In an embodiment, a method monitors, within a global navigation satellite system (GNSS) limited zone, an intra-zone location of a vehicle having a GNSS receiver, the intra-zone location being within the limited zone. The method determines a simulated intra-zone location of the vehicle based on the intra-zone location monitored to calculate a likely location of the vehicle. The method calculates a global location of the vehicle based on the intra-zone location and the location of the GNSS limited zone within a global network of limited zones. The method broadcasts, from a transmitter within the GNSS limited zone, a GNSS signal representing the global location of the vehicle.

In an embodiment, a method monitors, within a global navigation satellite system (GNSS) limited zone, an intra-zone location of a vehicle having a GNSS receiver, the intra-zone location being within the limited zone. The method determines a simulated intra-zone location of the vehicle based on the intra-zone location monitored to calculate a likely location of the vehicle. The method calculates a global location of the vehicle based on the intra-zone location and the location of the GNSS limited zone within a global network of limited zones. The method broadcasts, from a transmitter within the GNSS limited zone, a GNSS signal representing the global location of the vehicle.

A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

An apparatus for matching probe measurements to a path in a geographic location includes a receiver, a window manager, a location generator, a path calculator, and an output. The receiver is configured to receive a stream of probe measurements. The window manager is configured to fill a window with the measurements, to select an additional measurement from the stream, and to select an oldest measurement in the window. The location generator is configured to generate candidate locations for the measurements in the window and the additional measurement. The path calculator is configured to match the oldest measurement to a candidate location. The output is configured to output a path-matched probe measurement based on the oldest measurement and the candidate location matched to the oldest measurement.

An apparatus for matching probe measurements to a path in a geographic location includes a receiver, a window manager, a location generator, a path calculator, and an output. The receiver is configured to receive a stream of probe measurements. The window manager is configured to fill a window with the measurements, to select an additional measurement from the stream, and to select an oldest measurement in the window. The location generator is configured to generate candidate locations for the measurements in the window and the additional measurement. The path calculator is configured to match the oldest measurement to a candidate location. The output is configured to output a path-matched probe measurement based on the oldest measurement and the candidate location matched to the oldest measurement.

Disclosed herein are methods, devices, and systems for determining geographic location and time. In one embodiment, a radio and a processor configured for deriving a first signal tone originating from a first remote antenna located at a first location; deriving a second signal tone originating from a second remote antenna located at a second location; deriving a third signal tone originating from a third remote antenna located at a third location; determining a first frequency and a first phase at a first time of the first signal tone; determining a second frequency and a second phase at a second time of the second signal tone; and determining a third frequency and a third phase at a third time of the third signal tone. The method further includes determining a geographic location based on the first, second, and third frequencies; the first, second, and third phases; and the first, second, and third locations.

Disclosed herein are methods, devices, and systems for determining geographic location and time. In one embodiment, a radio and a processor configured for deriving a first signal tone originating from a first remote antenna located at a first location; deriving a second signal tone originating from a second remote antenna located at a second location; deriving a third signal tone originating from a third remote antenna located at a third location; determining a first frequency and a first phase at a first time of the first signal tone; determining a second frequency and a second phase at a second time of the second signal tone; and determining a third frequency and a third phase at a third time of the third signal tone. The method further includes determining a geographic location based on the first, second, and third frequencies; the first, second, and third phases; and the first, second, and third locations.

A system and method for detection of an aerial drone in an environment includes a baseline of geo-mapped sensor data in a temporal and location indexed database formed by (i) using at least one sensor to receive signals from the environment and converting into digital signals for further processing; (ii) deriving time delays, object signatures, Doppler shifts, reflectivity, and/or optical characteristics from the received signals; (iii) geo-mapping the environment using GNSS and the sensor data; and (iv) logging sensor data over a time interval, for example 24 hours to 7 days. Live sensor data can be then be monitored and signature data can be derived by computing at least one parameter such as direction and signal strength. The live data is continuously or periodically compared to the baseline data to identify a variance, if any, which may be indicative of a detection event.

A system and method for detection of an aerial drone in an environment includes a baseline of geo-mapped sensor data in a temporal and location indexed database formed by (i) using at least one sensor to receive signals from the environment and converting into digital signals for further processing; (ii) deriving time delays, object signatures, Doppler shifts, reflectivity, and/or optical characteristics from the received signals; (iii) geo-mapping the environment using GNSS and the sensor data; and (iv) logging sensor data over a time interval, for example 24 hours to 7 days. Live sensor data can be then be monitored and signature data can be derived by computing at least one parameter such as direction and signal strength. The live data is continuously or periodically compared to the baseline data to identify a variance, if any, which may be indicative of a detection event.

Disclosed are methods, systems, and non-transitory computer-readable medium for distributed vehicle processing. For instance, the method may include: in response to determining a first trigger condition of a first set of trigger conditions is satisfied, performing a first process corresponding to the first trigger condition on-board a vehicle; in response to determining a second trigger condition of a second set of trigger conditions is satisfied, prompting a second process corresponding to the second trigger condition by transmitting an edge request to an edge node and receiving an edge response from the edge node; and in response to determining a third trigger condition of a third set of trigger conditions is satisfied, prompting a third process corresponding to the third trigger condition by transmitting a cloud request to a cloud node and receiving a cloud response from the cloud node.