19867results about "Position fixation" patented technology

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems, methods, and apparatus are provided for automated identification of open space in a wireless communications spectrum, by identifying sources of signal emission in the spectrum by automatically detecting signals, analyzing signals, comparing signal data to historical and reference data, creating corresponding signal profiles, and determining information about the open space based upon the measured and analyzed data in near real-time.

Systems and methods for automated unmanned aerial vehicle recognition. A multiplicity of receivers captures RF data and transmits the RF data to at least one node device. The at least one node device comprises a signal processing engine, a detection engine, a classification engine, and a direction finding engine. The at least one node device is configured with an artificial intelligence algorithm. The detection engine and classification engine are trained to detect and classify signals from unmanned vehicles and their controllers based on processed data from the signal processing engine. The direction finding engine is operable to provide lines of bearing for detected unmanned vehicles.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and / or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and / or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Systems and methods are described for transmitting broadcasts by Peripherals, receiving the broadcasts by Centrals, and communicating with a Backend by Centrals. Specifically, a Peripheral may generate and transmit an encrypted broadcast packet to a Central, the Central may transmit the encrypted observation information to the Backend, which may decrypt the broadcast packet. Additionally, a Central may transmit a request for authorization to connect to a Peripheral to the Backend. If authorized by the Backend, the Central may connect to the Peripheral. Further, a Central may receive a plurality of broadcasts over a period of time. The Central may store information about the broadcasts and, at the conclusion of the period of time, transmit the information about the broadcasts and the last-received broadcast to the Backend.

Systems and methods are described for determining a peripheral's location based on observations from a plurality of centrals. A central may periodically transmit its location and observations of peripherals to a backend. The backend may match the location of the central with one or more observations of a peripheral to estimate a location of the peripheral. The backend may receive observations of the same peripheral from a plurality of centrals. The backend may aggregate estimated locations to triangulate a more precise location of the peripheral.

Dynamic geofences may be generated and updated based on locations of related assets. For example, locations of a group of related assets, including a primary asset and one or more secondary assets, may be determined. A geofence associated with the primary asset may then be analyzed to identify any geofences of secondary assets that overlap. This process may be repeated for each overlapping geofence to identify additional overlap and expand or move a combined dynamic geofence. Environmental aspects such as time of day, weather conditions, and risk levels may be considered for dynamic geofence adjustments. The combined geofence and asset locations may be displayed on a user interface.

Enhanced ranging and positioning services in wireless networks The invention relates to a wireless system and methods for configuring ranging capable devices to form a ranging constellation to support ranging-based positioning services. Multiple challenges in improving location accuracy when using ranging measurements to derive the location coordinates are addressed. In particular, timing at which the location information can be derived from ranging measurements and methods used for ranging-based location estimation are described.

Systems, methods, and instrumentalities are described herein for supporting low power high accuracy positioning (LPHAP). A wireless transmit / receive unit (WTRU) may receive configuration information (e.g., in a radio resource control (RRC) reconfiguration message) from a first cell. The configuration information may indicate a first sounding reference for positioning (SRSp) configuration and a second SRSp configuration. The first SRSp configuration may be associated with a first positioning area and the second SRSp configuration may be associated with a second positioning area. The first positioning area may include a first cell ID set and the second positioning area may include a second cell ID set. The first SRSp configuration may be activated and the second SRSp configuration may be deactivated.

Systems, methods, and devices for collaborative positioning. A wireless transmit / receive unit (WTRU) is configured to perform and report positioning measurements including SL collaborative measurements. The WTRU serving as an anchor WTRU may select a set of member WTRUs for distributing the PRS measurement configurations based on the inter-WTRU distance measured over a SL. The selected subset of member WTRUs each provide measurement report to the anchor WTRU. The anchor WTRU reports to the LMF the measurements received from the member WTRUs and the associated SL distance measurements.

Methods, devices, and systems for machine learning (ML)-assisted position determination are disclosed. Information is received which indicates artificial intelligence / machine learning (AI / ML) models for determining position. Information is received which indicates transmission reference points (TRPs) (502, 504) associated with corners. Information is received which indicates a reference signal received power (RSRP). The TRPs associated with corners include a first TRP. It is determined that the WTRU is located in a corner based on an RSRP of a positioning reference signal (PRS) (506) received from the first TRP being above an RSRP threshold. Position information is determined based on an AI / ML position model and the determination that the WTRU is located in the corner. Information indicating the position of the WTRU is transmitted.

A method implemented in a wireless transmit / receive unit (WTRU) is provided. The method may include receiving configuration information indicating (i) a set of positioning reference signal (PRS) resources and (ii) a time window to be used for phase measurement with the set of PRS resources. The method may include determining a phase difference measurement based on a first PRS of a first plurality of PRS and a second PRS of a second plurality of PRS, the first and the second PRS being received in the time window. The method may include determining a reference signal time difference (RSTD) measurement based on the first PRS of the first plurality of PRS and a third PRS of the second plurality of PRS and transmitting reporting information indicating the determined phase difference measurement and the determined RSTD measurement.

Disclosed are systems, apparatuses, processes, and computer-readable media to determine a location of a device using carrier phase positioning. A process includes transmitting, at the device to a network entity, a phase measurement capability of a device (e.g., a user equipment (UE)) for subcarrier set pairs of different resources received by the device. The different resources are associated with a reference signal. The process can include receiving, at the device, a phase measurement request from a network entity for configuring phase measurements of the subcarrier set pairs of the different resources. The process can include transmitting a phase measurement report to the network entity based on the phase measurement request, the phase measurement report including information associated with a measured phase difference of at least one subcarrier set pair associated with the different resources.

A user equipment of a wireless communication system according to an embodiment is provided. The user equipment is configured to determine and / or to receive information on an applicability of a machine-learning model. And / or, the user equipment is configured to determine and / or to receive information that the user equipment is located in a machine-learning assisted area.

The invention relates to a wireless system and methods for managing and / or configuring ranging capable devices to form a ranging constellation to support ranging-based positioning services. Multiple challenges in improving configuration and management of the ranging constellation are described.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A wireless transmit / receive unit, WTRU, receives a positioning request message from another WTRU (1402). The positioning request message indicates a request associated with one or more of a sidelink positioning reference signals, SL-PRS, transmission or a SL-PRS reception and indicates a range of one or more parameters associated with the SL-PRS transmission or reception; these parameters comprise one or more of SL-RSRP, angle of departure AoD, angle of arrival AoA, and a line of sight LOS / NLOS metric. The WTRU measures the one or more parameters indicated in the positioning request message (1404) and performs the SL-PRS transmission (1410) or the SL-PRS reception (1410) on the condition that the measured parameters are within the range indicated in the positioning request message (1408).

An object tracking device, such as may be attached to a trailer to track movements of the trailer, may have various communication capabilities, such as cellular / LTE, Wi-Fi and GPS, which each have varying power requirements. A power optimization routine determines which communications should be performed to conserve battery while also providing frequent location updates. The routine determines if another plugged in tracking device is within low power Bluetooth (BLE) range and, if so, communications location via that device. If not, a Wi-Fi scan is performed and a lookup table is consulted for the corresponding location of any identified Wi-Fi access points. If location data cannot be found for an identified Wi-Fi access point, GPS location of the device is determined and the lookup table is updated to include the GPS location of the Wi-Fi access point.

Systems and methods are described for transmitting broadcasts by Peripherals, receiving the broadcasts by Centrals, and communicating with a Backend by Centrals. Specifically, a Peripheral may generate and transmit an encrypted broadcast packet to a Central, the Central may transmit the encrypted observation information to the Backend, which may decrypt the broadcast packet. Additionally, a Central may transmit a request for authorization to connect to a Peripheral to the Backend. If authorized by the Backend, the Central may connect to the Peripheral. Further, a Central may receive a plurality of broadcasts over a period of time. The Central may store information about the broadcasts and, at the conclusion of the period of time, transmit the information about the broadcasts and the last-received broadcast to the Backend.

The invention relates to the technical field of unmanned aerial vehicle detection, in particular to a monitoring and early warning system and method for countering unmanned aerial vehicle detection interference, and in the monitoring and early warning system, a signal receiving module independently receives electric signals of multiple unmanned aerial vehicles through array space stations; the abnormal signal detection module performs feature extraction, and detects abnormal signals by using frequency feature change and a spectrum analysis technology; the time difference of arrival detection module calculates the time difference of arrival of each space station to the abnormal signal, and the angle of arrival detection module analyzes and determines the angle of arrival through a space covariance matrix; the cross positioning module synthesizes the time difference and the angle information to determine the position of the abnormal unmanned aerial vehicle; and the adaptive interference suppression module identifies the type of an abnormal unmanned aerial vehicle by using a feature extraction result and a machine learning model, selects a suppression strategy, controls an array space station to align to the position of the abnormal unmanned aerial vehicle, realizes efficient suppression, and protects normal operation of a legal unmanned aerial vehicle and other aerial equipment at the same time.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.