278 results about "Frequency space" patented technology

A near-optimal Karhunen-Loeve basis expansion modeling (KL-BEM) orthogonal time frequency space (OTFS) receiver with superimposed pilots has been proposed for high-mobility communications with Doppler spread channel. First, an initial KL-BEM channel estimation is conducted by superimposed pilots, followed by the removal of superimposed pilots from the received OTFS signal and equalisation by message passing (MP) algorithm. After that, the detected data symbols are utilized as pseudo pilots along with the superimposed pilots to refine both KL-BEM channel estimation and equalisation in an iterative manner. Simulation results confirm the superior performance of the proposed KL-BEM OTFS receiver over the prior art in terms of the mean-square-error (MSE) of channel estimation and bit error rate (BER). It also has a close BER performance to the BER lower bound obtained by assuming perfect channel estimation. It contributes to high spectral efficiency and fast convergence performance.

The invention relates to the technical field of signal processing, in particular to an unmanned aerial vehicle self-noise filtering method and system based on multichannel time-frequency spatial filtering. The method comprises the following steps: acquiring a multi-channel noise-containing sound signal by using a microphone array carried by an unmanned aerial vehicle, and performing short-time Fourier transform to obtain a frequency domain signal; estimating a ratio mask by using a deep neural network, and performing logarithm normalization processing on the frequency domain signal; remodeling the sound signal to match the FFT length of the time-frequency spatial filter, and constructing the time-frequency spatial filter in combination with the multi-channel ratio mask; removing the self-noise of the unmanned aerial vehicle by using the filter and obtaining a target sound signal; and finally, converting the frequency domain signal into a time domain signal through inverse short-time Fourier transform. Through innovative fusion of multi-channel acquisition, deep learning and time-frequency space filtering, the self-noise of the unmanned aerial vehicle in a complex environment is accurately filtered, and the accuracy and efficiency of transformer substation noise monitoring are remarkably improved. Reliable acoustic data are provided for state monitoring of the power equipment, and the method has important engineering application value.

The invention discloses an electromagnetic compatibility test data automatic acquisition and analysis method and system. The method comprises the following steps: automatically acquiring electromagnetic compatibility test data as an input signal and extracting a target signal; respectively extracting an amplitude component and a change rate component of the target signal, combining to obtain a complex eigenvalue, and performing time integration on the complex eigenvalue to obtain an eigenvector component of the target signal; dividing a frequency space into a low-frequency band and a high-frequency band, and calculating the power density of each frequency point of the target signal in a segmented manner; and carrying out quantitative analysis on the electromagnetic compatibility to obtain an electromagnetic compatibility score. According to the method, the target signal can be accurately extracted from the mixed input signal in real time, the multi-dimensional features are extracted from the target signal, the time domain and frequency domain features of the target signal are comprehensively described, the frequency spectrum power density is accurately calculated in a segmented and adaptive manner, the accurate quantitative analysis of the electromagnetic compatibility level is realized, and the accuracy of the electromagnetic compatibility is improved. And the accurate evaluation requirements of different test scenes on the compatibility level can be met.

The invention discloses an inter-Doppler interference suppression method based on a Gaussian learning factor particle swarm algorithm. The inter-Doppler interference suppression method comprises the following steps that pilot frequency and data symbols are coded to a resource grid of a two-dimensional time delay Doppler domain through orthogonal time-frequency space modulation; on a transmitter, mapping data on a time delay Doppler domain grid to a time-frequency domain through inverse symplectic finite Fourier transform to obtain a time-frequency domain signal; performing Hisenberg transformation on the time-frequency domain signal to obtain a time domain sending signal; obtaining a time domain receiving signal after the time domain sending signal passes through a wireless channel; performing Doppler compensation processing on the time domain receiving signal by using Doppler frequency shift to obtain a signal after Doppler compensation; then performing matched filtering on the signal after Doppler compensation and a received pulse, and sampling to obtain a matched filter output signal; and the matched filter output signal is subjected to the Sextile Fourier transform to obtain a time delay Doppler receiving signal. The method can realize suppression of inter-Doppler interference to a certain extent.

Disclosed is a windowing method for OTFS-based wireless signals to mitigate interference due to fractional delay and Doppler cases and to control out-of-band emission. The method provides for suitable windowing mechanisms for the multicarrier orthogonal time frequency space (OTFS) scheme in order to manage out-of-band emission and interference due to the limited time and frequency resolution of the OTFS frame.

Methods, systems, and devices for wireless communications are described. A device may receive a set of demodulation reference signals (DMRSs) over a multi-path channel on a set of resources in accordance with a reference signal pattern. The reference signal pattern may be associated with a non-uniform frequency spacing that results in a row-sampled Discrete Fourier Transform (DFT) matrix associated with the reference signal pattern having a lower coherence than other row-sampled DFT matrices. Additionally or alternatively, the device may receive a set of tracking reference signals (TRSs) over the multi-path channel. The set of TRSs may be specific to wide-area terrestrial broadcast services, single frequency network (SFN)-based broadcast services, multimedia broadcast multicast services (MBMSs), or the reference signal pattern. The device may perform channel estimation based on receiving one or both of the set of DMRSs or the set of TRSs over the multi-path channel.

Disclosed is a method for resource allocation in the delay-Doppler grid that assigns radio resources to the users in a flexible manner taking into consideration their specific requirements. The method provides a flexible structure for Orthogonal Time Frequency Space (OTFS) waveform in terms of resource allocation / scheduling. This flexibility is imperative for the ever-increasingly diverse user requirements of wireless communication systems in terms of reliability, latency, data rates, mobility, security etc.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, a configuration of a control region in a delay-Doppler domain. The UE may receive, from the base station, a physical downlink control channel (PDCCH) communication with orthogonal time frequency space (OTFS) precoding. The UE may decode the PDCCH communication with OTFS precoding based at least in part on the configuration of the control region in the delay-Doppler domain. Numerous other aspects are described.

The invention provides a partial discharge mode recognition method based on multi-channel sound signal time-frequency space spectrogram fusion, and belongs to the technical field of partial discharge mode recognition. The problem that information redundancy and difference between existing multi-channel sound signals cannot be effectively fused and discriminant features cannot be extracted is solved. The method comprises the following steps: collecting and summarizing multichannel sound signal data corresponding to different partial discharge models as a data set; performing normalization processing on the original multichannel partial discharge sound signal, and mapping a time domain signal into time-frequency joint distribution to obtain a gray scale time-frequency spectrogram; performing multi-scale and multi-direction decomposition on the grayscale time-frequency spectrogram to obtain each channel sub-graph; different fusion strategies are used for fusing the channel sub-graphs obtained through decomposition; reconstructing a time-frequency space fusion spectrogram from the fused sub-graphs of each channel through inverse transformation; extracting features; identifying a partial discharge mode; the method is applied to partial discharge detection.

Orthogonal Time Frequency Space (OTFS) is a novel modulation scheme with significant benefits for 5G systems. The fundamental theory behind OTFS is presented in this paper as well as its benefits. We start with a mathematical description of the doubly fading delay-Doppler channel and develop a modulation that is tailored to this channel. We model the time varying delay-Doppler channel in the time-frequency domain and derive a new domain (the OTFS domain) where we show that the channel is transformed to a time invariant one and all symbols see the same SNR. We explore aspects of the modulation like delay and Doppler resolution, and address design and implementation issues like multiplexing multiple users and evaluating complexity. Finally we present some performance results where we demonstrate the superiority of OTFS.

The present application provides a method for extracting surface wave dispersion curves based on strain fields, including the steps of: extracting strain data from seismic observation data; preprocessing the strain data according to the type of the seismic observation data to obtain strain components; converting the strain components from the time-space domain to the frequency-space domain through Fourier transform; converting the strain components from the frequency-space domain to the frequency-phase velocity domain through frequency-Bessel transform to obtain the surface wave dispersion spectrum of the strain components; and picking up the surface wave dispersion curves according to the surface wave dispersion spectrum. The present application fills the technical gap in extracting surface wave dispersion information from DAS data, provides a powerful tool for extracting surface wave dispersion information applicable to single-component or multi-component DAS data, has important theoretical significance and practical value for the development of surface wave dispersion imaging methods based on DAS observations, and provides ideas for extracting the dispersion information of surface waves or body waves such as Rayleigh waves, Scholte waves, and Love waves.

The present invention relates to the technical field of seismic exploration. Provided are a three-component seismic data vector anti-aliasing interpolation reconstruction method and an apparatus. The method comprises: representing three-component seismic data in a time domain as pure quaternions for vector joint; transforming the pure quaternion data in a time-space domain to a frequency-space domain to obtain frequency-space domain data; transforming the frequency-space domain data into a frequency-wave number domain; in the frequency-wave number domain, using an inclination angle scanning strategy to construct a mask matrix; performing vector anti-aliasing interpolation reconstruction on the frequency-space domain data and the mask matrix, so as to obtain a frequency-space domain reconstruction result; and inversely transforming the frequency-space domain reconstruction result to the time-space domain to obtain a time domain three-component three-dimensional data anti-aliasing reconstruction result. The present invention can effectively solve the problem of vector anti-aliasing reconstruction for three-component seismic data that contain both irregular and regular missing traces, thus improving the accuracy of effective wave event identification.

The invention discloses an I SAR fusion imaging method, system and device based on centralized multi-station networking, and relates to the technical field of radar imaging, and the method comprises the steps: obtaining I SAR frequency domain echo data of each subsystem; performing frequency domain space matching on the frequency domain echo data based on the observation angle difference of each radar; performing frequency domain alignment processing on the matched frequency domain data; and fusion and imaging are carried out. According to the I SAR fusion imaging method, system and device based on the centralized multi-station networking, the imaging resolution is remarkably improved, multi-station frequency domain data are mapped to a unified local frequency space through a coordinate transformation matrix, non-uniform data are subjected to uniform reconstruction in combination with a self-adaptive interpolation algorithm, and the imaging resolution is remarkably improved. The frequency domain integration interval is effectively expanded, compared with a single-station I SAR which only covers a local area of the total rotation angle of the target, the range resolution is further optimized through multi-station bandwidth synthesis in the range direction, and high-fidelity reconstruction of the target in the complex shape is achieved.

A squeezed light generator may include a triply-coupled optical resonator having a triplet resonance with a split-resonant frequency spacing Ω, where the triplet resonance receives light at frequencies associated with at least one split-resonant frequency in the triplet resonance and generates squeezed light with at least another split-resonant frequency in the triplet resonance.

The embodiment of the invention relates to the technical field of computer vision, in particular to an RGBT target tracking method based on frequency space enhancement and time adaptation, which comprises the following steps: obtaining a training sample set which comprises a plurality of video sequences, and each video sequence is composed of a visible light image and a thermal infrared image which are paired; constructing an RGBT target tracking model based on frequency space enhancement and time adaptation, wherein the RGBT target tracking model is composed of a frequency space enhancement network, a cross-modal feature extraction network and an online score prediction network; performing iterative training on the RGBT target tracking model based on the training sample set until convergence to obtain a trained model; and inputting the target video into the trained model to obtain a tracking result of the target video output by the trained model. According to the method, the coping capacity of RGBT target tracking in challenging scenes such as background interference and thermal crossover can be well improved, and the accuracy, efficiency and robustness of RGBT target tracking are effectively improved.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter network node may generate a guard interval (GI)-based orthogonal time frequency space (OTFS) waveform comprising at least one defined sequence associated with at least one GI in a time domain corresponding to the GI-based OTFS waveform. The transmitter network node may transmit at least one signal based on the GI-based OTFS waveform. Numerous other aspects are described.

Device, methods, and systems for implementing aspects of orthogonal time frequency space (OTFS) modulation in wireless systems are described. In an aspect, the device may include a surface of an object for receiving an electromagnetic signal. The surface may be structured to perform a non-electrical function for the object. The surface may generate an electrical signal from an electromagnetic signal. The electromagnetic signal may be received from a transmitter. The transmitter may map digital data to a digital amplitude modulation constellation in a time-frequency space. The digital amplitude modulation constellation may be mapped to a delay-Doppler domain and the transmitter may transmit to the surface according to an orthogonal time frequency space modulation signal scheme. The apparatus may further include a demodulator to demodulate the electrical signal to determine digital data.

The invention provides a two-stage fractional order time delay and Doppler frequency shift estimation method based on an orthogonal time frequency space (OTFS). The two-stage fractional order time delay and Doppler frequency shift estimation method based on the OTFS is characterized in that the two-stage fractional order time delay and Doppler frequency shift estimation method based on the OTFS is provided; firstly, integer estimation of time delay and Doppler frequency shift is carried out by using a maximum likelihood estimation method, and the integer range of the time delay and Doppler frequency shift is determined; secondly, the Fibonacci sequence is used for determining the segmentation proportion, and the integer interval is segmented; and then, calculating an inner product of a sending signal subjected to channel influence and a receiving signal, selecting a segmentation point with the maximum inner product to generate a new search area, re-determining the segmentation proportion, and repeating the steps until the maximum iteration frequency is reached. And finally, calculating the distance and the speed of the target by using the obtained time delay and Doppler frequency shift. According to the OTFS modulation-based two-stage fractional order time delay and Doppler frequency shift estimation method designed by the invention, fractional order time delay and Doppler frequency shift can be accurately estimated, and an important theoretical basis is provided for realizing target perception in a communication and induction integrated system.

The invention provides a method and system for evaluating bridge damage caused by ship collision and a medium, and relates to the technical field of bridge health monitoring, and the method comprises the steps: collecting acceleration response signal arrays at different heights and positions of a bridge pier, and generating a time sequence matrix; drawing time-frequency coherence spectrums under different primary functions, and obtaining coherence spectrum entropies; based on an information entropy principle, determining an optimal primary function; obtaining a local correlation coefficient of the time sequence matrix in a time-frequency space under the optimal primary function, and drawing a time-frequency coherence spectrum; according to the local correlation coefficient and the time-frequency coherence spectrum, evaluating the correlation dependence degree between the time sequences, and judging whether the ship and bridge collision damage occurs or not; if collision damage occurs, time-frequency coherent damage factors at different positions of the time sequence matrix are calculated, and the collision damage position and the collision damage degree are determined according to the convex maximum value in a time-frequency coherent damage factor trajectory curve. According to the method, the influence of environmental factors can be effectively separated, and a basic method support is provided for establishing a ship and bridge collision damage evaluation technology.

The invention belongs to the technical field of mobile communication, and particularly relates to an orthogonal time-frequency air conditioning-based integrated waveform design method, which comprises the following steps of: constructing a receiving and transmitting filter bank with a frequency spectrum shaping characteristic on a time domain level, converting an item with a complex analytic expression in a traditional architecture into a scaling factor capable of being linearly processed, and carrying out linear processing on the scaling factor; architectural simplification of a sensing signal processing flow is realized; on a delay Doppler domain level, aiming at an inter-Doppler interference mechanism caused by static environment clutter coupling and a fractional Doppler effect, a pilot frequency sequence matrix with a strong self-correlation main lobe and a weak cross-correlation side lobe is innovatively constructed, and accurate separation of aliasing echoes is realized by using a sharp delay-Doppler resolution characteristic of the pilot frequency sequence matrix. According to the scheme, through the cross-domain cooperation mechanism, on the premise of maintaining the communication sensing dual-mode performance, double breakthrough of signal processing architecture simplification and pilot frequency overhead optimization is achieved, and an innovative design framework is provided for a communication sensing integrated system in a mobile scene.

The invention provides a signal detection method for a multi-antenna orthogonal time-frequency-space sparse code division multiple access system, which is characterized in that dimensionality reduction is carried out on time domain and time delay Doppler domain signals by utilizing sparsity of a sparse code division multiple access codebook, and prior distribution of the time domain signals is approximated by using Gaussian distribution. Preliminary detection is realized by acquiring cavity distribution of a signal in a time domain, and the posterior probability of the signal is calculated by using a sparse code division multiple access codebook in a time delay Doppler domain. Based on a transformation relation in a multi-antenna orthogonal time-frequency-space sparse code division multiple access system, information exchange between a time domain and a time delay Doppler domain is realized. The sparse structure of the time domain matrix in the multi-antenna orthogonal time-frequency-space sparse code division multiple access system is utilized, and the complexity of matrix inversion in the algorithm is reduced. By using the method, the complexity of algorithm implementation can be reduced while the signal detection performance is ensured by utilizing the dual sparsity of the multi-antenna orthogonal time-frequency-space system and the sparse code division multiple access codebook.

The invention relates to a practical aggregation method of a power system frequency model, in particular to a practical aggregation method of a power system frequency model considering frequency space-time distribution. The method aims at solving the problem that no method can aggregate the whole frequency process of the power system without relying on electromechanical simulation under the condition that system parameters are incomplete at present. The method comprises the following steps: firstly, constructing a power disturbance set of a power system, and then calculating initial unbalanced power and initial steady-state frequency of each node of the power system under specific disturbance; based on the initial unbalanced power and the initial steady-state frequency of each node of the power system, alternately calculating the frequency difference and the unbalanced power of each node until each node reaches the uniform steady-state frequency, and obtaining a frequency difference track among the nodes of the power system under specific disturbance; and according to the calculated track of the frequency difference of each node, clustering is carried out according to the track of the frequency difference of each node in each step.

The invention provides an OTFS (Orthogonal Time Frequency Space) channel estimation method based on a bidirectional gating loop unit (BiGRU) and a multi-head attention mechanism, and belongs to the technical field of channel estimation. The method comprises the following steps: determining time delay-Doppler domain parameters according to a channel scene, and constructing a TDL (Tap Delay Line) channel model; designing a time-frequency domain pilot frequency structure; carrying out time-frequency domain modulation on a sending signal and adding high-power amplifier (HPA) nonlinear distortion; obtaining an initial channel state by using LS estimation; a BiGRU network and multi-head attention mechanism joint model is constructed, and channel state prediction is realized through bidirectional time sequence feature extraction and multi-dimensional attention weight distribution; and time delay-Doppler domain channel response reconstruction is completed by using the optimized model. Bidirectional dependency of channel time-varying features is captured through BiGRU, and a multi-head attention mechanism is combined to enhance the key path feature extraction capability, so that the channel estimation precision in a high-mobility scene is remarkably improved, and the influence of HPA nonlinear distortion on the system performance is effectively inhibited.

The invention provides a construction method and system of a non-reciprocal emission / absorption device with a Fizeau dragging effect. The construction method comprises the following steps: selecting a metal substrate, a dielectric grating and a two-dimensional material; applying a bias voltage in the x-axis direction to the two-dimensional material layer to generate a Fizeau dragging effect; the bias voltage is adjusted under TM polarization, so that the electron drift speed is close to the Fermi speed, asymmetric surface plasmon resonance is excited, and unequal emissivity and absorptivity are achieved; an adjustable singular point is generated in an angle-frequency space by adjusting the filling ratio of the grating, so that the numbers of spectral formants of emissivity and absorptivity near the singular point are different, and the wavelength integral nonreciprocity intensity is improved. The non-reciprocal heat radiation characteristic can be realized through voltage regulation and control without an external magnetic field.

The application discloses a large-scale PDE neural operator pre-training method based on a high-frequency enhancement module, a partial differential equation (PDE) data set is composed into a mixed data set, a large-scale PDE neural operator is constructed, preprocessed PDE data is mapped to a latent representation space through a space-time encoder, a frequency decomposition module is used for frequency space mapping, the frequency decomposition module includes parallel high-frequency branches and low-frequency branches, and high-frequency features and low-frequency features are obtained respectively; a multi-frequency fusion module (GFM) adaptively fuses the high-frequency features and the low-frequency features through a gating mechanism; finally, a prediction head is used for processing the fused features, and final output features, i.e., predicted physical features of a next time step, are obtained. The application firstly introduces an explicit frequency division and a high-frequency enhancement mechanism, the input field is divided into low-frequency and high-frequency parts, the low-frequency branches / high-frequency branches are used for processing respectively, and thus the model can simultaneously consider global trend modeling and local gradient detail reconstruction.

The invention provides an orthogonal time-frequency air conditioning communication system demodulation method based on deep learning. The method comprises the following steps: constructing an orthogonal time-frequency air conditioning communication system model and an interference model; according to communication system characteristics and anti-interference requirements, constructing a network structure combined by a convolutional neural network and a bidirectional long-short-term memory network; preprocessing the training data, and performing time sequence alignment on the input data and the label data; inputting the preprocessed data into a CNN (Convolutional Neural Network) to extract local spatial features, inputting the data into a combined network, capturing time-dependent features, calculating a mean square error loss function according to a predicted demodulation bit and a real bit, calculating a network parameter gradient by using a back propagation algorithm, and updating network parameters by using an optimizer according to the gradient; and carrying out model training until expected requirements are met. According to the invention, the advanced neural network architecture is innovatively combined, so that the communication reliability and robustness of the communication system in the interference environment are effectively improved.

The application provides a bridge damage assessment method and system caused by ship collision and a medium, and relates to the technical field of bridge health monitoring. The method comprises the following steps: collecting acceleration response signal arrays of different heights and positions of a bridge pier, and generating a time series matrix; drawing a time-frequency coherence spectrum under different base functions, and obtaining a coherence spectrum entropy; determining the optimal base function based on the information entropy principle; obtaining the local correlation coefficient of the time series matrix in the time-frequency space under the optimal base function, and drawing a time-frequency coherence spectrum; evaluating the correlation and dependence degree between time series according to the local correlation coefficient and the time-frequency coherence spectrum, and judging whether the ship-bridge collision damage occurs; if the collision damage occurs, calculating the time-frequency coherence damage factor of the time series matrix at different positions, and determining the collision position and the collision degree according to the maximum protruding value in the time-frequency coherence damage factor trajectory curve. The method can effectively separate the influence of environmental factors, and provides basic method support for establishing the ship-bridge collision damage assessment technology.

The present invention discloses a low-complex, reliable multidimensional orthogonal time-frequency space (ND-OTFS) modulation-based communication system for uplink and downlink wireless communication between resource-constrained Internet of Things (IoT) and machine-to-machine (M2M) devices comprising at least one transmitter configured to transmit bit stream involving N-Dimensional signal mapper and OTFS frame and at least one receiver configured to be integrated into said IoT or M2M devices, featuring a low-complexity detector for receiving the transmitted bit stream.

The invention discloses a vibration test and state monitoring method and system for an in-operation high-voltage circuit breaker, and the method comprises the steps: carrying out the energy propagation time sequence test of a multi-measurement-point vibration signal, constructing an energy flow direction topological graph, and precisely positioning a vibration source region through energy ratio analysis and path backtracking; acquiring a response time constant by adopting an impact response attenuation test, and converting a vibration source into a fault space positioning coordinate through space grid division and rate matching; a frequency-space mapping relation is established based on a fault position, and vibration characteristics are comprehensively described through peak frequency time sequence tracking and nonlinear component identification such as frequency multiplication, modulation and transient state; performing dispersion analysis on the continuous action impact peak value to form an action consistency deviation, and fusing a nonlinear feature set to quantitatively evaluate the mechanical degradation degree; the grading test density is generated according to the degradation state, the time period test unit is determined, the state grading test benchmark is established to realize mechanical state grade judgment, and the equipment operation reliability and the monitoring efficiency are improved.

The invention relates to a low-complexity OTFS multi-antenna detection algorithm, which belongs to the field of wireless communication, and is characterized in that a transmitting signal of a transmitting end reaches a multi-antenna receiving end through a time-varying multipath channel based on an orthogonal time-frequency-space OTFS modulation system; preliminarily separating received signals from different angles of arrival (AoA) at a receiving end by using a multi-antenna array and beam forming; then, starting from the angles of a time delay-Doppler (DD) domain and a low-complexity delay-time (DT) domain, according to composition of signals in beam forming branches, performing coherent combination on multipath components in each branch through maximum ratio combination (MRC), meanwhile, collecting all branches by the MRC and performing coherent combination, and performing continuous iteration to obtain an optimal estimated value; the result shows that the bit error rate performance of the provided low-complexity DT domain multi-antenna Bi-MRC detection is obviously superior to that of the existing multi-antenna MP-MRC detection, and the number of iterations required for achieving the optimal value and the time consumption of single iteration are greatly reduced.