by one UAV that other UAVs can then avoid.

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An automated system helps unmanned aerial vehicle (UAV) pilots plan and monitor flights to avoid airspace restrictions. The system uses a checklist of flight restriction conditions generated based on a planned flight area and time period. The system also monitors for changes to the restrictions and notifies the pilot before the flight if any restrictions have changed.

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Monitoring and regulating unmanned aerial vehicles (UAVs) to improve safety and security without requiring physical modification to the UAV. The method involves detecting UAVs by capturing and analyzing datagrams transmitted by the UAVs. The datagrams contain monitoring data like UAV and controller locations. The UAVs are configured to transmit these datagrams along with their normal communications. This allows existing UAV communication systems to be used for monitoring.

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A device and method to automatically track and disable unauthorized drones using multiple cameras and a pan-tilt electromagnetic module. Cameras detect and track the drone's movements. A control unit analyzes the video and moves the pan-tilt module to keep the drone in view. It can then aim an electromagnetic pulse to disable the drone's systems. The automated tracking and aiming improve response time and accuracy compared to manual anti-drone systems.

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Using a network of high-speed cameras to remotely supervise and control drones in a way that maintains a visual line of sight and avoids the need for human pilots to physically see the drone. The camera network captures the drone in flight and provides real-time flight data to guide it safely, even in complex environments where GPS may not work. It enables efficient drone operations beyond the visual line of sight while complying with regulations.

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Integrated anti-drone management system that can detect, identify, prioritize, and neutralize unauthorized drones that enter restricted areas. The system uses drone detection, identification, and neutralization technologies. When a drone is detected, its ID and position information are obtained. The system then determines whether to neutralize the drone based on its ID, position, and other data like flight registration. If neutralization is required, the system takes action. By linking detection, ID, and neutralization, the system can effectively respond to unauthorized drones in restricted areas.

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Policing unmanned aircraft to prevent unauthorized control and dangerous use. The system uses remote identification, flight plan verification, dual control, and biometric pilot authentication to police unmanned aircraft. Approaches include requesting flight plans, remotely destroying non-compliant drones, and determining pilot identity through biometrics.

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A system for managing drone flight to prevent unauthorized areas. The system sets buffer zones around restricted areas where drones are not permitted to fly. The size of the buffer zones is dynamically adjusted based on factors like the number of nearby cell towers, signal strength, and GPS accuracy. This allows precise control over drone access to restricted areas without overly restricting flight in nearby permitted areas.

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Detecting and mitigating unauthorized drones using a technique called HopSAC to estimate and model the frequency hopping parameters of a drone's radio signal. The technique involves iteratively fitting a parameter model to a sequence of received signal samples and classifying the samples as inliers or outliers. This allows the frequency hopping parameters to be accurately estimated even in the presence of noise, interference, and other impairments. The estimated parameters can then be used to identify and track the drone.

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Centralized system for registering, tracking, and controlling drones to enhance safety and access control. The system receives location data from drones via long range, low power wireless transmission, updates a central registry with the data, and generates displays of drone locations in vicinity of public devices. It also determines access control areas and communicates with drones to authorize entry based on bidding process.

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A drone tracking system that uses LIDAR to detect and track drones entering a monitored airspace. The system uses a horizontally mounted LIDAR to create a "light fence" of fanned beams that can detect objects crossing the beams. When a drone is detected, an alert can cue a long-range LIDAR to track it. The light fence provides drone detection while the long-range LIDAR provides tracking.

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