173 results about "Real signal" patented technology

The invention provides an automatic processing method for real-time observation data of an ocean station, and belongs to the technical field of ocean observation data processing. A wavelet packet decomposition multi-scale noise separation algorithm is established to distinguish environmental noise and real signals, dual-sensor redundancy configuration is combined with Bayesian inference to identify sensor drift, and a calibration coefficient is updated in real time through a recursive least square method. A one-dimensional time sequence is mapped to a high-dimensional phase space by utilizing a phase space reconstruction algorithm to realize high-precision prediction of a chaotic signal, a hierarchical data storage architecture is established, and a data migration strategy is iteratively optimized through a hierarchical correlation degree function; the technical problem that time synchronization signals are difficult to reconstruct accurately according to asynchronous sampling data of multiple sensors of an ocean station is solved.

The invention provides a wind tunnel structure sensitive reflection settlement position intelligent identification method, and belongs to the technical field of wind tunnels. Vibration sensors and displacement sensors are arranged at key positions of a wind tunnel structure to form a monitoring network, collected signals are preprocessed, and a settlement factor matrix is established; a dynamic load matrix is constructed to describe composite load distribution, a vibration burr identification matrix is established, real signals and noise are separated by adopting wavelet transformation, a slow settlement trend matrix is constructed to extract a long-term change rule, and a least square optimization algorithm is adopted to jointly solve each matrix parameter to establish a settlement position identification function. The settlement three-dimensional position coordinate is determined according to the multi-sensor data fusion result, the structure safety state is evaluated through the settlement risk coefficient, and the technical problems that the wind tunnel structure settlement position recognition precision is insufficient, and a real settlement signal and a noise interference signal cannot be effectively distinguished are solved.

The invention discloses a signal reconstruction and noise suppression method and system for a distributed Raman temperature measurement sensing system, and the method comprises the steps: obtaining original anti-Stokes light and Stokes light time domain signals of the distributed Raman temperature measurement sensing system, and constructing a space-time signal matrix; performing preprocessing and data enhancement on the space-time signal matrix; constructing a dual-path feature fusion network for Raman signal reconstruction and noise suppression, and initializing the network; defining a loss function fusing temperature physical constraints, and training the dual-path feature fusion network; and inputting an original Raman signal to be processed into the trained network, outputting the reconstructed anti-Stokes and Stokes signals with the high signal-to-noise ratio, and carrying out temperature demodulation according to the anti-Stokes and Stokes signals with the high signal-to-noise ratio. While the spatial resolution is maintained or improved, the noise of the Raman temperature measurement system is effectively suppressed, especially the real signal of a temperature abrupt change point can be recovered, the temperature demodulation precision, stability and reliability are improved, and reliable data are provided for infrastructure safety monitoring.

The invention relates to the technical field of laser radar wind field inversion, in particular to a coherent Doppler anemometry laser radar-based three-dimensional wind field inversion method, which comprises the following steps of: acquiring original power spectrum data of an anemometry laser radar to be inversed in each direction, and sequentially performing interpolation processing on the original power spectrum data in each direction to obtain an inversion result; obtaining power spectrum data after interpolation in each direction; calculating to obtain a cumulative power spectrum function; and optimizing the obtained vector three-dimensional wind field by using the cumulative power spectrum function so as to calculate the maximum function value of the cumulative power spectrum function, and the three-dimensional wind field corresponding to the maximum function value is the optimal three-dimensional wind field. According to the method, all the power spectrum data after azimuth interpolation are directly processed as a whole, random noise is averaged by using an accumulation process, a real signal is highlighted, and stable and accurate three-dimensional wind field inversion can be realized even when the signal-to-noise ratio is extremely low.

The invention discloses a blind signal source separation method based on a multi-resolution attention separation network, and belongs to the technical field of signal processing. The method comprises the following steps of signal preprocessing, multi-scale feature extraction, attention module training, multi-resolution feature fusion, signal source recognition model training, model performance real-time monitoring and multi-scene adaptation optimization, and microcosmic and macroscopic features of signals are effectively captured through a multi-scale channel feature coding network. The adaptability of the model to non-stationary signals and complex structure signals is enhanced, the separation precision is improved, the attention mechanism can dynamically adjust feature weights, highlight target signal features, suppress background noise and remarkably improve the signal separation quality, meanwhile, calculation resource allocation is optimized, the model reasoning time is shortened, and the method is suitable for large-scale popularization and application. The MRAS-Net adopts a classification-oriented consistency synthesis strategy to ensure that the synthesized virtual signal features and the real signal features are highly consistent in classification tasks, and the generalization ability and the result interpretation of the model are enhanced.

The invention provides an industrial single-chip microcomputer automatic control method based on time sequence event triggering, and the method comprises the steps: carrying out the multi-period sampling and time window division of an original signal inputted by an industrial field sensor or a switching value, and extracting the time distribution characteristics of the signal; performing signal stability judgment and pseudo edge elimination based on the signal time distribution characteristics, and outputting a stable edge event set; performing event confirmation delay and multi-level logic judgment on the stable edge event set to generate a preliminary time sequence trigger signal; environment characteristic data are collected, real-time feedback of an actuator is obtained, and system judgment parameters are dynamically corrected; and generating a control command and verifying an execution result based on the preliminary time sequence trigger signal and actuator feedback, the method can dynamically distinguish real signals and noise under vibration interference, simultaneously ensures the real-time performance and trigger reliability of the system, and solves the problems of insufficient edge detection stability and false trigger phenomenon caused by mechanical vibration.

The invention relates to the technical field of image processing and extremely weak light imaging, and particularly provides a photon counting image reconstruction method and system, and the method comprises the steps: determining a target threshold value based on the adjustment of a dynamic adjustment coefficient under different illumination or gain conditions based on an initial threshold value; counting a first photon number of a single photon signal in the background image and a second photon number of the single photon signal in the signal image based on a target threshold, and generating noise photon number statistical distribution and signal photon number statistical distribution to determine a dynamic photon number processing interval; and performing time-space joint accumulation on the pixels conforming to the dynamic photon number processing interval, generating a two-dimensional photon accumulation matrix, and converting the two-dimensional photon accumulation matrix into a gray level image to form a single group of reconstructed gray level images. According to the method, real signals can be effectively extracted, the influence of dark noise, shot noise and readout noise is suppressed, zero noise detection is realized, and finally, the dynamic range, the signal-to-noise ratio and the stability of the image are remarkably improved through single-group image reconstruction and multi-group integration processing.

The invention discloses an AI-based power distribution equipment partial discharge online diagnosis and positioning method, which relates to the technical field of equipment detection, and comprises the following steps: acquiring high-frequency signals in power distribution equipment in real time, sequentially calculating a topological inconsistency index, an echoing characteristic response abnormal index and a burst pulse ring chaos index, and calculating a false index based on the three results, so as to realize the partial discharge online diagnosis and positioning of the power distribution equipment. The method is used for judging whether the signal is a real signal generated by partial discharge of equipment. And if the false index is lower than a threshold value, determining that the discharge signal is a real discharge signal, and performing type identification and accurate positioning through a preset AI model. According to the method, non-discharge interference signals can be effectively identified, the fault judgment accuracy is improved, the false alarm rate is reduced, the trust of operation and maintenance personnel on a system diagnosis result is enhanced, the manual inspection pressure is relieved, and the maintenance cost is reduced.

The invention relates to the technical field of automobile power system testing, in particular to a dynamometer and HIL integrated finished automobile multi-working-condition automatic testing and calibrating system, which combines a dynamometer rack with a hardware-in-the-loop simulation technology, develops a dynamics scene model covering conventional and limiting working conditions, and improves the testing accuracy of the dynamometer rack and the hardware-in-the-loop simulation technology. The conversion and interaction of virtual and real signals are realized through road load simulation and energy consumption simulation; the dynamometer and HIL integrated whole vehicle multi-working-condition automatic test calibration system is composed of IO, DOE, automatic calibration, objective evaluation and other functional modules, can automatically execute test cases, complete parameter calibration and optimization analysis, and perform objective evaluation on test results, and can realize multi-working-condition test, reduce the dependence on real vehicle road test, improve the test efficiency and comprehensiveness, and reduce the test cost. The controller development period is shortened, and the cost is reduced.

The invention relates to the technical field of electroencephalogram signals, in particular to a method, a device and equipment for removing motion artifacts of electroencephalogram signals, and the method can obtain to-be-processed electroencephalogram signals, decompose the electroencephalogram signals into a plurality of mutually orthogonal intrinsic mode components by utilizing multivariable empirical mode decomposition, and obtain motion artifacts of the electroencephalogram signals. The real electroencephalogram signal and the artifact signal are decomposed into different components; standard mutual information between each intrinsic mode component and a preset class label is calculated; multiplying the standardized mutual information by a corresponding intrinsic mode component to obtain an optimized signal component, so that a component related to a real signal is enhanced, and an artifact signal is weakened; all the optimized signal components are accumulated, and the electroencephalogram signals with the motion artifacts removed are obtained. It can be understood that according to the technical scheme shown by the invention, through multi-level and multi-dimensional signal decomposition and artifact removal processing, the motion artifacts can be accurately recognized and removed, and the quality of the electroencephalogram signals is greatly improved.

The invention discloses a medical signal generation method and system based on a time-frequency double-domain constraint generative adversarial network. According to the method, a multi-category electrocardiosignal generation model is designed on the basis of a conditional generative adversarial network, global attention interaction is carried out by utilizing a learnable potential feature prototype and position-coded signal features through an adaptive neural representation module, and long-distance time sequence dependence of electrocardiosignals is modeled; through the adaptive spectrum sensing module and the dynamic mask mechanism of energy sensing, the discriminator intensifies the discrimination of the consistency of signal frequency domain information while paying attention to the time domain form, thereby effectively inhibiting the non-natural high-frequency artifacts in the generation process, and ensuring the high fitting of the generated signal and the real signal. Experiments show that the fidelity and diversity of generation of various types of electrocardiosignals can be remarkably improved.

The application discloses a kind of under the condition of aviation engine inter-shaft bearing fault diagnosis method of class imbalance based on Cycle-GAN, and its specific include: data acquisition and pre-processing, improvement and establish Cycle-GAN model, train improved Cycle-GAN model and complete signal conversion, complete the fault diagnosis of actual vibration signal by Cycle-GAN model.The application proposes a new fault diagnosis transfer learning method based on Cycle-GAN, by improved Cycle-GAN model, signal sample under known condition is converted into new signal sample under unknown condition, provide the conversion signal of data distribution closer to real signal, while also ensure that conversion signal retains the fault category information in original signal, solve the problem of fault data scarcity in actual scene, and use conversion signal to train classifier, so that the classifier can distinguish fault data under unknown condition.In practical engineering application, especially in the problem of aviation engine inter-shaft bearing fault diagnosis under the condition of class imbalance, the application has wide application prospect.

The application relates to a medical imaging system, a medical imaging method and a computer readable storage medium. The method comprises the following steps: obtaining first projection data by detecting radioactive rays passing through a first scanning field of view, and simultaneously detecting a part of radioactive rays in radioactive rays not passing through the first scanning field of view but passing through a second scanning field of view to obtain second projection data, wherein the second scanning field of view is larger than the first scanning field of view, and the first scanning field of view is located in the second scanning field of view; obtaining third projection data corresponding to the second scanning field of view based on the first projection data and the second projection data; and reconstructing a tomographic image in the second scanning field of view based on the third projection data. Through the application, the problem that the signal in the extended scanning field of view obtained by speculation is greatly different from the real signal in the related art is solved, and the reconstruction quality of the computer tomographic image is improved.

The application provides a signal predistortion processing method and device, electronic equipment and storage medium, and relates to the technical field of communication. The method comprises the following steps: firstly, calculating predistortion complex array by a memory polynomial model based on historical baseband data and historical baseband feedback data; then, applying the predistortion complex array to a baseband signal to generate an in-phase component signal and a quadrature component signal containing amplitude and phase predistortion information; then, respectively performing carrier modulation on the in-phase component signal and the quadrature component signal to obtain an in-phase branch signal and a quadrature branch signal; then, calculating a predistortion real signal based on the in-phase branch signal and the quadrature branch signal; and finally, performing carrier modulation on the predistortion real signal to obtain an up-converted signal. The technical scheme provided by the application solves the technical problem that phase predistortion information cannot be preserved in the signal predistortion process.

The invention discloses an insect flapping frequency inversion method based on initial phase calculation, and relates to the technical field of radar measurement. The method comprises the following steps: establishing an insect flapping motion radar echo model containing an amplitude initial phase and a phase initial phase, and obtaining a micro-motion signal from collected insect echoes based on the insect flapping motion radar echo model to generate a micro-Doppler spectrogram; based on the micro-Doppler spectrogram, calculating an initial phase value of the phase of the insect flapping wing, and based on the initial phase value, constructing a phase compensation factor to obtain a flapping wing parameter plane; and detecting an energy peak value in the flapping parameter plane based on the phase compensation factor, and determining the flapping frequency of the insect based on the position of the energy peak value. According to the method, the phase initial phase and the amplitude initial phase are introduced, the double physical processes of wing movement and body micro movement during insect flapping are restored, a radar echo model is highly matched with a real signal generation mechanism, errors are reduced, and the anti-interference capability is improved.

Disclosed is a method for determining area (202) in which attenuation object (204) is located in space (206), wherein space is divided to finite elements (210, 210a-d). The method comprises providing first transmitter (208, 302) to transmit radio signal with first strength value; moving measurement device (212, 304) along first path (214) and a plurality of real signal strength values at interest-locations (216a-b) along the first path; calculating theoretical signal strength value, for each of the interest-locations of the first path, using radio signal propagation model assuming a free propagation between the first location and the interest-locations; setting attenuation value for each of the finite elements, along lines (218a-b) connecting the first location and the interest-locations; and using locations of the finite elements with the non-free space attenuation value to determine the area in which the attenuation object is located.

The invention provides a tire vertical force estimation method and system, electronic equipment, a medium and a program product, and relates to the technical field of vehicles. According to the tire vertical force estimation method, radial acceleration signals are screened based on a sliding time window with a preset length, so that abnormal radial acceleration signal segments existing in the radial acceleration signals are removed; furthermore, a local minimum value point smaller than a radial acceleration threshold value is identified in the target radial acceleration signal based on the radial acceleration threshold value, so that real signal characteristics representing the tire grounding physical process can be effectively distinguished from false fluctuations caused by various environmental noises and system inherent noises; the misjudgment of false negative peak extreme points is obviously inhibited, the accuracy of the negative peak extreme points is improved, and the accuracy and robustness of the estimation of the vertical force of the tire are further improved.

The invention discloses a low-complexity signal-to-noise ratio estimation method and device, and relates to the technical field of coherent optical communication, and the method comprises the steps: employing a modulation mode to map a signal to a constellation diagram in a communication link, and extracting a to-be-estimated real number signal from a received signal according to a preset signal-to-noise ratio estimation mode; judging the real number signal to be estimated according to an estimation mode to obtain a positive signal and a negative signal; carrying out addition and subtraction operation on the positive and negative signals respectively and carrying out modulus averaging to obtain a noise modulus value of linear representation; and inputting the noise module value into a preset lookup table, and combining a log value of a known signal module value to obtain a signal-to-noise ratio estimation value based on logarithm representation. According to the method, multiplication is completely removed, the complexity is greatly reduced, iteration is not involved in the table look-up process, so that the complexity is very low, the estimation precision can be freely set according to the size of the table, and the flexibility is high.

The invention discloses a direct-current-bias-free high-power LED visible light signal transmission method and system, and relates to the technical field of optical communication, and the method comprises the steps: carrying out 64QAM-OFDM modulation and IQ modulation on original audio and video data, carrying out AC coupling peak-to-peak value extraction and DC component filtering, and then carrying out single-power-supply amplification and pre-equalization; and a driving positive voltage signal is generated to drive a high-power LED to emit light, and an optical communication signal is generated. Through a low-loss alternating-current coupling transmission mode, the modulated real signal peak-to-peak value is subjected to coupling transmission and single positive power supply amplification, so that the signal is changed into positive voltage to control the LED light intensity and form an LED optical communication signal, direct-current voltage does not need to be introduced into a digital domain, the problem of bandwidth reduction is avoided, and the signal transmission efficiency is improved. The direct-current bias voltage of the LED can be kept stable, the LED works in a linear modulation area, bandwidth expansion is carried out through the pre-equalization circuit, and the functions of LED illumination and high-speed communication can be considered.

The invention discloses a Beidou B1I signal pseudo-range simulation method based on time synchronization, which relates to the technical field of satellite navigation, and realizes time synchronization initialization by initializing effective signal triggering, loading initial parameters, detecting a rising edge of a time reference source, starting delay counting and automatically activating signal enabling when an alignment delay threshold value is reached; the C / A code time sequence precision and the dynamic adaptability are guaranteed through two time sequence control, the precision of the pseudo-range calculated based on the C / A code is guaranteed by calculating the convergence pseudo-range, and the pseudo-range dynamic generation is realized; and finally, the analog C / A code and the navigation message are modulated to a carrier after being subjected to XOR, analog satellite signals are generated through digital-to-analog conversion, and signal modulation and output are achieved. According to the invention, navigation signals completely consistent with real signals can be provided in an environment without real satellite signals, the blank in the prior art is filled, and the reliability and applicability of a positioning system are improved.

The application discloses a kind of based on dual three-dimensional memory hyperchaos SCMA-OFDM transmission system, the system includes sending end and receiving end, the user of sending end possesses respective codebook, J user shares K subcarrier, initial bit information and after the calculation of hyperchaos model of memristor triangle mapping chaotic codebook enter SCMA encoder and carry out codebook mapping processing, obtain encrypted SCMA-OFDM signal, for carrier synchronization, it is inserted pilot, after pilot, obtain frequency domain signal and information data using fast inverse fourier transform after the calculation of hyperchaos model of memristor triangle mapping, frequency domain signal is changed into time domain signal;Then to time domain signal is increased cyclic prefix CP and cyclic suffix CS to eliminate intercarrier interference, then parallel-serial conversion parallel signal is changed into serial signal, finally through up-conversion DUC complex signal mixing becomes real signal into transmission channel.The transmission system of regular hexagon chaotic codebook, its performance is improved by 2.5dB than traditional codebook.

The invention discloses a non-invasive-minimally invasive electroencephalogram signal recording method for deep brain region activity, which comprises the following steps: acquiring a deep electroencephalogram real signal and a first superficial electroencephalogram signal collected by a subject in a first time period and in a minimally invasive state; the second superficial layer electroencephalogram signals are collected by the tested body in a second time period and in a non-invasive state; performing model calibration on the initialized electroencephalogram signal prediction model according to the deep electroencephalogram real signal and the first superficial electroencephalogram signal to obtain a calibrated electroencephalogram signal prediction model; inputting the second superficial layer electroencephalogram signal into the calibrated electroencephalogram signal prediction model for deep prediction to obtain a deep layer electroencephalogram prediction signal of the subject in a second time period; and obtaining deep electroencephalogram record data according to the deep electroencephalogram real signal and the deep electroencephalogram prediction signal. According to the method, the integrity and safety of deep electroencephalogram signal recording can be effectively improved. The invention relates to the technical field of electroencephalogram signal processing.

Polar transmitter calibration Various embodiments relate to a transmit and receive system using polar modulation, including: a transmitter configured to produce a transmit signal using modulation; a receiver configured to receive a transmit signal using in-phase / quadrature (IQ) processing; a Tx / Rx switch configured to loop a transmitted signal from the transmitter back to the receiver for calibration; and a controller configured to: command the transmitter to generate a real signal; command the Tx / Rx switch to loop the real signal back to the receiver to produce a first received signal; command the transmitter to generate an imaginary signal; command the Tx / Rx switch to loop the imaginary signal back to the receiver to produce a second received signal; determine a compensation parameter based on the first received signal and the second received signal; and command the receiver to compensate a third received signal based upon the compensation parameter.

The application relates to the fields of big data processing and aero-engine monitoring, and discloses a UAV engine state evaluation method and system based on digital twinning. The method comprises the following steps: collecting and preprocessing engine operation data; constructing a decoupled cloud macroscopic operation domain twin and an airborne microscopic mechanism domain twin, and hard-coding a physical conservation law into an airborne hybrid evaluation model; introducing a fault injection and adversarial generation mechanism to construct an adversarial game logic of virtual faults and real signals; triggering a meta-learning mechanism based on feature difference signals to perform small sample incremental fine-tuning on the model; and performing cloud-edge collaborative decision and state synchronization according to the confidence. The system comprises data acquisition, double-layer twin construction, adversarial generation evolution and cross-domain collaboration modules. The application improves the system robustness and fault prediction capability through mechanism and data double constraints.

The invention discloses a three-path coprime spectrum driven broadband spectrum detection method and device, and belongs to the technical field of broadband electromagnetic spectrum sensing. The method comprises the following steps: carrying out undersampling on a real signal by adopting a three-path coprime sampling rate, and obtaining three paths of branch spectrums with different resolutions through multi-phase filtering, IDFT (Inverse Discrete Fourier Transform) and cross-correlation operation; and after the resolution is unified through up-sampling, adaptive merging judgment is carried out by using saliency measurement based on spectrum similarity, and a real spectrum peak and an aliasing false peak are effectively distinguished. The device core comprises a radio frequency front end, a three-channel low-speed ADC and a digital signal processing platform. According to the method, pseudo-peak-free panoramic spectrum sensing in the frequency band of 300MHz-10GHz under the under-sampling condition is realized, and the method has the advantages of low hardware complexity, high engineering feasibility, high robustness to dense signals and the like, and is particularly suitable for non-cooperative electronic reconnaissance scenes.

The application relates to a satellite navigation deception method, system and device based on an intelligent metasurface. The method comprises the following steps: deploying a single or multiple RIS modules fixed on a mobile or fixed carrier between a navigation satellite and a target receiver; according to the ability of the RIS module to reflect or transmit a navigation frequency band signal, using the RIS module to receive and forward a single or multiple real navigation signals, changing the propagation path of the real navigation signal, without storing and processing the navigation signal, and the deployment complexity and cost are low. Furthermore, a signal processing model is constructed according to the signal obtained by the target receiver, and the signal forwarding beam of the RIS module is controlled through the signal processing model, so that the target receiver in a certain area receives a forwarding signal power greater than a real signal power, and the success rate of navigation deception is improved.

The invention discloses a time-frequency consistency electroencephalogram signal generation method and system based on distance constraint. A composite loss function containing three losses of time-distance coupling, frequency-distance coupling and phase synchronization is designed. Time-distance coupling loss is weighted according to the distance between the electroencephalogram virtual channel and the source channel, and the consistency of signals of the electroencephalogram virtual channel far away from the source channel and real signals in the time domain is enhanced; frequency-distance coupling loss, amplitude consistency between an electroencephalogram virtual channel signal with a short strengthening distance in a low frequency band and a real signal, and frequency consistency between an electroencephalogram virtual channel signal with a long strengthening distance in a high frequency band and the real signal; according to the phase loss item, the phase synchronism is strengthened in a specific frequency range for the task state electroencephalogram signals, and the method is suitable for a task state scene. According to the method, the time-frequency domain consistency, the channel distance and the task state phase coherence of the generated signals are fully considered, and the signal generation quality of the electroencephalogram virtual channel (especially the far end) is effectively improved.

The application discloses a parameter setting method, device and system for a swing reactance of an excitation regulator, wherein the parameter setting method adds forced oscillation to a speed regulator link in a closed-loop simulation test environment, so as to stimulate equal-amplitude oscillation of mechanical power and unit frequency in a set frequency range; the error between a real signal value output by a real excitation device and a simulation signal value output by a simulation test model is calculated, the initial value of the swing reactance parameter is selected according to the error, the adaptability and effectiveness of the swing reactance are verified based on the initial value, the test result is obtained through a voltage step test under a set working condition, and the swing reactance parameter is modified according to the test result, so that the active power fluctuation when the PSS is put into operation meets the set condition. The parameter setting method provided by the application can reduce the risk of power oscillation accidents caused by large unit speed calculation error due to unreasonable swing reactance parameter setting and weak damping or even negative damping of the PSS.

The invention belongs to the field of airborne interference imaging altimeter error correction, and particularly relates to a platform and baseline error correction method based on an airborne interference imaging altimeter, which comprises the following steps of: acquiring a height measurement data sequence X1 continuously acquired along a flight path; preprocessing the X1 to obtain a preprocessed data matrix X2; performing empirical orthogonal function decomposition on the X2 along the rail direction, and extracting a spatial mode, a time coefficient and a characteristic value; determining a main characteristic mode according to a variance contribution rate corresponding to the characteristic value; identifying and separating a platform error component, a baseline error component and a real height signal component by combining distribution characteristics of a space mode and a time coefficient; and reconstructing a real height signal based on a separation result to realize comprehensive correction of a platform error and a baseline error. According to the method, the platform error and the baseline error which are different from real signals in space-time characteristics are effectively separated through EOF decomposition, and the height measurement precision of the airborne interference imaging altimeter is remarkably improved.

The application relates to a communication method and device. A first root is determined, wherein when a frequency offset of an LP-SS corresponding to the first root is less than or equal to a first value, an equivalent time domain offset of the LP-SS is greater than a first threshold. A first LP-SS is sent or received, the first LP-SS being determined according to a first ZC sequence, and the first ZC sequence being determined according to the first root. Due to the first root satisfying the characteristic, among the correlation peaks corresponding to the first LP-SS, the correlation peak corresponding to the real signal can fall within the range of a detection window, so that the signal receiving end can successfully demodulate, the demodulation success rate of the first LP-SS is improved, and the time-frequency synchronization performance is improved.