10985results about "Position fixation" patented technology

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.

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.

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.

Sidelink positioning may be accomplished by a wireless transmit / receive unit (WTRU). The WTRU may be configured to transmit a first message comprising sidelink positioning information associated with a group of WTRUs. The sidelink positioning information may comprise an indication of a sidelink positioning method for determining positions of the WTRUs in the group of WTRUs. The WTRU may be configured to transmit a second message comprising a request for sidelink positioning reference signal (SL-PRS) resources for the group of WTRUs. The WTRU may be configured to receive an indication of allocated SL-PRS resources for the group of WTRUs. The WTRU may be configured to send an indication of the allocated SL-PRS resources to the group of WTRUs.

The invention discloses a rescue method and system of a rescue robot for exploration, and relates to the technical field of underground space rescue, and the method comprises the following steps: obtaining multi-path acoustic echo data of a karst cave and motion track data of the robot, and constructing a three-dimensional point cloud model according to the multi-path acoustic echo data and the motion track data of the robot; and identifying unmatched data in the multi-path acoustic echo data and the robot motion trail data, and taking an area where the unmatched data is located as an abnormal area. According to the method, the spatial resolution of signal acquisition is enhanced through the multi-microphone array, robust acoustic fingerprints are extracted in combination with a noise reduction algorithm and short-time Fourier transform, high-confidence human body sound source signals are screened out by using a feature template matching mechanism, accurate extraction and recognition of human body acoustic features in a karst cave complex noise environment are realized, and the accuracy of human body acoustic feature recognition is improved. The problem of misjudgment caused by confusion of sound source features and environmental noise in a traditional method is effectively solved.

The present invention relates to a warning system and in particular to a warning system that is movable to a monitoring zone. The invention has been developed primarily for use for early notification of danger by approaching vehicles to a monitored zone such as an emergency in an emergency lane of a roadway. The warning system of the invention comprises at least two forms of detectors for detecting and tracking vehicles and obtaining characteristics of the tracked vehicle relative to the monitored zone a determinator for receiving the characteristics of the tracked vehicle relative to the monitored zone and assessing the expected relative impact of the vehicle on the monitored zone and an alarm system for providing an alarm action according to a predetermined danger of the assessed expected relative impact of the vehicle to the monitored zone.

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.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to transmit wirelessly and encrypted signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), wherein the stationary unit (20) comprises a control device (22) which is designed to determine a respective position (51 - 57) of the mobile unit (10) relative to the stationary unit (20) from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) at predetermined time intervals, to determine a movement path (50) of the mobile unit (10) from the chronologically successively determined positions (51 - 57) of the mobile unit (10) and to determine from the movement path (50) and a predetermined target position a probability with which a function is to be triggered when the mobile unit (10) approaches the target position, wherein the control device (22) is further configured to compare the probability with a predetermined threshold value and to trigger the function if the probability exceeds the threshold value.

The invention relates to a substation operation risk identification method based on a multi-view video and high-precision positioning. Acquiring video data of a working site through a plurality of cameras with fixed visual angles and mobile video acquisition equipment; a high-precision positioning system is used for obtaining three-dimensional space coordinates of operators and equipment in real time; establishing a three-dimensional digital twinborn model of the substation equipment, and performing dynamic scene reconstruction based on the multi-view video stream to generate a real-time three-dimensional scene of the operation site; fusing the positioning data and the three-dimensional scene by adopting a space-time fusion algorithm to generate a dynamic digital portrait of the operator; and carrying out real-time analysis on behaviors and positions of operators by using a risk assessment algorithm based on a preset risk rule, calculating to obtain a risk assessment value, and setting a feedback mechanism to continuously optimize positioning and scene reconstruction precision. According to the invention, efficient, accurate and real-time identification and early warning of the operation risk of the transformer substation are realized, and the safety management level of an operation site is effectively improved.

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.

The invention relates to the technical field of electric power operation, and discloses a power plant employee violation intelligent identification method and system based on an AI large model, and the system comprises a visual collection module, an edge calculation node, a personnel positioning and tracking module, a three-dimensional scene reconstruction module, a multi-modal analysis module, a grading early warning module, a self-adaptive adjustment module, and an inspection robot. According to the invention, accurate identification of personnel behaviors in a complex industrial environment is realized, the problems of high false alarm rate, response lag and the like of a traditional monitoring system are effectively solved through a specially designed self-adaptive adjustment mechanism and a grading early warning strategy, and the technical scheme has the advantages that through innovative integration of technologies of machine vision, edge calculation, multi-modal analysis and the like, the safety of the system is improved. An intelligent safety management and control system with an autonomous optimization capability is constructed, and breakthrough progress is made in core indexes such as identification precision, response speed, resource utilization efficiency and the like.

The invention discloses a multi-unmanned aerial vehicle cluster cooperative positioning method based on multi-sensor fusion, and the method comprises the following steps: S1, collecting and processing the multi-sensor data of unmanned aerial vehicles, compensating VIO accumulated drift through fusing ultra-wideband ranging information, guaranteeing the time-space consistency of the multi-sensor data through employing a layered time synchronization strategy, and carrying out the collection and processing of the multi-sensor data of the unmanned aerial vehicles; suppressing multipath interference of the UWB signal and eliminating an NLOS error by using adaptive Kalman filtering, and obtaining initial positioning data of the unmanned aerial vehicle; s2, acquiring key frames of multiple unmanned aerial vehicles based on a window sampling method, and performing key frame optimization and outlier processing to balance noise suppression and real-time performance; and S3, constructing a factor graph model of the key frame data based on a graph optimization theory, and obtaining optimized cluster position information by solving a nonlinear least square optimization problem. The method effectively improves the accuracy and stability of multi-unmanned aerial vehicle cluster cooperative positioning, and can be applied to the fields of unmanned aerial vehicle logistics distribution, environment monitoring and the like.

The invention relates to the technical field of TDOA (time difference of arrival) positioning, and provides an ultrasonic three-dimensional positioning method based on beam enhancement and TDOA, which comprises the following steps: extracting initial space parameters based on beam scanning of an array receiving signal, carrying out iterative optimization on beam weight to adjust a direct wave component and suppress reflection interference, constructing a closed-loop optimization mechanism, and carrying out beam enhancement and TDOA positioning. Calculating an enhanced signal and an array element reliability measurement index through frequency domain segmentation and energy normalization; forming an optimization array based on the array element reliability measurement index, extracting a time delay parameter from the optimization array, constructing a distance measurement equation set, and calculating an initial estimation value of a target position by adopting a weighted optimization algorithm; and constructing a residual error model, constructing an optimized weight matrix by combining an array element reliability measurement index and a signal quality index, iteratively calculating a target coordinate until a convergence condition is met, and outputting a final three-dimensional coordinate. According to the method, the comprehensive performance of ultrasonic three-dimensional positioning in the aspects of anti-interference performance, stability and positioning precision in a complex environment is improved, and error source control is realized.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to transmit wirelessly and encrypted signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), wherein the stationary unit (20) comprises a control device (22) which is designed to determine a position of the mobile unit (10) relative to the stationary unit (20) from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) and to control a function if a control command for triggering the function is transmitted to the stationary unit (20) by a mobile unit (10) authenticated and authorized by the stationary unit (20) and / or the position of the mobile unit (10) is within a predetermined access area (30), and wherein the control device (22) is designed to determine an angle (ϕ) from which the signals (S) were received from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21), to determine a measured distance (rg) between the stationary transceiver (21) and the mobile transceiver (11) from a signal (S) received at the stationary transceiver (21) from the mobile transceiver (11) and from the measured distance (rg) and a vertical distance (rv) stored as a correction value in the control device (22) between the stationary transceiver (21) and the mobile transceiver (11), to determine a horizontal distance between the stationary transceiver (21) and the mobile transceiver (11) in the polar coordinate system lying in the horizontal plane as a distance (r) from which the signals (S) were received, so that the position of the mobile unit (10) can be specified as polar coordinates of a polar coordinate system lying in a horizontal plane, in whose coordinate origin the stationary transceiver (21) is arranged.

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.

The invention relates to a microphone array sound source positioning method and system based on cross-correlation-beam forming closed-loop optimization, and belongs to the technical field of sound source positioning. The method comprises the following steps: collecting multichannel sound signals through a microphone array and preprocessing the multichannel sound signals to extract time-frequency features and suppress noise interference; time delay information among the microphones is estimated by adopting a generalized cross-correlation phase transformation algorithm, and an optimization strategy is introduced to improve estimation stability and anti-interference performance; enhancing the target sound source signal in combination with a minimum variance undistorted response beam forming algorithm and an adaptive Kalman filtering mechanism; constructing a closed-loop feedback optimization mechanism based on the beam output signal to realize feedback adjustment; and adopting a hybrid network architecture, taking the beam output signal amplitude spectrum as input, and outputting the frequency spectrum or mask of the obtained target sound source signal. The method has the advantages of high calculation efficiency, high positioning precision and strong anti-interference capability, and is suitable for real-time acoustic signal processing in a complex environment.

Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) receives configuration information for a two-part positioning reference signal (PRS) transmitted by a transmission point, wherein the two-part PRS comprises a first part PRS and a second part PRS separated by a time gap, attempts to detect the first part PRS based on the configuration information, and obtains a positioning measurement of the second part PRS based on detection of the first part PRS and the configuration information.

The invention relates to a multi-element microphone array sound source localization method based on multistage signal preprocessing and subspace spectrum optimization, and belongs to the technical field of acoustic detection. Aiming at the problems of poor noise immunity, weak multi-sound-source resolution capability and low calculation efficiency of the existing sound source positioning technology, a triple signal preprocessing and subspace collaborative optimization scheme is provided; firstly, incoherent noise is suppressed through phase coherent filtering, a signal is reconstructed through principal component analysis, and phase deviation is calibrated through fundamental frequency; then constructing a guiding matrix and decomposing a noise subspace, and extracting a coarse positioning result; and finally, high-precision angle optimization is realized based on a chaos initialization differential evolution algorithm, and the efficiency is improved by combining a dynamic search range and an early stop mechanism. According to the method, the anti-interference capability in a low signal-to-noise ratio environment is remarkably enhanced, the problems of missing detection and false detection during dense distribution of multiple sound sources are effectively solved, meanwhile, the positioning precision and the real-time performance are considered, and the method is suitable for acoustic fault detection of complex scenes such as power transmission line inspection.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to transmit wirelessly and encrypted signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), wherein the stationary unit (20) comprises a control device (22) which is designed to determine a distance (r) and an angle (Φ) as a position of the mobile unit (10) relative to the stationary unit (20) from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21), so that the position of the mobile unit (10) can be specified as polar coordinates of a polar coordinate system lying in a horizontal plane, in whose coordinate origin the stationary transceiver (21) is arranged, and to control a function when a control command for triggering the function is transmitted to the stationary unit (20) by a mobile unit (10) authenticated and authorized by the stationary unit (20) and / or the position of the mobile unit (10) is within a predetermined access area (30), and wherein the control device (22) has a learning mode in which the control device (22) is designed to determine a respective position of the mobile unit (10) and to store it as a position assigned to an object, initiated by a respective learning control command.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to wirelessly and encryptedly transmit signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), which has a first antenna array (23A) and a second antenna array (23B), wherein the stationary unit (20) comprises a control device (22) which is designed to determine from a signal (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) and at least partially received by the first antenna array (23A) two positions (P10, P11) of the mobile unit (10) relative to the stationary unit (20), of which a first is an actual position (P10) and a second is a first mirrored position (P11), and to determine from the signal (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) and at least partially received by the second antenna array (23B) two positions (P10, P12) of the mobile unit (10) relative to the stationary unit (20), of which a first is an actual position (P10) and a second is a second mirrored position (P12), and wherein the control device (22) is designed to compare the two positions (P10, P11) determined by means of the first antenna array (23A) with the two positions (P10, P12) determined by means of the second antenna array (23B) and to verify the matching position as the actual position (P10).

An underwater acoustic sensor network node positioning error correction method combined with acoustic velocity inversion, which method relates to the technical field of acoustic velocity inversion. The method comprises: deploying an acoustic source point and underwater acoustic sensor nodes which are at fixed positions, the underwater acoustic sensor nodes collecting acoustic velocity data sent by means of the acoustic source point, and by means of acoustic velocity data at different underwater acoustic sensor nodes, using an acoustic velocity field inversion algorithm to construct an acoustic velocity field model; collecting real-time acoustic velocity data at the different underwater acoustic sensor nodes, and obtaining acoustic velocity characteristic information at the different underwater acoustic sensor nodes and water characteristic information at the different underwater acoustic sensor nodes; performing comprehensive analysis on the acoustic velocity characteristic information and the water characteristic information, and evaluating the positioning accuracy of the acoustic velocity field model in respect of the underwater acoustic sensor nodes; and comparing quantized positioning accuracy results for the underwater acoustic sensor nodes with a preset threshold, and when there is a relatively large error in the positioning accuracy, generating an error signal. The method is conducive to improving the precision of underwater acoustic wave propagation and the accuracy of underwater acoustic sensor network node positioning, and evaluating the positioning accuracy of an acoustic velocity field model in respect of underwater acoustic sensor nodes.

The invention discloses an immersed tunnel leakage voiceprint recognition system based on deep learning. The system comprises an acoustic signal acquisition module, a signal preprocessing module, a voiceprint feature extraction module, a deep learning recognition module and a leakage positioning and early warning module. According to the invention, the leakage water flow sound and the structural damage elastic wave signal of the immersed tunnel are comprehensively considered, the multi-dimensional voiceprint feature extraction and deep learning model are fused, and the adaptive signal noise reduction and sound source positioning technology is combined, so that the high-precision monitoring and real-time early warning of the leakage of the immersed tunnel are realized; the accuracy and real-time performance of immersed tunnel leakage nondestructive monitoring are improved, and powerful support is provided for follow-up risk prediction and early repair.

The invention discloses an unmanned aerial vehicle detection method based on multi-band radio spectrum analysis, and the method can recognize the flight control behaviors of a target, such as hovering, cruising or hovering, through the extraction of a signal track and the introduction of a behavior modeling mechanism, and effectively overcomes the defect that the prior art lacks the dynamic behavior analysis capability. A multi-node synchronization mechanism and a TDOA positioning method are combined, so that high-precision traceability of a target space position is realized; meanwhile, risk level assessment is carried out based on signal features, a track mode and a space region, so that the system has intelligent early warning capability. According to the whole scheme, a full-link unmanned aerial vehicle detection method from multi-frequency receiving, frequency spectrum identification, behavior judgment, target positioning to risk output is constructed, and the problems of single frequency band, rough identification means, lack of tracking and evaluation capability and the like in the prior art are effectively solved; and the practicability and the accuracy of the unmanned aerial vehicle detection system in a complex airspace environment are remarkably improved.

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.

The invention discloses a sound acquisition and processing system based on cooperation of multiple microphone arrays. The system comprises a sound acquisition module, a multi-channel signal preprocessing module, a sound signal feature extraction module, an abnormal sound recognition module, a sound source positioning module and an alarm module. A multi-channel mixed data signal is collected through a circularly-arranged multi-microphone array formed by a plurality of microphones, after echo cancellation, wave beam domain noise reduction and multi-sound-source separation, a single-sound-source feature vector is extracted, according to the single-sound-source feature vector, abnormal sound including explosion, screaming or glass breakage is recognized through a BiLSTM and an attention mechanism model, and the abnormal sound is recognized through an attention mechanism model. And the GCC-PHAT and MDS-MUSIC algorithms are combined to position abnormal sound production, and alarm information is generated. According to the invention, accurate identification, positioning and alarm of the abnormal sound can be realized, and the real-time performance, the accuracy and the multi-target processing capability of abnormal sound monitoring in a complex environment can be obviously improved.

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.