Abstract: Systems and methods for providing drone activity cloud services to cloud consumers using cloud and edge computing are provided. The drone monitoring service is rendered by drone sensors detecting and identifying drones, cloud and edge servers aggregating drone activity data from sensors and UAS traffic management systems, and cloud consumers monitoring drone activities using cloud and edge devices to access the cloud. The drone data analytics service reports drone activity statistics, predicted drone activities, and abnormal behaviors to cloud consumers based on the statistics and behavior models obtained by machine learning and federated learning techniques. The drone mitigation service, when initiated by cloud consumers, determines how to optimally configure sensors and collaboratively send signals to deactivate unauthorized drones. Moreover, data processing, artificial intelligence, mobility support, and traffic management functional units empower cloud and edge servers to support these cloud services.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, obtain predetermined data of expected communication protocols used between the drone and a controller, and determine whether the RF signal corresponds to one of the expected communication protocols by comparing the samples of the RF signal to the predetermined data and decoding the RF signal. In further aspects the system extracts a unique identifier of the drone based at least partially on the decoded RF signal.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a one or more drones includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, the set of samples comprising samples of the first RF signal, obtain a parameter model of the first frequency hopping parameters, and fit the parameter model to the set of samples.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, obtain predetermined data of expected communication protocols used between the drone and a controller, and determine whether the RF signal corresponds to one of the expected communication protocols by comparing the samples of the RF signal to the predetermined data and decoding the RF signal. In further aspects the system extracts a unique identifier of the drone based at least partially on the decoded RF signal.

Abstract: A system and method for detecting a scrambling seed in communication between a drone and a controller are described. The system comprises a radio-frequency (RF) receiver configured to receive an RF signal transmitted between the drone and a controller. The RF signal includes scrambled data that contain repetitions of unscrambled data based on known scramblers with an unknown scrambling seed. The system further comprises a memory device in communication with a hardware processor and having stored computer-executable instructions to cause the hardware processor to identify the smallest number of bits required in each segment of scrambled data for data combining by finding an invertible predetermined matrix. The hardware processor is configured to determine the unknown scrambling seed based on a function combining the predetermined matrix, transition matrices of scramblers, and segments of received scrambled data.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, obtain predetermined data of expected communication protocols used between the drone and a controller, and determine whether the RF signal corresponds to one of the expected communication protocols by comparing the samples of the RF signal to the predetermined data and decoding the RF signal. In further aspects the system extracts a unique identifier of the drone based at least partially on the decoded RF signal.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a one or more drones includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, the set of samples comprising samples of the first RF signal, obtain a parameter model of the first frequency hopping parameters, and fit the parameter model to the set of samples.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The RF signal includes a synchronization signal for synchronization of the RF signal. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a sequence of samples from the RF receiver, obtain a double differential of the received sequence of samples, calculate a running sum of a defined number of the double differential of the received sequence of samples, and detect the presence of the drone based on the running sum.

Abstract: A system and method for detecting a scrambling seed in communication between a drone and a controller are described. The system comprises a radio-frequency (RF) receiver configured to receive an RF signal transmitted between the drone and a controller. The RF signal includes scrambled data that contain repetitions of unscrambled data based on known scramblers with an unknown scrambling seed. The system further comprises a memory device in communication with a hardware processor and having stored computer-executable instructions to cause the hardware processor to identify the smallest number of bits required in each segment of scrambled data for data combining by finding an invertible predetermined matrix. The hardware processor is configured to determine the unknown scrambling seed based on a function combining the predetermined matrix, transition matrices of scramblers, and segments of received scrambled data.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a one or more drones includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, the set of samples comprising samples of the first RF signal, obtain a parameter model of the first frequency hopping parameters, and fit the parameter model to the set of samples.

Abstract: A system and method for detecting a scrambling seed in communication between a drone and a controller are described. The system comprises a radio-frequency (RF) receiver configured to receive an RF signal transmitted between the drone and a controller. The RF signal includes scrambled data that contain repetitions of unscrambled data based on known scramblers with an unknown scrambling seed. The system further comprises a memory device in communication with a hardware processor and having stored computer-executable instructions to cause the hardware processor to identify the smallest number of bits required in each segment of scrambled data for data combining by finding an invertible predetermined matrix. The hardware processor is configured to determine the unknown scrambling seed based on a function combining the predetermined matrix, transition matrices of scramblers, and segments of received scrambled data.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, obtain predetermined data of expected communication protocols used between the drone and a controller, and determine whether the RF signal corresponds to one of the expected communication protocols by comparing the samples of the RF signal to the predetermined data and decoding the RF signal. In further aspects the system extracts a unique identifier of the drone based at least partially on the decoded RF signal.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a one or more drones includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, the set of samples comprising samples of the first RF signal, obtain a parameter model of the first frequency hopping parameters, and fit the parameter model to the set of samples.

Abstract: A system and method for detecting a scrambling seed in communication between a drone and a controller are described. The system comprises a radio-frequency (RF) receiver configured to receive an RF signal transmitted between the drone and a controller. The RF signal includes scrambled data that contain repetitions of unscrambled data based on known scramblers with an unknown scrambling seed. The system further comprises a memory device in communication with a hardware processor and having stored computer-executable instructions to cause the hardware processor to identify the smallest number of bits required in each segment of scrambled data for data combining by finding an invertible predetermined matrix. The hardware processor is configured to determine the unknown scrambling seed based on a function combining the predetermined matrix, transition matrices of scramblers, and segments of received scrambled data.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a one or more drones includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a set of samples from the RF receiver for a time interval, the set of samples comprising samples of the first RF signal, obtain a parameter model of the first frequency hopping parameters, and fit the parameter model to the set of samples.

Abstract: Systems and methods for detecting, monitoring, and mitigating the presence of a drone are provided herein. In one aspect, a system for detecting presence of a drone includes a radio-frequency (RF) receiver configured to receive an RF signal transmitted between a drone and a controller. The RF signal includes a synchronization signal for synchronization of the RF signal. The system can further include a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the at least one processor to receive a sequence of samples from the RF receiver, obtain a double differential of the received sequence of samples, calculate a running sum of a defined number of the double differential of the received sequence of samples, and detect the presence of the drone based on the running sum.