314 results about "Channel impulse response" patented technology

The invention discloses an indoor UWB-IMU fusion trajectory tracking system and method based on factor graph optimization, and belongs to the technical field of UWB indoor positioning. The system adopts a multi-stage processing framework, and specifically comprises the following steps: firstly, collecting channel pulse response and distance information by virtue of a wireless communication system, constructing a dynamic environment sensing mechanism, and evaluating the current channel state and the availability of each base station in real time; secondly, for the ranging values of the available base stations in the NLOS environment, compensating by using historical information, and for the ranging values of the unavailable base stations, estimating and correcting by using a time step length; and finally, collaborative optimization is carried out on UWB ranging data, IMU inertial information and base station state information through an SW-FGO algorithm, so that positioning stability is ensured, and adverse effects of obstacle shielding and a multipath effect on trajectory tracking precision are reduced. The invention provides a fusion positioning system which combines the advantages of UWB and IMU, can realize the tracking of a target motion track, and is suitable for most LOS and NLOS indoor mixed scenes.

The invention provides a communication and perception integrated channel modeling method based on geometric statistics principle extension, and the method comprises the steps: constructing a channel simulation scene, configuring basic parameters of a channel, and obtaining large-scale parameters, communication path loss and perception sub-channel path loss, the basic parameters at least comprising the positions and speeds of a plurality of perception targets; acquiring an initial communication cluster parameter set and a sensing sub-channel cluster parameter set according to the basic parameters; according to a shared sensing sub-channel cluster parameter corresponding to a shared sensing target, correcting the initial communication cluster parameter set to obtain a corrected communication cluster parameter set including a shared communication cluster parameter, the shared sensing target being determined based on a pre-configured shared parameter; obtaining sensing cascade path loss and sensing cascade channel impulse response according to the parameters; and obtaining a communication channel impulse response according to the corrected communication cluster parameter set. Modeling depicts real sharing characteristics of communication and sensing channels, and can be well compatible with existing channel modeling standards.

The invention relates to the technical field of terminal communication, and provides a team state synchronization method based on ad hoc network communication, an intelligent terminal and a medium, after a plurality of intelligent terminals complete team networking, a first intelligent terminal elected as a team master device broadcasts a synchronization beacon frame, enabling the second intelligent terminal to enter a corresponding working state after receiving the synchronous beacon frame; predicting whether the bit error rate in a future short time is increased or not based on the channel impulse response fed back by the second intelligent terminal and the real-time position coordinates; when the predicted bit error rate is increased, forward error correction coding redundancy is increased in a pre-sent light effect instruction, and a target light effect instruction is obtained; and the target lighting effect instruction is sent to the second intelligent terminal, so that the second intelligent terminal controls the partition lamp group to output the corresponding lighting effect according to the received target lighting effect instruction, and visual synchronization of the team state is realized. According to the method, the accuracy of light effect instruction transmission can be guaranteed, and efficient visual synchronization of the team state is realized.

The invention discloses an HRR-based acoustic fire hazard type identification method, device and equipment and a medium, and relates to the technical field of fire hazard detection, and the method comprises the steps: obtaining an original acoustic signal through transmitting a high-frequency modulation ultrasonic wave and receiving a flame region reflection echo, obtaining channel impulse response data through channel estimation, and carrying out the channel impulse response data; flame features are extracted, a heat release rate curve is calculated and generated, finally fire type identification and fire behavior stage determination are completed based on the curve, dense smoke, shielding and illumination interference can be resisted, accurate quantification of the heat release rate is realized, fire type identification and fire behavior development stage determination can be finely carried out, and the accuracy of fire behavior determination is improved. And a stable and reliable technical support is provided for fire monitoring and emergency decision making.

This disclosure relates to techniques for performing beam selection using machine learning assistance in a wireless communication system. A wireless device and a cellular base station may establish a wireless link. An artificial intelligence model to use for beam selection may be determined. Channel impulse response information for a cell in a first frequency range may be determined. A downlink beam for a cell in a second frequency range may be selected based at least in part on the artificial intelligence model and the channel impulse response information for the cell in the first frequency range.

This disclosure provides methods, components, devices and systems for adjacent channel interference (ACI) mitigation techniques for ultra-wideband (UWB) systems. Some aspects more specifically relate to ACI mitigation for UWB systems. In some implementations, a wireless communication device may receive control information that identifies a preamble for communications to the wireless communication device in a UWB system. The wireless communication device may receive, via a signal in the UWB system, a data packet that includes the preamble. The wireless communication device may estimate a channel impulse response (CIR) of the signal and determine an interference metric that is based on the estimated CIR. The wireless communication device may process the data packet based on the interference metric.

The invention discloses an ISAC angular domain energy imaging method and an ISAC angular domain energy imaging system based on actual measurement channel response calibration ray tracing, and mainly solves the problem that an imaging model faces serious channel mismatch and cross-scene generalization limitation due to the fact that simulation data lacks physical consistency constraint in the prior art. According to the scheme, the method comprises the steps that geometric features are extracted from public map data or laser point cloud data, and an ISAC scene environment geometric model is constructed; acquiring an actual measurement channel impulse response containing multipath information by using the communication and sensing integrated equipment; performing path matching on the actual measurement channel impulse response and the ray tracing simulation channel response, inverting environment propagation parameters and correcting scattering parameters; and inputting the calibrated parameters into a ray tracking model, counting energy contribution in each space direction under the condition of a single antenna, obtaining angular domain energy distribution and confidence coefficient, and mapping the angular domain energy distribution and confidence coefficient to a spherical grid to form an imaging result. According to the method, physical mismatch between simulation and real environments is effectively eliminated, low-cost and high-precision angular domain energy imaging and confidence evaluation are realized under the condition of a single antenna, and the method can be used for imaging reconstruction of an ISAC system, environmental perception and generation of a neural network training data set.

The invention relates to the technical field of communication, in particular to a high-precision measurement method for radial velocity of a shallow sea underwater acoustic target based on ray sound field reconstruction, which comprises the following steps of: establishing a three-path propagation model comprising direct arrival, water surface reflection and seabed reflection, and constructing a joint representation equation comprising channel impulse response and target motion parameters by the path propagation model; according to the method, a space-time joint representation model of multipath sound rays is constructed, and the limitation of a traditional single-path model is broken through by quantifying the coupling relation between propagation time delay and Doppler frequency shift of different paths; the development provides a new technical means for underwater target tracking and positioning, underwater acoustic communication Doppler compensation and marine environment dynamic monitoring, and especially has an important application prospect in the fields of underwater unmanned cluster collaboration and the like.

A micro-deformation monitoring method, comprising: on the basis of received data of a wireless communication network, determining a channel impulse response (110); on the basis of the channel impulse response, generating a range-angle map (120); on the basis of the range-angle map, determining a phase difference between a monitoring target point and a reference point (130); and on the basis of changes in the phase difference, determining the deformation of the monitoring target point (140). Further provided are an electronic device and a computer-readable storage medium.

A distributed ultra-wide band (UWB) radar system and methods for operating the same are disclosed. The distribute radar system uses a plurality of separate UWB radios or nodes that do not use a centralized clock or source of time. However, the distributed UWB system operates to provide radar-like functionality and fine-grain sensing capabilities through synchronization based on line-of-sight (LOS) signal processing and noise estimations. Synchronized channel impulse responses (CIRs) can be processed for general object detection and tracking, gesture recognition, or even micro-motions such as monitoring vitals

The invention relates to a method for operating a transceiver device (1), comprising the following steps to be performed by the transceiver device (1): transmitting a pulse radio signal (5) at a given time; receiving a reflected signal of the transmitted pulse radio signal (5); generating a channel impulse response that describes the reflected signal as a function of a path delay; determining a self-interference distance range of the path delay of the channel impulse response, wherein the reflected signal of the self-interference distance range describes a self-interference signal of the transceiver device (1); determining at least one target distance range of the path delay of the channel impulse response, wherein the reflected signal of the target distance range describes a signal of the target distance range;Determining a signal component of the target distance range signal correlated with the self-interference signal using an operator, wherein the operator maps the self-interference signal to the correlated signal component of the target distance range signal; determining a signal component of the signal uncorrelated with the self-interference signal by removing the signal component correlated with the self-interference signal using a correlation cancellation filter.

The present invention provides a method for low-complex estimation of Direction of Arrival (DoA) and Time of Arrival (ToA) in multi-antenna-based communication comprising detecting overlapped paths between a Mobile Station (MS) and a Base Station (BS) operating under said multi-antenna-based communication with scatters present therein involving channel paths represented as Channel Impulse Response (CIR) defined with channel signatures including delay and angle steering vectors, decoupling the channel paths in delay and angle-domain and separately estimate the DoA and ToA of each path with a low computational complexity which is based on one-dimensional low-index based rotation methodology and finally pairing the DoA and the ToA.

The invention discloses an indoor positioning method and system based on 5G channel characteristics and pedestrian dead reckoning, and belongs to the technical field of indoor positioning. The method comprises the following steps: firstly, converting input complex 5G channel impulse response (CIR) data into a two-dimensional characteristic matrix; inputting the two-dimensional feature matrix into a deep convolutional neural network to perform feature transformation and obtain a 5G positioning position track, and then performing time sequence smooth optimization on the 5G positioning position track by using a Kalman filter to obtain an optimized 5G position track; according to the invention, a deep convolutional network is adopted to fully extract amplitude-phase composite features of 5G channel impact response CIR, and machine learning step length measurement and calculation of multi-dimensional gait features are combined to accurately position an indoor position track, so that the utilization efficiency of positioning data is improved; and intelligent complementation can be carried out between the optimized 5G position trajectory and the dead reckoning trajectory, and the indoor positioning precision and positioning stability in a complex indoor environment are improved.

The invention relates to the technical field of wireless ranging, and discloses a channel estimation method, a coherent combination method, a circuit, a sensor and equipment. The channel estimation method for ultra-wideband ranging comprises the steps that channel estimation is carried out on at least two fragments, channel impulse responses of the at least two fragments are obtained, and the at least two fragments are from the same MMS data packet; and accumulating the channel pulse responses of the at least two segments to obtain the channel pulse response of the MMS data packet. The channel estimation of the ranging packet based on the plurality of segments is realized, the energy of the channel pulse response is increased, the ranging sensitivity is improved, and the advantages of the ranging packet based on the plurality of segments are brought into full play.

The invention provides a multipath TOA calculation method and system based on a ground-based navigation system and electronic equipment, and the method comprises the steps: collecting a signal frequency spectrum which is transmitted by the ground-based navigation system and is superposed by a plurality of propagation paths in a frequency domain channel of the ground-based navigation system, and constructing a discrete frequency domain channel impulse response model related to the signal frequency spectrum; determining the number of propagation paths of the ground-based navigation system signals according to the signal spectrum; and alternately correcting the arrival time and the path amplitude of all the propagation paths by gradually increasing the propagation paths to the path number and the second target function until the first target function converges, so as to obtain the target arrival time and the target path amplitude of each propagation path of the ground-based navigation system. According to the method, the calculation precision of the number of propagation paths is improved, the false alarm and missed detection probability in a complex multipath channel is reduced, the arrival time of the propagation paths and the calculation accuracy of the path amplitude are improved, and therefore the positioning precision of the whole foundation navigation system is improved.

The invention discloses a scene-adaptive multipath time delay alignment method and device for a wireless communication system, and the method comprises the steps: employing an SISO channel detection system to actually measure channel data, employing rectangular or RRC shaping filtering to generate a CAZAC oversampling sequence as a template function, calculating a cross-correlation matrix of an IQ signal and the template function, and enabling the CAZAC oversampling sequence to serve as the template function; a noise threshold is calculated based on the median power and the false alarm rate, dynamic threshold filtering is executed, a cross-correlation matrix after denoising is generated, and preliminary estimation of the time domain impulse response is completed; extracting multipath time delay and complex gain from the cross-correlation matrix by using an SAGE algorithm; drawing a power delay spectrum PDP for the channel impulse response; and performing alignment operation on the PDP in combination with the geographical location information of the transceiver during actual measurement. According to the method, the defect of traditional alignment in a severe scene is overcome, the statistical modeling accuracy is improved, the multipath time delay can be effectively aligned through experimental verification, and reliable support is provided for channel modeling.

The invention discloses a self-supervised ultra-wideband positioning method based on an improved double-delay depth deterministic strategy. The method comprises the following steps: acquiring channel impulse response data CIR and performing preprocessing; an improved double-delay depth deterministic strategy model is constructed to carry out UWB ranging error correction, the improved double-delay depth deterministic strategy model is based on a double-delay depth deterministic strategy gradient model, a double-commentator network structure is designed, a spatial-temporal feature coding layer based on a self-attention mechanism is introduced, and UWB ranging error correction is carried out. Capturing a long-range dependency relationship through a dynamic weight distribution mechanism, and establishing cross-timestamp time-space association feature mapping; a target network delay updating mechanism is introduced, so that the updating frequency of a target network is lower than that of a commentator network and an actor network, and action noise generated by a strategy is regularized; and generating a pseudo tag by adopting extended Kalman filtering, and carrying out iterative optimization to obtain a positioning result. The method is particularly suitable for processing noise and multipath effect in CIR data, and high-precision UWB positioning is realized.

The invention discloses an ultrasonic cross-metal channel estimation method based on improved block sparse Bayesian learning, and belongs to the field of ultrasonic cross-metal communication channel estimation. Constructing a pilot signal relationship between the receiving end and the transmitting end on the two sides of the metal wall; dividing a to-be-estimated metal channel impulse response into zero-value blocks or non-zero blocks of block sparse Bayesian according to whether the to-be-estimated metal channel impulse response is zero or not; the method comprises the following steps: iteratively updating hyper-parameters a, b, Bi and lambda of a non-zero block by adopting an expectation maximization algorithm, realizing structured sparse learning, calculating a maximum posteriori estimation result by utilizing a final hyper-parameter of the non-zero block, and taking the maximum posteriori estimation result as an estimation value of ultrasonic cross-metal channel pulse response. According to the method, a block sparse Bayesian learning algorithm is improved by utilizing the characteristics of metal channel pulse response, and compared with an original algorithm, the accuracy of channel estimation in a low signal-to-noise ratio environment is improved.

The invention belongs to the technical field of unmanned aerial vehicle millimeter wave communication channel modeling, and discloses an urban low-altitude unmanned aerial vehicle millimeter wave communication channel modeling method under sand and dust weather conditions. According to the method, a three-dimensional geometric random channel model is provided, and scatterers are divided into three types: near-field scatterers at the transmitting end and the receiving end adopt bicylindrical models, suspended dust adopts a complete ellipsoid model, and ground fixed scatterers adopt a lower half ellipsoid model with a larger semi-major axis. On the basis of the model, channel impulse response containing sight distance, primary scattering components and secondary scattering components is derived, and a space-time correlation function and Doppler power spectral density are calculated. And finally, establishing a joint path loss model: on the basis of the two-path fading model, introducing an additional attenuation factor related to the visibility of the sand and dust and the particle charge mass ratio, and determining specific parameters of the factor according to the grade of the sand and dust. According to the method, the channel characteristics can be accurately predicted, and theoretical support is provided for anti-interference design and link optimization of the millimeter wave communication system of the unmanned aerial vehicle.

The invention relates to a position estimation method and device based on multi-task joint learning. The method comprises the following steps: acquiring a channel impulse response sample and an estimated value of a receiving end to a distance; constructing a variational auto-encoder model; the variational auto-encoder model comprises an encoder, a decoder, a channel state clustering device, a mutual information estimator, a channel state discriminator and a geometric information estimator; pre-training and joint training are sequentially performed on the variational auto-encoder model to obtain a trained variational auto-encoder model, in the pre-training stage, an encoder, a decoder and a channel state clustering device are trained, and in the joint training stage, full model parameters are optimized based on preset joint loss; and inputting a channel impulse response to be positioned into the trained variational auto-encoder model, and determining a target position according to the output geometric information estimator. By adopting the method, the accuracy, the stability and the robustness of positioning estimation can be improved, and the high-precision indoor positioning requirement can be met.

This application provides a signal receiving method, a transmitting method, a terminal, a system, and a storage medium, relating to, but not limited to, the field of optical communication technology. The receiving terminal removes a unique header from the time-domain signal data according to a first preset length. The time-domain signal data is obtained by transmitting the original signal data from the transmitting terminal through a transmission channel and is a linear convolution of the original signal data and the channel impulse response of the transmission channel. The original signal data includes a data group composed of a unique header of the first preset length and symbol data of the second preset length. Multiple intermediate time-domain data blocks are constructed from the time-domain signal data after removing the unique header, based on the length of the data group, so that each intermediate time-domain data block corresponds to a circular convolution of a data group and the channel impulse response. Frequency domain equalization is performed on the intermediate time-domain data blocks to obtain first equalized time-domain signal data. The embodiments of this application can improve the communication quality of the optical communication system while maintaining transmission capacity.

The application discloses a wireless communication channel parameter measurement method and system, comprising the following steps: obtaining a sending signal based on a PN sequence of a wireless transmitting end; obtaining an influence of a channel impulse response based on the sending signal; performing convolution on the sending signal and the influence of the channel impulse response to obtain a receiving signal; obtaining autocorrelation outputs of different channels based on the receiving signal and the PN sequence; and obtaining path loss of the channel based on the autocorrelation outputs of the different channels. Compared with the traditional channel measurement activity using a special channel measurement instrument or a VNA, the device cost is greatly reduced, the manpower and material resources cost of the measurement activity is low, and a large amount of channel data can be obtained according to different experimental schemes.

One or more measurements of a positioning reference signal (PRS) is performed (1010, figure 10) by a first apparatus 202 (operating as a terminal device, UE 110, or a base station, gNB 120). The first apparatus obtains (1020), based on the one or more measurements, at least one of: a set of first estimates 215 of a power delay profile (PDP), or a set of second estimates of a channel impulse response (CIR). The first apparatus performs (1030) differential quantization 220 for at least one of: a subset of first estimates from the set of first estimates, or a subset of second estimates from the set of second estimates. Then, the first apparatus transmits (1040), via a plurality of reference signal received power per path (RSRPP) messages, to a second apparatus 204 (operating as a location server, LMF 130), a measurement report 225 including at least one of: quantized first estimates of the PDP or quantized second estimates of the CIR. The UE may measure received DL PRS signals, or the gNB may measure received UL PRS signals, and estimate PDP or CIR. The container to encapsulate the CIR / PDP is not limited to RSRPP, and may be other reporting messages. The second apparatus 204 may perform 235 differential de-quantization for the at least one of the quantized first estimates or the quantized second estimates, and then construct 240 at least one of the power delay profile or the channel impulse response based on at least the differential dequantization.

The application relates to the technical field of positioning device signal processing and positioning precision, and particularly discloses a non-line-of-sight classification and error compensation method and system based on a double convolution neural network, the method comprising the following steps: acquiring channel impulse response data of an ultra-wideband signal, and pre-processing the channel impulse response data to obtain an amplitude sequence in real number form; constructing a double convolution neural network classification model, the double convolution neural network classification model comprising parallel large-kernel convolution blocks and small-kernel convolution blocks, which are respectively used for extracting macroscopic waveform features and microscopic fluctuation features from the amplitude sequence; and performing classification training after fusing the macroscopic waveform features and the microscopic fluctuation features; and based on the trained classification model, the regression compensation of ranging errors of non-line-of-sight signals is performed, macroscopic waveform contour features and microscopic local fluctuation features can be simultaneously extracted from data, and a complementary feature extraction mechanism can more comprehensively describe the differences between LOS / NLOS signals compared with a single-structure network.

Systems and techniques for localization of disturbances are illustrated. One embodiment includes a method for detecting a disturbance in an area of operation, the area of operation including a plurality of transmitter-receiver pairs. The method obtains, based on a first plurality of signal transmissions between the plurality of transmitter-receiver pairs, at least one baseline channel impulse response (CIR) measurement. The method obtains, based on a second plurality of signal transmissions between the plurality of transmitter-receiver pairs, at least one additional CIR measurement; The method obtains, based on the at least one additional CIR measurement and the at least one baseline CIR measurement, at least one residual CIR measurement. The method derives, based on a sufficient similarity between the at least one residual CIR measurement and at least one particular key of a plurality of keys, localization data for at least one disturbance detected within the area of operation.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a first indication of a set of analog receive beams and an instruction to report one or more post-analog-beamformed channel impulse responses (CIRs) that are based at least in part on the set of analog receive beams. The UE may transmit a second indication of a CIR report that indicates the one or more post-analog-beamformed CIRs. Numerous other aspects are described.

Aspects presented herein may improve the efficiency and performance of artificial intelligence (AI) / machine learning (ML) (AI / ML) positioning by enabling a network node (e.g., a base station, transmit receive point (TRP), etc.) to compress uplink (UL) reference signal measurements to reduce reporting overhead for UL reference signal measurements. In one aspect, a network node performs at least one channel impulse response (CIR) measurement or at least one channel frequency response (CFR) measurement for a sounding reference signal (SRS) set. The network node compresses at least one CIR measurement or at least one CFR measurement for the SRS set. The network node reports, for the network entity, one or more of the at least one compressed CIR measurement or the at least one compressed CFR measurement for the SRS set.

The invention discloses a positioning information determination method and an electronic device, and relates to the technical field of smart home, and the method comprises the steps: transmitting an ultrasonic detection signal to a target space through a smart home device, and obtaining an echo sequence; extracting a sampling sequence corresponding to the echo sequence based on the starting moments corresponding to the plurality of emission periods, and filtering the sampling sequence to obtain a first receiving signal used for indicating the dynamic change of the moving target in the target space; performing cross-correlation operation on the first receiving signal and the ultrasonic detection signal to obtain a channel impact response sequence corresponding to the target space; and performing clustering analysis on the channel impact response sequence to determine the positioning information of the moving target. The problem that a human body sensing technology cannot accurately position the moving target in a complex home scene under the condition that special hardware is not additionally installed is solved, and the effect that the moving target can be positioned without additional special hardware is achieved.

The embodiment of the invention provides an RIS cascade channel model simplification method and device based on cluster deletion, and relates to the technical field of wireless communication. The method comprises the following steps: generating a first multipath of a first channel from a transmitting end to a reconfigurable smart surface (Tx-RIS), and generating a second multipath of a second channel from the RIS to a receiving end (RIS-Rx); performing power normalization and arrangement processing on the first multipath and the second multipath respectively; respectively carrying out convolution operation on the first multipath and the second multipath according to the sorting sequence, and determining reserved multipath combination information; calculating RIS electromagnetic response according to the multipath combination information; and generating a channel impulse response of Tx-RIS-Rx according to the RIS electromagnetic response. According to the scheme provided by the invention, the cluster or multipath component with low power ratio is removed from the Tx-RIS and RIS-Rx sub-channels, so that the modeling complexity is effectively reduced and the modeling efficiency is improved on the premise of ensuring the statistical channel characteristics.

The application discloses a kind of distributed array high-precision time synchronization method based on compressed sensing (CS) and secondary least square (QLS), belong to wireless communication and radar signal processing technical field.For under the restriction hardware bandwidth and strong multipath environment, traditional cross-correlation method is limited by Rayleigh resolution and sampling grid, there is the problem of serious peak aliasing, insufficient synchronization accuracy, the application proposes CS-QLS joint decoupling strategy.The method constructs frequency domain observation matrix and high-density time delay over-complete dictionary by transmitting sparse multi-tone probe signal, reconstructs sparse channel impulse response using CS, separates multipath aliasing and determines direct wave coarse synchronization boundary;Further combined with main path and adjacent grid point amplitude information, QLS is used to fit continuous domain peak position, and grid mismatch error is corrected.The method breaks through the limitation of physical bandwidth and sampling grid, and realizes nanosecond-level high-precision time synchronization in complex non-line-of-sight environment with very low computational complexity.