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.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Drone tracking sensors; Computer software for drone tracking systems. Providing an on-line network environment that features technology that enables customers to access drone tracking data.
3.
SYSTEMS AND METHODS FOR ESTIMATING OFFSET OF SYNCHRONOUS SCRAMBLERS
Systems and methos for estimating offset of synchronous scramblers are provided. In one aspect, a method of estimating an initial state of a synchronous scrambler in the presence of a linear error control code includes receiving a vector including a transmit bit vector encoded using the linear error control code, and performing nulling on the linear error control code to null impact of the linear error control code from the received vector. The method also includes obtaining a system of equations from the received vector in response to performing the nulling on the linear error control code, and using a min-sum procedure to recover the initial state of the synchronous scrambler from the system of equations.
Systems and methos for estimating offset of synchronous scramblers are provided. In one aspect, a method of estimating an initial state of a synchronous scrambler in the presence of a linear error control code includes receiving a vector including a transmit bit vector encoded using the linear error control code, and performing nulling on the linear error control code to null impact of the linear error control code from the received vector. The method also includes obtaining a system of equations from the received vector in response to performing the nulling on the linear error control code, and using a min-sum procedure to recover the initial state of the synchronous scrambler from the system of equations.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Drone tracking sensors; Recorded computer software for tracking drones Providing a web site featuring technology that enables users to access drone tracking data
6.
SYSTEMS AND METHODS FOR DRONE MONITORING, DATA ANALYTICS, AND MITIGATION CLOUD SERVICES USING EDGE COMPUTING
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.
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.
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.
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.
H04B 1/7136 - Dispositions pour la production de sauts de fréquences, p. ex. utilisant une batterie de sources de fréquence, un accord continu ou une transformée
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
H04B 1/7143 - Dispositions pour la production de séquences de sauts
H04B 1/7156 - Dispositions pour la synchronisation des séquences
B64U 101/20 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’utilisation en tant que relais de communication, p. ex. plates-formes de haute altitude
11.
Systems and methods for detecting a scrambling seed in communication with an unmanned aircraft system
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.
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.
H04B 1/7136 - Dispositions pour la production de sauts de fréquences, p. ex. utilisant une batterie de sources de fréquence, un accord continu ou une transformée
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
H04B 1/7143 - Dispositions pour la production de séquences de sauts
H04B 1/7156 - Dispositions pour la synchronisation des séquences
13.
SYSTEMS AND METHODS FOR DETECTING, MONITORING, AND MITIGATING THE PRESENCE OF UNAUTHORIZED DRONES
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.
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.
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.
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.
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.
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.
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.
G01S 1/02 - Radiophares ou systèmes de balisage émettant des signaux ayant une ou des caractéristiques pouvant être détectées par des récepteurs non directionnels et définissant des directions, situations ou lignes de position déterminées par rapport aux émetteurs de radiophareRécepteurs travaillant avec ces systèmes utilisant les ondes radioélectriques
H04K 3/00 - Brouillage de la communicationContre-mesures
20.
Systems and methods for detecting, monitoring, and mitigating the presence of a drone using frequency hopping
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.
H04B 1/7136 - Dispositions pour la production de sauts de fréquences, p. ex. utilisant une batterie de sources de fréquence, un accord continu ou une transformée
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
H04B 1/7143 - Dispositions pour la production de séquences de sauts
H04B 1/7156 - Dispositions pour la synchronisation des séquences
21.
SYSTEMS AND METHODS FOR DETECTING, MONITORING, AND MITIGATING THE PRESENCE OF A DRONE USING FREQUENCY HOPPING
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.
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.
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.
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.
09 - Appareils et instruments scientifiques et électriques
Produits et services
Electronic control systems for drones; aeronautical radio
communication machines and apparatus for securing airspace
from drones; computer software for a drone tracking and
mitigation system.
09 - Appareils et instruments scientifiques et électriques
Produits et services
Electronic control systems for drones; aeronautical radio communication machines and apparatus for securing airspace from drones; computer software for a drone tracking and mitigation system
