56 results about "Pulse noise" patented technology

The invention relates to the technical field of rolling bearing fault diagnosis, in particular to a rolling bearing fault diagnosis method based on data fusion and a neural network, and the method comprises the steps: S1, collecting vibration data of a plurality of sensors, superposing Gaussian white noise and pulse noise, and simulating a strong noise industrial environment; s2, extracting time domain and frequency domain features of vibration signals of each sensor, and constructing a preliminary feature matrix; s3, performing noise reduction processing and depth feature extraction on the feature matrix by using SDAE, fusing to generate a bearing data set, and dividing a training set and a test set; and S4, inputting the training set into an Adam optimization-based fractional order GRU model for training, and verifying the trained model by using the test set. According to the rolling bearing fault diagnosis method, the precision and robustness of rolling bearing fault diagnosis in a strong noise environment are remarkably improved by fusing the multi-source sensing data and the fractional order neural network model.

The invention particularly relates to a voice noise reduction method suitable for different noise environments, and relates to the technical field of voice signal processing. Analyzing a noise environment and characteristics; adaptive selection of a noise reduction algorithm; adaptive noise reduction processing is executed; and noise reduction effect evaluation and iterative optimization are carried out. According to the invention, refined noise classification is matched with the algorithm, so that the limitation of a traditional single algorithm in a complex environment is solved; the steady-state noise is dynamically counteracted by adopting an adaptive filter, the frequency domain gain of the unsteady-state noise is adjusted in real time through Wiener filtering, and the pulse noise is subjected to dynamic threshold processing by combining median filtering and wavelet transform; especially, the design of cooperation factors in wavelet transform can accurately distinguish signal details and noise: intensively suppress pulse noise, loosely retain details such as voices and consonants, and realize dynamic balance of noise reduction intensity and signal distortion.

The invention discloses a laser echo pulse noise suppression method based on dynamic double thresholds and an embedded system, belongs to the technical field of laser signal processing, and aims to solve the problem that strong pulse noise suppression and effective signal protection are difficult to balance in the prior art. The method comprises the following steps: acquiring a frame of digital signal sample; calculating a median value M and an absolute deviation mean value MADM of the sample; determining a dynamic high threshold TH and a low threshold TL based on M and MADM; and traversing each sampling point, and performing grading processing according to the relationship between the amplitude and the double thresholds: applying first noise suppression processing to the sampling point with the amplitude higher than TH, applying second noise suppression processing to the sampling point with the amplitude between TL and TH, and keeping the original value of the sampling point with the amplitude not higher than TL. The invention also discloses an embedded system for realizing the method. According to the invention, the pulse noise can be adaptively and accurately suppressed, the signal integrity is effectively protected, and the signal-to-noise ratio and the system robustness are improved.

The invention discloses a data fusion method and processing system based on the industrial internet, and relates to the technical field of industrial internet and edge intelligence. Stream segmentation processing is used for replacing global calculation, mutual information analysis and resampling are only carried out on latest data segments, time consumed by alignment of hundreds of data streams is compressed to a millisecond level, and the data fusion efficiency is improved. The real-time control requirement of the flexible production line is met; the dynamic offset generation is combined with the equipment sampling rate, the communication protocol and the type weight, the compensation intensity is adaptively adjusted, and alignment distortion caused by equipment heterogeneity is avoided; a noise perception mechanism is introduced, a gradient median and absolute deviation are utilized to construct a self-adaptive threshold value, pulse noise points are accurately marked, weight penalty is applied, the integrity of fault features is kept while interference is suppressed, and signal smoothness caused by traditional filtering is prevented; tensor decomposition under a federated learning framework supports distributed data privacy protection, and a noise suppression module preposed design avoids pollution to a core feature extraction process.

The invention relates to the technical field of communication, in particular to a signal detection method and system based on Gini gamma correlation coefficient matrix eigenvalues. The method comprises the following steps: acquiring signals received by multiple paths of sensors, and calculating rank statistics of each path of received signal; calculating Gini gamma correlation coefficients of any two paths of received signals to form a correlation coefficient matrix; obtaining characteristic values of the Gini gamma correlation coefficient matrix, and calculating a geometric mean value and an arithmetic mean value of the characteristic values; constructing test statistics based on the ratio of the geometric mean value to the arithmetic mean value; comparing the test statistic with the detection threshold to complete the detection process; according to the method, the influence of a large abnormal value in the pulse noise is effectively suppressed through Gini gamma correlation transformation, the test statistic constructed based on the ratio of the geometric mean value to the arithmetic mean value of the characteristic values shows excellent robustness in a pulse interference environment, and the signal detection performance is remarkably improved; signal detection can be carried out under background noise containing pulse components.

The invention discloses an aircraft fuel quantity measurement self-adaptive filtering method, system and device based on multi-dimensional statistic dynamic adaptation and a medium. The method comprises the following steps that S01, signals are collected and preprocessed; dividing a fuel quantity digital signal output by a sensor into continuous time blocks according to a fixed time window; s02, calculating a multi-dimensional statistical magnitude; comprising the mean value, variance and kurtosis of the current time block; s03, performing multi-stage filtering processing; s04, performing data fusion and conversion; and keeping the original value of the data pulse point, and combining the original value with the fine filtering result of the non-pulse point to obtain a complete filtered signal. By monitoring the multi-dimensional statistical characteristics (mean value, variance and peak value) of a fuel quantity signal in real time and combining a coarse filtering-pulse detection-fine filtering multi-stage structure, filtering parameters are dynamically adjusted, efficient suppression of mixed noise (low-frequency shaking, Gaussian noise and pulse noise) is achieved, and the precision of fuel measurement under complex working conditions is improved.

The application relates to the technical field of power line carrier communication, and discloses a PLC signal pulse noise processing method and device and communication equipment, the method comprising the following steps: acquiring a current time domain signal collected by a current sampling point; slidingly buffering the current time domain signal into a buffer window, the buffer window comprising a plurality of buffer positions arranged continuously, and each buffer position storing a time domain signal; judging whether there are continuous target time domain signals of a preset number on any side of a target buffer position, the target buffer position being one of the plurality of buffer positions and being used for outputting a time domain signal of the sampling point, and the target time domain signal being a time domain signal with a signal strength greater than or equal to a preset threshold; and processing the time domain signal output by the target buffer position according to the judgment result. According to whether the signal strength of the continuous number of time domain signals is greater than the preset threshold, the time domain signal output from the specific buffer position in the buffer window is processed, the misjudgment can be reduced, and the signal quality is improved.

The invention discloses an underwater acoustic anti-interference transmission method and system based on sparse time-frequency characteristic mapping, and the method comprises the steps: adaptively generating a fractional order linear frequency modulation waveform with a specific time-frequency shearing slope at a transmitting end according to the Doppler state of an underwater acoustic channel, and achieving the physical layer focusing of transmitted energy; at a receiving end, constructing a hybrid observation model comprising a wide block sparse channel component and a narrow block sparse burst noise component, and inferring posterior probability distribution of environmental burst noise in a fractional order domain through joint iteration by using a dual-channel variational Bayesian algorithm; and finally, recovering an original signal through soft threshold interference cancellation and fractional order channel equalization. Through active feature mapping of the waveform and heterogeneous sparse joint inference of the receiving end, the problem of communication failure caused by underwater acoustic high-dynamic Doppler diffusion and marine organism impulse noise interference is effectively solved, and the transmission reliability in a severe underwater acoustic environment is remarkably improved.

The invention provides a vehicle-mounted pantograph-catenary temperature detection method and device, and the method comprises the steps: collecting an initial infrared image set containing a target train related pantograph-catenary through an infrared imaging device disposed at the roof of a target train; screening the initial infrared images contained in the initial infrared image set based on a pre-trained definition recognition model to obtain a to-be-processed infrared image set; based on a pre-trained noisy point elimination model, processing the to-be-processed infrared images contained in the to-be-processed infrared image set to obtain a target infrared image set; and according to the target infrared image set, determining the pantograph-catenary temperature associated with the target train. Automatic pantograph-catenary temperature monitoring is achieved, and the influence on the temperature monitoring process caused by the problems of image blurring, quality reduction, isolated pulse noise points and the like due to train movement is avoided.

The application provides an echo cancellation method and system based on a non-standard FIR structure, and relates to the technical field of telephone communication.The method comprises the following steps: sampling a far-end signal to obtain a discrete value of the far-end signal; filtering an input vector of an adaptive filter at a current time through the adaptive filter to obtain an output vector; wherein the adaptive filter is a non-standard FIR filter, and a tap weight coefficient of an i-th tap of the non-standard FIR filter is calculated at an n-i time; obtaining a near-end sampling signal at the current time, subtracting the near-end sampling signal from the obtained output vector to obtain a residual signal at the current time, and returning the residual signal to the far-end; updating a tap weight coefficient vector of the adaptive filter, and repeating the above steps until the call is ended.The application can reduce the error of echo cancellation in a pulse noise environment.

The application provides a high-degree-of-freedom DOA estimation method based on a mirror image co-prime array in a pulse noise environment, and relates to the technical field of array signal processing, and comprises the following steps: S1: obtaining an observation signal by relying on non-circular signal characteristics; S2: calculating a pseudo-covariance matrix based on the information of the observation signal and a square-based correlation entropy operator to suppress the pulse noise; S3: vectorizing the pseudo-covariance matrix to obtain a virtual vector, removing redundant rows in the virtual vector, and performing truncation and sorting according to positions corresponding to continuous virtual array elements to obtain a virtual array receiving signal; S4: performing spatial smoothing on the virtual array receiving signal to obtain a full-rank reconstructed covariance matrix; S5: obtaining a noise subspace by performing eigenvalue decomposition on the covariance matrix; and S6: obtaining an accurate DOA estimation value by performing spectral peak searching on the noise subspace by using a MUSIC algorithm. The method has a high degree of freedom, can accurately complete DOA estimation in a pulse noise environment, and has good performance.

The method comprises the following steps: dividing real-time ocean noise time domain data of a polar region into a plurality of observation time periods, calculating a kurtosis value of each observation time period, further dividing each observation time period into a plurality of short time periods, and calculating short-time energy of each short time period; if the kurtosis value of the observation time period is greater than a threshold value and the short-time energy of a short time period in the observation time period is greater than an average value, judging that pulse noise exists in the observation time period, extracting a pulse noise signal, detecting a pulse event in the pulse noise signal, and taking a key parameter of the pulse event as a feature extraction result; and for an observation time period without pulse noise, acoustic characteristics of background noise without pulse are extracted through a frequency domain method and characteristic parameters. Through signal separation and feature extraction, the data transmission quantity is remarkably reduced, the transmission efficiency and the effective information quantity of the data are improved, meanwhile, the noise detection accuracy is improved, the polar region severe environment can be better adapted, and the requirement for long-term monitoring is met.

The invention discloses a transmission optimization method and device and related equipment, and belongs to the technical field of power line carrier communication. The transmission optimization method is applied to a first device, and comprises the following steps: carrying out pulse noise monitoring on a channel to obtain first channel state information, and carrying out white noise monitoring on the channel to obtain second channel state information; determining diversity mode parameters according to the first channel state information, and determining modulation mode parameters according to the second channel state information; and according to the communication transmission parameters, generating a first frame, and sending the first frame to the second device, the first frame being used for indicating the second device to communicate based on the communication transmission parameters, the communication transmission parameters comprising diversity mode parameters and modulation mode parameters. According to the method, the accuracy of channel state evaluation is improved by jointly monitoring the white noise and the pulse noise, the diversity times and the modulation mode are dynamically adjusted according to the channel state, collaborative optimization of the diversity times and the modulation mode is achieved, and the method can be applied to interference complex scenes.

The application relates to the technical field of communication interference elimination, in particular to a pulse interference elimination method for a power carrier communication chip, which comprises the following steps: acquiring carrier signals of each communication node in a power carrier communication network and the length of a power line between any two communication nodes; acquiring suspected pulse noise points; calculating pulse noise weights of the suspected pulse noise points; intercepting each suspected pulse signal in the carrier signal; obtaining a pulse noise spectrum diagram of each communication node; calculating line loss ratios between any two communication nodes; obtaining a comprehensive pulse spectrum diagram of each communication node; calculating an attenuation ratio of each frequency position; obtaining a noise suppression spectrum diagram; and obtaining a carrier signal after noise suppression based on the noise suppression spectrum diagram, so as to eliminate pulse interference in the carrier signal. The application dynamically filters the frequency domain characteristics of the carrier signal, and improves the communication quality of the power carrier communication chip.

The invention discloses a method and system for suppressing non-pulse noise to accurately measure pulse arrival time, and the method comprises the steps: S1, generating pulsar simulation parameters which comprise a rotation period P, a flow density S1250 and a pulse arrival phase delay standard deviation sigma delta p; s2, constructing a pulsar standard contour Q (x), and generating based on a pulse contour type Ptype, a sub-pulse number and a sub-pulse contour shape; s3, simulating multi-epoch observation data, injecting noise, adding phase delay delta p, and generating an average contour q (x); s4, judging a pulse region: positioning a candidate pulse region through baseline identification, and screening a final pulse region according to a contour type; s5, calculating a phase difference delta x between the standard contour and the average contour by using a phase gradient method; and S6, comparing a difference value between the phase difference delta x and the analog phase delay delta p, and verifying whether higher timing accuracy is obtained by removing the noise in the non-pulse region or not. The pulsar timing precision is remarkably improved by reducing noise interference in a non-pulse area, and the pulsar timing method is suitable for a high-precision scientific target.

The present application relates to a kind of free weight training monitoring method using wearable PPG sensor, belong to mobile computing application and human training auxiliary technical field.The present application uses infrared light and green light on PPG sensor to irradiate wrist skin, and collects the optical density change data containing muscle movement information.By analyzing change data, the load weight currently used by exerciser, the number of repetitions and the type of movement are obtained, and further predict the adjusted load weight required in next step.The present application proposes a novel arterial noise elimination method, effectively reduces the influence of pulse noise in artery, designs a novel feature extraction method based on recurrence plot, maps each action segment to two-dimensional phase space to extract space-time features, and constructs a novel multi-task learning model based on convolutional neural network.The present application can effectively identify load weight and movement type, realize the monitoring of free weight training.

The application relates to the field of underwater acoustic signal processing and discloses a deep learning method and device for weak line spectrum joint detection and reconstruction under non-Gaussian pulse noise. In order to solve the problem that in the prior art, a weak line spectrum detection method mainly extracts target features by using experience knowledge, and the performance of the method depends on the cognitive degree of an operator for samples to a great extent, and the problem that underwater acoustic signal processing technology under a Gaussian noise assumption is directly applied to signal detection under non-Gaussian noise, which causes the performance to decrease or even fail, the technical scheme provided by the application is as follows: a weak line spectrum joint detection and reconstruction method comprises the following steps: collecting pulse noise, and constructing a ship line spectrum data set according to the noise; pre-processing the data set to obtain a lofar graph; extracting weak features of the lofar graph, and obtaining a line spectrum detection and reconstruction result; training a preset model according to the lofar graph and the result, and outputting a trained model. The application is suitable for weak line spectrum detection and reconstruction under Gaussian pulse noise.

The present application relates to a kind of power line carrier communication system pulse noise suppression method, belong to power line data communication field.The method includes: S1: parameter adaptation: in receiving end, input parameter adaptation module to receiving signal, through the way of sliding window, pulse noise detection module and pulse noise suppression module are adapted condition parameters, i.e.detection parameter and noise suppression parameter;S2: pulse noise detection: received data is input pulse noise detection module according to block, obtain the peak of detection data block, and the peak is compared with the detection parameter of adaptation, judge whether there is pulse noise;S3: pulse noise suppression: through the way of iteration, constantly find out the maximum value of each section of received data and its position, and the maximum value and the data in its adjacent interval are zero, finally, the data higher than a certain threshold is limited to reach the effect of inhibiting pulse noise.The present application method is simple, and does not need to rely on experience to select amplitude threshold.

The present invention discloses a signal processing method for lightning signals, which relates to the field of lightning signal processing. It includes: S1 obtaining lightning signals; S2 identifying repeatedly occurring pulse signals as continuous steady-state pulse noise signals; S3 fitting the continuous steady-state pulse noise signals into standard noise; S4 performing sliding cross-correlation identification and denoising on the lightning signals with the standard noise as a reference; filtering out the baseline signals by separating the baseline signals and useful signals, which reduces low-frequency interference while maximizing the retention of the original lightning signal information; using the method of identifying the pulse noise waveform to fit the identified continuous steady-state pulse noise signals into standard noise, and performing identification and denoising on the lightning signals based on the standard noise signal waveform. Compared with the frequency-domain filtering method, it can more effectively filter out power harmonics and environmental noise interference.

The application provides a time delay-Doppler joint estimation method under polar pulse noise interference. On the basis of the orthogonal matching pursuit algorithm, the maximum correlation entropy criterion and the l1 norm constraint are introduced to enhance the robustness under the pulse noise, and a fast solving algorithm based on a distributed iterative optimization strategy is used to improve the calculation efficiency. Compared with the existing same type estimation method, the method has a wider application range, higher estimation accuracy and stronger robustness.

The invention relates to the technical field of line fault positioning, in particular to a risk early warning method and an early warning device for a forest fire caused by a power transmission line fault, and the method comprises the steps: obtaining a transient traveling wave signal at each monitoring point, carrying out the phase-mode transformation of the transient traveling wave signal, and extracting a forward traveling wave signal of each monitoring point; the first interference degree, the traveling wave distortion degree, the superposition complexity, the second interference degree, the adjustment coefficient and the corrected decomposition layer number of each monitoring point are determined, and fault positioning is carried out on the power transmission line; and early warning the forest fire risk caused by the power transmission line fault by using a fuzzy reasoning algorithm according to the meteorological environment condition and the vegetation dense condition at the fault position. According to the method, by correcting the number of decomposition layers, the masking interference influence of pulse noise and mixed refraction and reflection traveling waves on traveling wave characteristics is eliminated, the precision of positioning the single-phase earth fault of the power transmission line is improved, and early warning is more accurately performed on the forest fire risk caused by the power transmission line fault.

To accurately extract and remove pulse noise from a received signal.SOLUTION: A receiver generates a first noise signal by calculating the difference between a guard interval added to the beginning of a data interval of a modulated signal and a guard-equivalent interval at the end of the data interval from which the guard interval is copied. The receiver then adjusts filter parameters to minimize the difference between the signal in the guard interval or the signal in the guard-equivalent interval and the second noise signal. The receiver then removes pulse noise included in the data interval from the second noise signal generated using the adjusted filter parameters as a noise replica signal.SELECTED DRAWING: Figure 3

The invention relates to the field of hearing aids, in particular to an impulse noise suppression method and system for a hearing aid, and the system comprises a machine body module, a processing module, a protection module and a driving module. The hearing aid main body comprises a shell, a sound receiver, and a battery, a charging interface, a processor, a broadcaster and keys which are arranged in the sound receiver, the external ear hanging piece is hung at the external ear part and is used for mounting and supporting the hearing aid main body, and sudden pulse noise is inhibited by setting the maximum upper limit of the volume when the player plays; the driving module drives the sound receiving device to rotate, so that the follow-up sound processing module can process pulse noise conveniently, meanwhile, the driving module can drive the protective net to wrap the sound receiving device, at the moment, the protective net can reduce sonic boom caused by air flow impact when the sound receiving device receives sound and filter some unnecessary noise to a certain extent, external pulse noise interference is further prevented, and the sound receiving device can be used for sound receiving. Therefore, the hearing aid can be normally used under the interference of pulse noise.

A method, apparatus, and system for communicating data. Data is identified for transmission. Pulses of noise signals encoding the data are transmitted.

The invention relates to a direction-of-arrival estimation method, in particular to a high-robustness self-adaptive direction-of-arrival estimation method, and solves the technical problems of low direction-of-arrival estimation precision and poor robustness and stability in a time-varying environment due to pulse noise interference in a traditional MUSIC algorithm. According to the invention, the logarithmic compression operator is adopted to compress the array signal, so that the overall signal-to-noise ratio of the array signal can be remarkably improved, the pulse noise interference is suppressed, and the estimation precision of the direction of arrival is improved; besides, a self-adaptive adjustment mechanism of compression parameters is introduced, the situation that the compression strength is not matched with the noise environment possibly existing during fixed parameter compression is avoided, impulse noise interference from different sources can be dealt with, and the robustness and stability of direction-of-arrival estimation in the complex time-varying environment are improved; meanwhile, a dual-branch direction-of-arrival estimation framework based on a PAST algorithm and an EWMA algorithm not only ensures the real-time performance of adaptive adjustment of compression parameters, but also can improve the precision of direction-of-arrival estimation.

The invention provides a voltage sag detection method and device based on a Teager energy operator and morphological filtering, and relates to the technical field of power system sag protection and electric energy quality monitoring. The method comprises the following steps: firstly, converting a three-phase voltage signal into a voltage component under a two-phase static coordinate system through Clark conversion; secondly, a virtual instantaneous voltage power modulus containing a fundamental wave offset mechanism is constructed, and sag characteristic components can be effectively extracted; then, a morphological filtering combination filter is used for conducting denoising processing on the differential power signals, high-frequency impulse noise interference is eliminated, and pure characteristic signals are obtained; and finally, calculating an energy spectrum of the pure characteristic signal by using a Teager energy operator, and carrying out voltage sag detection in combination with a self-adaptive dynamic threshold, so as to judge the starting and ending moments of the voltage sag. According to the invention, the voltage sag can be accurately detected within 1ms, and the anti-noise performance is excellent.

The present application relates to a kind of direct current insulation resistance detection method and detection device.The method is by establishing the mathematical model of the insulation resistance of the DC bus to be measured and bus voltage, when not accessing the positive bridge arm and negative bridge arm of unbalanced bridge, and when accessing the negative bridge arm of unbalanced bridge, the positive and negative bus voltage to ground value is collected, and the noise influence is introduced, based on the above-mentioned measured values collected, the calculation method for eliminating the noise influence is created, the iteration calculation is obtained, and the parameter θ to be identified is obtained.The insulation resistance value of the DC system to be measured is solved by substituting θ into mathematical model.The method fully considers the environmental noise and the pulse noise caused by the switching of circuit switch during the test, thereby reducing the insulation resistance detection error of the DC system to be measured, and improving the reliability of detection result.

The application provides a pressure relief valve with active noise cancellation function, comprising: a valve body, which is formed with a liquid inlet cavity and a pressure relief cavity in communication with each other; a bypass pipe, which is in communication with the liquid inlet cavity; a pressure relief assembly, which comprises an adjusting piece, a pressure relief elastic piece and a pressure relief valve core, the pressure relief valve core and the pressure relief elastic piece are arranged in the pressure relief cavity, the adjusting piece is movably arranged on the valve body, and the pressure relief elastic piece is arranged between the adjusting piece and the pressure relief valve core; a piezoelectric actuator and a noise reduction elastic piece, the piezoelectric actuator is arranged on the liquid inlet cavity, the noise reduction elastic piece is arranged between the driving end of the piezoelectric actuator and the pressure relief valve core, and the piezoelectric actuator is configured to drive the noise reduction elastic piece. The pressure relief valve with active noise cancellation function provided by the application introduces active noise cancellation technology into the pulse noise control of the pressure relief valve by arranging the piezoelectric actuator, and can adjust the force applied to the pressure relief valve core through the noise reduction elastic piece to eliminate the transient noise caused by the pulse pressure when the pressure relief valve core moves.

The invention relates to a borehole radar data high-resolution processing method based on mixed time-frequency analysis, and the method comprises the steps: constructing a discrete frequency based on the scale resolution of borehole radar data; performing Hilbert transform on the drilling radar data to generate an analysis signal; and filtering the signals, performing signal reconstruction, further obtaining weighted energy of different frequency bands, and finally outputting data after high-resolution processing. Dynamic weighting is realized through low-frequency and high-frequency weighting factors, and low-frequency / high-frequency components are flexibly enhanced or suppressed; through envelope normalization, pulse noise is suppressed, and the signal-to-noise ratio is improved; original phase information is reserved during frequency domain filtering through conjugate symmetric filling, signal distortion is avoided, and time positioning precision can be kept in time-frequency analysis; through different frequency band energy weighting processing and high and low frequency joint analysis, simultaneous broadening of high and low frequencies is realized, and high-resolution amplitude preservation processing is realized.

The application discloses a high-order off-grid DOA estimation method and system based on an extended coprime array and belongs to the field of polar water sound detection. The method comprises the following steps: acquiring signals received by the extended coprime array to form a receiving data matrix; introducing a phase fraction low-order moment method to construct a phase fraction low-order moment matrix C, vectorizing C, removing redundancy and rearranging to obtain a single-snapshot continuous virtual uniform linear array signal vector z1; based on z1, using a division method of an overlapping subarray to construct a multiple measurement signal vector matrix Z; using a high-order Taylor expansion term to construct an off-grid model, using an extrapolation-based iterative sparse projection algorithm to jointly estimate a sparse signal matrix and a grid offset according to the matrix Z, and estimating the DOA of a target. The application provides a new solution to the problems of performance decline of a conventional DOA estimation method in a polar pulse noise environment and a limited number of detectable targets of a traditional uniform linear array.