524 results about "Wireless positioning" patented technology

The invention relates to the technical field of space behavior analysis, and discloses a user consumption behavior analysis method and system for different scenes in a commercial space, and the method comprises the steps: obtaining user behavior data through a wireless positioning device and a distributed environment sensor; performing space-time alignment on the multi-source heterogeneous data, and fusing commodity granularity data of a transaction system to construct a three-dimensional trajectory model; based on the three-dimensional track model, identifying residence characteristics and a moving mode of the user, and associating commodity distribution to generate a dynamic thermodynamic diagram; adjusting a guidance strategy and environmental parameters according to the density gradient of the thermodynamic diagram and the user attribute hierarchy; the payment feature data and the user behavior data are integrated to update the user tag, and a cross-regional association strategy is generated, the comprehensive, flexible and efficient commercial space user consumption behavior analysis method is provided, the problem that in the prior art, dynamic user behaviors are understood insufficiently is solved, and therefore the commercial intelligence process is promoted.

The invention discloses a target positioning method and system based on a single reference station, and relates to the field of wireless positioning, and the method comprises the steps: generating vortex electromagnetic waves carrying orbital angular momentum based on a transmitting end of a reference station, and generating a time-varying phase modulation transmitting signal and a metasurface time-varying coding sequence through a programmable metasurface; a time-varying phase modulation emission signal forms a multipath superposition effect in a propagation environment, a receiving end obtains a mixed signal of a direct wave and a reflected wave, and the receiving end carries out OAM mode separation on the mixed signal of the direct wave and the reflected wave through a spiral phase plate and an annular array to obtain signal components in different modes; and based on the signal component and the metasurface time-varying coding sequence, reconstructing an equivalent virtual array response by adopting a compressed sensing algorithm. According to the invention, the orbital angular momentum modal separation technology and the metasurface dynamic coding technology are creatively fused, and high-precision real-time direction finding in a complex multi-path environment is realized under a single base station architecture.

The invention discloses a broadcast type radio positioning system base station site selection analysis and evaluation method and system, and relates to the technical field of wireless positioning, and the method comprises the steps: building a radio ground base station deployment sample database and an elevation model database; based on a combined optimization strategy of a greedy algorithm and a genetic algorithm, selecting an optimal base station set covering a pre-working area from the database; constructing a three-dimensional evaluation system, and comprehensively evaluating the optimal base station set from three dimensions of deployment cost, system robustness and positioning precision; optimizing the base station set based on a digital twinning technology, wherein the optimization comprises multi-band signal emission modeling and machine learning recommendation of a historical case library; and dynamic presentation and parameter adjustment of a base station deployment effect are realized through a three-dimensional visual interface and an interactive sand table system. According to the method, a large-range working area can be well covered, the situation that a signal coverage blind area exists is avoided, then the working efficiency is improved, and flexible and efficient site selection evaluation on the radio ground base station in a local sudden battlefield can be achieved.

Disclosed are techniques for wireless positioning. In an aspect, a network entity may determine that a positioning reference signal (PRS) processing load for a UE exceeds a PRS processing capacity of the UE. The network entity may send, to the UE, assistance data that reduces the PRS processing load for the UE. In another aspect, a user equipment (UE) may determine, based on information received from a network entity, that one or more PRS measurements is associated with a low-latency location request. The UE may modify one or more parameters associated with the one or more PRS measurements to reduce measurement latency. The UE may perform the one or more PRS measurements associated with the low-latency location request according to the modified one or more parameters.

Disclosed are techniques for wireless positioning. In an aspect, a user equipment (UE) may determine a sidelink measurement gap for positioning (SL-MGP). The UE may perform sidelink positioning during the SL-MGP, wherein performing SL positioning comprises transmitting or receiving at least one sidelink positioning reference signal (SL-PRS). In another aspect, a network entity, such as a base station or a location server, may receive, from a UE, first information indicating SL-PRS processing capability of the UE. The network entity may determine a SL-MGP based at least in part on the first information. The network entity may send, to the UE, second information indicating the SL-MGP.

The invention relates to the cross technical field of satellite navigation and wireless positioning technology, in particular to a real-time dynamic high-precision positioning method based on Beidou and UWB tight coupling, which solves the problem that in the prior art, error coupling in Beidou and UWB observation data is not fully solved, and especially in a high-speed dynamic scene, the positioning accuracy is greatly improved. The mutual influence of the Beidou receiver clock error, the UWB base station clock error and the multi-path error causes the continuous accumulation of the error and the significant reduction of the positioning precision. The invention discloses a real-time dynamic high-precision positioning method based on Beidou and UWB tight coupling. A data preprocessing and space-time alignment module, an error joint estimation model, an ambiguity fast fixing algorithm, a geometric constraint enhanced positioning engine module and a dynamic coordinate conversion and fusion output module are included. According to the mode provided by the invention, a highly integrated multi-model Kalman filtering architecture is adopted, so that synchronous and accurate compensation of the clock error of the Beidou receiver, the time delay of the UWB base station and the multi-path effect is realized.

The invention belongs to the technical field of wireless positioning, and discloses a non-line-of-sight interference-resistant dynamic positioning method and a base station layout method for positioning. Comprising the following steps: calculating original distance measurement results of each initial base station in a label and a sub-region, obtaining current shielding probability and current signal intensity of the initial base station and current geometric accuracy factors of different initial base station combinations in an initial base station set, selecting candidate base stations, calculating information gain of each candidate base station pair, and obtaining the information gain of each candidate base station pair; selecting candidate base stations with information gains meeting preset requirements to construct a target base station subset, inputting an original ranging result of the target base station subset into a Kalman filter based on a motion state space model for processing, and compensating an NLOS time delay error through a sliding window mean value to obtain a positioning result of a label and an NLOS time delay error estimation value, the problem that the positioning result is not accurate enough in a complex environment is solved.

Disclosed are techniques for wireless positioning. In an aspect, a user equipment (UE) receives, from a location server, assistance data for a positioning procedure, obtains a frequency offset measurement of one or more positioning reference signal (PRS) resources transmitted by at least one transmission-reception point (TRP) based on the assistance data, and enables a location of the UE to be determined based, at least in part, on the frequency offset measurement.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an intelligent aerial 3D printing and spraying system and method based on an unmanned aerial vehicle cluster, and the system comprises a spatial three-dimensional laser ranging scanning modeling module for generating a real-size scene model, a three-dimensional positioning network module, and a three-dimensional positioning network composed of a plurality of laser radar arrays. Wherein the laser radar or the wireless positioning beacon array is arranged on a working plane to construct a three-dimensional space coordinate reference system; the printing module is integrated on the unmanned aerial vehicle, compared with traditional high-altitude operation, the construction efficiency is improved, the constraint of tedious procedures such as scaffold building and manual high-altitude operation is thoroughly eliminated, the unmanned aerial vehicle cluster can be rapidly deployed in a short time, and operation tasks such as large-area single-color or full-color spraying, repairing, modeling and printing are efficiently completed with high precision; the project construction period is greatly shortened, the comprehensive construction cost is reduced, the safety construction level is improved, the engineering income is improved, and the construction accident risk is reduced.

The invention relates to the technical field of evacuation intelligent simulation, in particular to a fire-fighting evacuation path dynamic planning method and system based on digital twinning. In the fire-fighting evacuation path dynamic planning method and system based on digital twinning, a digital twinning environment containing multi-dimensional real-time sensing data such as temperature, smoke and heat radiation intensity is constructed; the method can dynamically analyze space-time evolution characteristics such as fire spreading trend and heat accumulation, further carries out accurate quantitative evaluation on the danger level of each segment of an evacuation path, and meanwhile, integrates video monitoring and wireless positioning information to grasp the specific positions and moving tracks of people in a building in real time, thereby improving the safety and reliability of the evacuation path. The actual flow bottleneck is identified based on the flow direction consistency, the distribution density and the congestion condition of the crowd, and finally, the dynamic danger of the fire environment and the macroscopic flow trend of the crowd are combined, and the passage cost value of each path section is subjected to dual dynamic correction, so that the flow rate of the crowd is improved. And an evacuation path planning result giving consideration to fire hazard avoidance and crowd congestion evacuation is generated, so that the real-time performance and safety of evacuation decision making are effectively improved.

The invention relates to the technical field of wireless positioning, and provides a high-speed rail user positioning method and system based on trajectory compensation, and the method comprises the steps: recognizing high-speed rail users, carrying out the data preprocessing, constructing high-speed rail grids, and generating a signal fingerprint database; preliminarily screening out a plurality of candidate grids according to RSRP and TA signal features reported by high-speed rail users in real time; based on the service cell switching sequence, a hidden Markov model or particle filtering is adopted for motion trail modeling, and the advancing direction and speed of a train are recognized; introducing a multi-source information fusion and grid compensation strategy; and selecting a final positioning result from the candidate grids in a weighted voting mode, and outputting grid IDs and latitude and longitude coordinates. Through multi-source data fusion, track compensation and intelligent decision making, the positioning precision and reliability of the high-speed rail user in a complex mobile environment are remarkably improved, and the method has important technical popularization value.

Device localization (e.g., ultra-wideband device localization) may be used to provide coordinated outputs and / or receive coordinated inputs using multiple devices. Providing coordinated outputs may include providing partial outputs using multiple devices, modifying an output of a device based on its position and / or orientation relative to another device, and the like. In some cases, each device of a set of multiple devices may provide a partial output, which combines with partial outputs of the remaining devices to produce a coordinated output.

The invention relates to the technical field of wireless positioning, in particular to an intelligent positioning analysis method and system for a safety tool, and the method comprises the steps: collecting the video data and voice data of a high-altitude operation site in real time through a video collection module worn by an operator; the method comprises the following steps: acquiring far-end high-altitude operation video data through a ground camera, and when the far-end high-altitude operation video data is lower than a preset value, acquiring three-dimensional position data of personnel in real time through a wireless positioning module; establishing a three-dimensional electronic fence model on the monitoring platform, and synchronizing the three-dimensional position data to the three-dimensional electronic fence model; when the monitoring platform detects that the three-dimensional position data exceed the three-dimensional electronic fence, early warning is triggered; after early warning is triggered, video data and voice data of the aerial work site in the corresponding time period are obtained, personnel posture information in the video data is analyzed, and abnormal types are recognized in combination with voice keywords. Therefore, personnel supplementary positioning under the condition of low visibility can be realized, and the reliability of the positioning monitoring system is improved.

The application provides an angle of arrival measurement method, an electronic device, a readable storage medium and a chip, and relates to the technical field of wireless positioning. The method is applied to an electronic device, and the electronic device comprises a first antenna and a second antenna. The antenna radiation field patterns of the first antenna and the second antenna are similar within a first angle range around the electronic device and are not similar within a second angle range around the electronic device. The method comprises the following steps: determining the difference between target parameters measured by the first antenna and the second antenna according to a wireless signal; determining the angle of arrival range of the wireless signal according to the difference; wherein the angle of arrival range is the first angle range or the second angle range; and measuring the angle of arrival of the wireless signal by using the first antenna and the second antenna according to the angle of arrival range. The technical scheme provided in the embodiment can improve the accuracy of angle of arrival measurement.

The invention discloses a semi-supervised learning positioning method based on channel mapping, belongs to the field of signal processing, and is applied to the problem of wireless positioning of user equipment in a communication and sensing integrated network. According to the method, mass unlabeled channel data which is easy to obtain is fully utilized, and the implicit relationship between the channel and the position is learned from the unlabeled data and the labeled data together. The semi-supervised learning scheme provided by the invention can be divided into two stages: firstly, pre-training an unsupervised dual-branch channel mapping twin network by using an unlabeled data set, and then performing supervised training fine tuning on the dual-branch channel mapping twin network and an overall positioning network of a positioning head module by using a labeled data set. According to the method, only a small part of labeled data is used, and robustness and positioning performance superior to a supervised learning algorithm and other baseline algorithms are obtained.

This disclosure provides methods, devices and systems for wireless positioning. An example method includes determining a first received signal strength indicator (RSSI) signature, the first RSSI signature including a respective RSSI associated with each access point (AP) of a first plurality of APs, where the first plurality of APs form at least a portion of a mesh network of APs, comparing the first RSSI signature with each reference RSSI signature of a first plurality of reference RSSI signatures, each reference RSSI signature of the first plurality of reference RSSI signatures including a respective RSSI associated with each AP of the first plurality of APs, and identifying a first position of the wireless STA based on the comparing of the first RSSI signature.

The invention provides an unmanned aerial vehicle positioning method and system based on a wireless positioning beacon and a program product, and relates to the technical field of unmanned aerial vehicle positioning, and the unmanned aerial vehicle positioning method comprises the steps: obtaining the first position information of the wireless positioning beacon, the second position information of an unmanned aerial vehicle, and the measurement distance information between the wireless positioning beacon and the unmanned aerial vehicle; determining a relative error vector of the unmanned aerial vehicle relative to the wireless positioning beacon based on the measurement distance information, the first position information and the second position information; and determining relative position information between the unmanned aerial vehicle and the wireless positioning beacon based on the relative error vector.

The invention discloses a high-precision indoor positioning system based on a smart bracelet, and the system comprises a data processing module which is used for obtaining and preprocessing multi-source sensing data collected by the smart bracelet; the gait reckoning module is used for executing gait event detection and pedestrian dead reckoning processing; the wireless observation module is used for carrying out preprocessing and credibility evaluation on indoor wireless positioning observation data; the fusion positioning module is used for carrying out credibility weighted fusion; the trajectory constraint module is used for applying trajectory rationality constraint and correcting abnormal position points; the error correction module is used for constructing a positioning error dynamic correction model and executing online correction processing; and the track output module is used for carrying out smoothing and time resampling processing and extracting a human body position determination result set. The method is based on the multi-source perception fusion and federated Kalman dynamic correction method, achieves the indoor high-precision positioning of the smart bracelet, and has the advantages of continuous track, controllable error and high environmental adaptability.

The invention discloses an ultra wide band (UWB) robust positioning method for a non-line-of-sight (NLOS) interference environment, and belongs to the technical field of wireless positioning. According to the method, firstly, all three-base-station combinations are generated through a permutation and combination method, the initial position of each group of base stations is solved through a trilateral positioning method, and a multi-dimensional coarse positioning point cloud is formed; then grouping the coarse positioning points according to the resolving participation condition of the base stations, acquiring representative position points of the base stations by adopting a central position estimation algorithm, and constructing a base station space distribution model; a mean vector and a covariance matrix of the point cloud are calculated, after a pseudo-inverse matrix is solved through SVD decomposition, the mahalanobis distance from each representative point to the distribution center is calculated, a dynamic threshold value is set according to the 95% confidence coefficient of chi-square distribution, a base station with the distance exceeding the threshold value is judged as an NLOS abnormal node, and data of the base station is abandoned; and finally, constructing a dual-stage anomaly suppression mechanism: screening reliable base stations based on geometric consistency at a measurement stage, dynamically adjusting the Kalman gain through an exponential gain constraint factor at a residual stage, constructing a dynamic noise model by fusing a geometric precision factor, and realizing position calculation by adopting improved extended Kalman filtering. According to the method, the positioning error can be effectively reduced in the NLOS interference environment, and a centimeter-level reliable positioning solution is provided for the fields of industrial Internet of Things or indoor positioning and the like.

The invention discloses a multi-base-station combined wireless positioning method and system based on a self-attention mechanism, and relates to the technical field of deep learning and wireless communication, and the method comprises the following steps: collecting channel observation data of distributed base stations, and forming a multi-base-station combined channel matrix; performing Gaussian normalization processing on each dimension of data of the multi-base-station joint channel matrix to obtain a normalized multi-base-station joint channel matrix, and performing multi-channel convolution to obtain a feature fusion matrix; performing self-attention value calculation on the feature fusion matrix to obtain a distributed attention coding matrix; and constructing a long-short-term memory recurrent neural network for the distributed attention coding matrix, and decoding the spatial position coordinates of the target to be perceived. According to the method, the ideas of distributed base station sensing, multi-base station channel information fusion and self-attention coding and decoding are innovatively provided, the channel feature extraction mode in an existing wireless positioning algorithm is improved, and the base station sensing precision in a large-range wireless communication scene is improved.

The invention discloses a dynamic positioning precision optimization system based on a self-learning fusion model, and relates to the technical field of wireless positioning. Comprising the steps that an acquisition and synchronization module synchronously acquires AOA, RSSI and TOA signals from a plurality of anchor points and generates a synchronous multi-source signal flow; the discrimination module extracts multi-dimensional instability characteristics such as fluctuation entropy, angle jitter and delay abrupt change rate of the signal flow, and classifies the current channel environment into predefined modes such as high occlusion, non-line-of-sight error or stable line-of-sight; the mapping module calls a corresponding weight distribution strategy according to the modal identifier to generate a real-time fusion weight vector; the adaptive positioning module couples the weight vector to an unscented Kalman filter observation model, dynamically adjusts the weight of each signal source in state updating, and outputs an estimated position and a positioning confidence coefficient; the optimization module monitors the positioning confidence and iteratively optimizes the weight strategy online based on the deviation of the positioning confidence from the target value. The method effectively improves the positioning precision and robustness in a complex dynamic scene.

Disclosed are techniques for wireless positioning. In an aspect, a user equipment (UE) performs one or more positioning measurements of one or more repetitions of a first positioning reference signal (PRS) resource on a first positioning frequency layer of at least a first PRS instance using a first receive beam, wherein a number of the one or more repetitions of the first PRS resource is based on a receive beam sweeping capability parameter of the UE, the receive beam sweeping capability parameter indicating a number of repetitions of a PRS resource on a positioning frequency layer of a PRS instance for which the UE is expected to use the same receive beam, and reports the one or more positioning measurements to a positioning entity.

The invention relates to a scraper conveyor chain fault detection system and method, the system comprises a motor state detection unit, a chain operation state detection unit and a chain fault positioning unit, the motor state detection unit comprises a motor state data acquisition module, a motor state data wireless transmission module and a motor state data processing module; the chain running state detection unit comprises a chain state data acquisition module, a chain state data wireless transmission module and a chain state data processing module; the chain fault positioning unit comprises a chain strain data acquisition module, a wireless positioning module and a chain fault positioning data processor. The fault type of the chain is judged according to the power of the motor of the scraper conveyor; and the specific position of the chain fault is correspondingly obtained according to the chain strain value of the fault point on each flat ring. The chain breaking, chain clamping and chain jumping fault types of the chain can be detected, the chain breaking, chain clamping and chain jumping positions can be accurately positioned, rapid maintenance is achieved, and the maintenance efficiency is improved.

Disclosed are techniques for wireless positioning. In an aspect, a user equipment (UE) receives, from a network entity, a configuration of one or more positioning reference signal (PRS) resources to measure during a positioning session, the one or more PRS resources having a PRS periodicity TPRS and a PRS occasion length LPRS, and measures the one or more PRS resources during a measurement period, wherein the measurement period is based on a number of measurement instances of the one or more PRS resources the UE is expected to process multiplied by a periodicity parameter, wherein the periodicity parameter is based on a PRS processing window of ‘T’ milliseconds, the PRS periodicity TPRS, and a measurement gap periodicity of at least one measurement gap.

The invention relates to the technical field of wireless positioning, in particular to a foundation deformation monitoring radar site selection method, which comprises the following steps: shooting to obtain an image of a to-be-monitored area, and obtaining a three-dimensional point cloud model of the to-be-monitored area; preprocessing the image, extracting and classifying ground feature features, training a deep learning model to identify different ground feature types, and assigning the different ground feature types to corresponding point cloud attributes; selecting a radar layout area according to the geological environment data, and dividing the radar layout area into a plurality of grids; selecting a grid at the center of the radar layout area as a radar monitoring point; constructing a fitness function according to intervisibility from a radar monitoring point to each point cloud, signal intensity data of radar scanning and point cloud attributes; and searching to obtain a grid with the maximum fitness function value, namely an output radar site selection result. According to the invention, the intervisibility and the radar signal intensity are comprehensively considered, the global optimal radar arrangement position is found by using the particle swarm optimization algorithm, and the quality and reliability of monitoring data are improved.

The invention relates to the technical field of wireless positioning, in particular to a dynamic-dynamic TDOA (time difference of arrival) cooperative positioning method based on an unmanned aerial vehicle-mounted mobile base station. The method comprises the following steps: constructing a cooperative sensing network comprising at least four unmanned aerial vehicles carrying unmanned aerial vehicle-mounted base stations, and realizing microsecond-level high-precision time synchronization of the whole network through a bidirectional distance measurement technology in combination with an introduced clock error model. All the base stations receive signals transmitted by the moving target to be measured under the unified time base, the arrival time is recorded, and a TDOA measurement value is calculated with the main node base station as the reference. And based on the group of TDOA measurement values, tracking and positioning the to-be-measured moving target by adopting an extended Kalman filtering algorithm, and estimating and outputting the three-dimensional position and speed of the to-be-measured moving target in real time by linearizing the nonlinear model. The method effectively overcomes the technical problems of difficult time synchronization and serious error coupling in a dynamic-dynamic scene, and has the advantages of being independent of ground infrastructure, high in positioning precision, strong in robustness and remarkable in cooperative gain.

The invention discloses a wireless positioning blood pressure transducer real-time monitoring and analyzing method based on the Internet of Things. The method comprises the following steps that S1, invasive pressure measuring signals are collected, wirelessly transmitted and preprocessed; s2, a Transform invasive pressure measurement signal analysis model is constructed; s3, performing local adaptive optimization on the hyper-parameters by adopting a bat algorithm; s4, performing global optimization on the bat algorithm hyper-parameters by using a sparrow search algorithm; s5, performing multi-sensor positioning data acquisition and Kalman filtering fusion to obtain real-time positioning; s6, the blood pressure anomaly detection result and the positioning data are fused, and a combined health risk assessment report is formed; and S7, the remote early warning module transmits the joint evaluation report and the real-time positioning information. The system has the advantages that real-time monitoring and accurate positioning of the blood pressure transducer are achieved by integrating the Internet of Things, multi-sensor positioning and intelligent data analysis, and efficient and accurate data support is provided for remote medical treatment and intelligent health management.

The invention relates to an indoor man-vehicle conflict early warning method, and the method comprises the steps: assembling a UWB chip tag on an in-station forklift, enabling an in-station worker to wear the UWB chip tag, and setting a UWB wireless positioning base station at the same time; obtaining a UWB broadband signal of the UWB wireless positioning base station, and carrying out signal denoising reconstruction processing; calculating a signal emission position through a hybrid positioning algorithm, wherein the hybrid positioning algorithm is a Chan algorithm based on a time difference of arrival / angle ranging hybrid positioning mode; and the safety fields of the forklift and the workers are divided respectively, and whether anti-collision early warning is carried out or not is judged according to the signal emission position. According to the scheme provided by the invention, the UWB chip is assembled to be matched with the UWB wireless positioning base station, the UWB broadband signal transmitting and receiving information is obtained, the signal transmitting position is calculated through signal denoising reconstruction processing and a hybrid positioning algorithm, whether anti-collision early warning is carried out or not is judged, and the probability of occurrence of safety accidents is reduced.

Disclosed are techniques for wireless positioning. For example, a computing device can determine, based on a device being within the indoor environment, an updated horizontal uncertainty for the device is equal to an average of measurement errors of signals from satellite vehicles (SVs). The computing device can determine external positioning assistance data for the device has a reliability greater than one of a first reliability threshold or a second reliability threshold. The computing device can determine a number of the SVs of the SVs is greater than or equal to a first threshold number of SVs. The computing device can determine, based on the number of SVs being greater than or equal to the first threshold number of SVs, position(s) for the device based on the updated horizontal uncertainty for the device and a horizontal uncertainty for the device from the external positioning assistance data for the device.

The invention relates to the technical field of wireless fingerprint positioning, in particular to a wireless positioning method based on a residual image attention neural network, which comprises the following steps of: acquiring fingerprint data; image signal processing; designing a residual image neural network; using a Softmax classifier to perform position prediction according to an embedded vector generated by the graph network; the method has good performance on fingerprint map construction and positioning tasks in a complex environment, high-precision position estimation in the complex environment is realized, and high-quality position service can be provided; and meanwhile, the capability of deep fingerprint positioning to adapt to environment change is improved, and the method has good positioning performance in an indoor complex and changeable dynamic scene.