301 results about "Radar interference" patented technology

The invention belongs to the technical field of radar interference identification, and discloses a radar interference identification method based on LSTM and a variational auto-encoder. According to the method, a joint network of the LSTM and the variational auto-encoder is constructed to encode the time sequence signal to obtain a corresponding feature vector, then the feature vectors of the emission signal and the echo signal are spliced to obtain a combined vector capable of representing the interference type, and then classification learning is performed on the combined vector through the convolutional neural network, so that the interference type can be represented. And identification of interference signals is realized. By means of the capability of the LSTM network to solve the long-term dependence problem and the advantages of the variational auto-encoder in dimension reduction and feature extraction, time sequence data can be effectively processed, and complex distribution of data can be learned; and meanwhile, vectors before and after the interference process are spliced to represent a change relation before and after the signal, so that interference pattern identification under any change can be adapted.

Systems and techniques are provided for mitigating radar interference between radars on a same and / or different vehicles. An example process includes receiving a first signal associated with a first radar sensor; receiving a second signal associated with a second radar sensor; determining an interference between the first signal and the second signal; in response to determining the interference, determining one or more adjustments to an operation of at least one of the first and second radar sensors based on at least one of a safety parameter, a coverage parameter, and a respective context of one or more vehicles associated with at least one of the first and second radar sensors; and transmitting one or more instructions to adjust the operation of at least one of the first and second radar sensors during one or more time intervals.

The invention provides an in-ocean solitary wave amplitude inversion method, an electronic device and a readable storage medium, SWOT satellite observation data is combined with other remote sensing means observation data of close time to form a double-time-phase remote sensing image, and then the observed in-ocean solitary wave amplitude of a target sea area is obtained. According to the method, large-area two-dimensional sea surface height observation data with high resolution and high precision can be provided based on radar interference measurement, and under the condition that sea surface height abnormity caused by the marine internal solitary waves on the sea surface can be captured, the amplitude of the internal solitary waves is obtained in combination with other remote sensing observation data, so that the calculation process is simplified, and the calculation efficiency is improved. And the inversion precision is improved.

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) deformation inversion method for lifting rail offset correction, and mainly relates to the technical field of surface deformation monitoring. In order to solve the problem that the deformation monitoring quantity of the existing multi-dimensional small baseline set formed aperture radar interference is obviously lower than the actual deformation quantity, a time sequence deformation observation equation is established by using multi-orbit synthetic aperture radar data, an ascending-orbit small baseline set InSAR settlement monitoring point cloud and a descending-orbit small baseline set InSAR settlement monitoring point cloud are calculated respectively, point cloud registration is carried out, and the settlement monitoring point cloud of the ascending-orbit small baseline set InSAR settlement monitoring point cloud is calculated to obtain the settlement monitoring point cloud of the descending-orbit small baseline set InSAR settlement monitoring point cloud. Calculating the offset of the monitoring result of the lifting rail in the vertical, east-west and south-north directions; calculating to obtain an ascending orbit incidence angle correction number and a descending orbit incidence angle correction number of the synthetic aperture radar image by using the offsets of the ascending orbit monitoring result in the vertical direction, the east-west direction and the south-north direction; and finally, constructing a multi-dimensional small baseline set InSAR deformation inversion model containing lifting rail offset correction, solving to obtain a corrected deformation monitoring quantity, and improving the deformation monitoring precision.

The invention provides a wave radar anti-interference adaptive adjustment method, and belongs to the technical field of interference adjustment, and the method comprises the steps: 1, transmitting a radar signal based on a target wave radar, and collecting an interfered original echo signal from a radar receiver; 2, interference signals in the original echo signals are analyzed and extracted, and the types of the interference signals are identified; step 3, based on the interference signal type matching adaptive filtering coefficient, initializing an adaptive filter to obtain a first adaptive filter; 4, performing time dispersion processing on the frequency of the interference signal by using a frequency hopping waveform technology, inputting the interference signal into the first adaptive filter to obtain a signal adjustment parameter, and configuring to obtain a final adaptive filter; and step 5, adjusting the target wave radar based on the final adaptive filter, and evaluating an adjustment result. Radar interference is effectively suppressed through adaptive filtering and frequency hopping processing, and the signal processing precision is improved.

A system for radar interference mitigation, preferably including one or more transmitter arrays, receiver arrays, and / or signal processors, and optionally including one or more velocity sensing modules. A method for radar interference mitigation, preferably including transmitting a set of probe signals, receiving a set of reflected probe signals, and / or evaluating interference, and optionally including decoding the set of received probe signals and / or compensating for interference.

The invention discloses a radar interference identification method based on multi-representation domain feature interactive fusion and a graph structure semantic classifier, and the method comprises the steps: constructing a multi-representation domain feature interactive fusion module, taking a time domain waveform, a spectrogram and a time-frequency spectrogram as input data, and outputting fusion features; constructing a graph structure semantic classifier, inputting the fused features into the graph structure semantic classifier, analyzing semantic association of different types of signals by the graph structure semantic classifier, and outputting a classification result; dividing the data set into a training set and a test set, and storing network parameters with the best classification effect in the training set according to a classification result; and loading network parameters, and inputting the test set into the radar interference identification network for processing to obtain an identification result. According to the method, the interference signals can be fully represented, the identification and processing capability of the interference signals is improved, robustness representation is carried out on the interference signals, and the accuracy of radar interference identification is improved.

The invention discloses a method for estimating parameters of a ground phase-coded radar interference source based on an SAR image. The method comprises the steps of deriving a corresponding relation between phase-coded interference parameters and SAR image features and estimating the parameters. According to the method, the corresponding relation between the pulse width, the bandwidth, the carrier frequency and the repetition frequency of the interference signal and the interference characteristics on the SAR image is determined according to the mathematical relation, the problems of unclear mathematical expression, unclear parameter corresponding relation and the like on the phase coding radio frequency interference SAR image are solved, and the interference fringe parameters on the SAR image are estimated and the corresponding relation is obtained through derivation, so that the interference fringe parameters on the SAR image are estimated. And inversion of interference source parameters of the ground phase-coded radar is realized. Simulation results show that parameters such as pulse width, bandwidth, carrier frequency, repetition frequency and the like of phase coding radio frequency interference can be accurately estimated; the method can be applied to estimating parameters such as pulse width, bandwidth, carrier frequency, repetition frequency and the like of a phase-coded signal from an SAR image interfered by a ground same-frequency phase-coded radar signal.

The invention provides a radar complex interference identification method based on a feature fusion network, and the method can automatically learn and extract useful features from original radar interference signals through employing an interference signal time domain and time-frequency domain feature extraction network, and can adapt to more complex signals. And fusing all the features, and sending the fused features to a trained feature classification fusion network for classification. A model formed by the interference signal time domain and time-frequency domain feature extraction network and the feature classification fusion network has strong generalization ability, and a complex mode can be learned from a large amount of data, so that unknown interference can be identified to a certain extent; after model training is completed, the reasoning (prediction) speed is relatively high, and real-time interference identification can be provided; in addition, the model can also process complex, nonlinear and hybrid interference signals.

The invention provides an anti-detection camouflage method based on missile-borne tail end guidance features, and relates to the technical field of anti-detection camouflage, and the method comprises the steps: constructing a feature data set through the reflection feature parameters of radar transmission waves with different transmission features under different environment data, transmission angles and distances, and building a reflection feature calculation model; the method comprises the following steps: acquiring guided missile tail end guidance features, performing preprocessing according to the emission angle, distance and environmental data of guided missile radar, predicting reflection feature parameters through a model, modulating radar interference waves with the same reflection feature parameters as the reflection feature parameters to generate an interference blind area with reflection waves, and controlling the position and size of the interference blind area. Blind area coverage is conducted on the position where the missile is located, the blinding index of the missile in the time period is calculated by calculating the moving trajectory fluctuation coefficient of the missile after interference and the change coefficient of a landing area, whether an attack target is lost or not is judged, and whether a tempting signal is released or not is selected.

The invention relates to a multifunctional radar interference strategy generation method and device, computer equipment and a storage medium, and the method comprises the steps: employing a part-observable Markov decision model, carrying out the modeling of a non-cooperative game process of multifunctional radar confrontation according to an OODA cycle, obtaining a multifunctional radar confrontation process model, and carrying out the calculation of the model. And an interference strategy generation network based on Transform and A2C is designed. A plurality of TIT units are used as observation feature extractors, action probability distribution is output through a strategy network, state value evaluation is carried out through a value network, and a strategy-value double-branch decoupling structure is formed. Under the constructed multifunctional radar adversarial process model, the interference strategy generation network is trained, the trained interference strategy generation network is utilized to generate the corresponding interference strategy, and the effective and accurate interference strategy can be generated in real time by adopting the method.

The invention discloses a cognitive radar active anti-interference waveform generation method and system based on DQN and MAB, and the method comprises the steps: obtaining a radar interference time-frequency diagram based on a radar transmitting signal and an interference signal; based on the radar interference time-frequency diagram, simulating a radar confrontation process and constructing a transmitted waveform strategy library; solving the waveform strategy library by using a DQN algorithm, and optimizing a solving result by using an MAB algorithm to obtain an optimal transmitted waveform; and a CFAR detector is adopted to detect the optimal emission waveform, and the optimal anti-interference waveform and parameters are generated. According to the method, the global strategy search of the DQN and the local parameter optimization of the MAB are fused, the anti-interference dynamic adaptation problem in a multi-pulse time sequence interaction scene is effectively solved, and the method is suitable for the real-time anti-interference requirements of an airborne radar electronic countermeasure system and a complex electromagnetic environment.

The embodiment of the invention relates to the technical field of radars, in particular to a radar interference signal semi-supervised recognition method, system and device and a medium, and the method comprises the steps: carrying out the short-time Fourier transform of a radar interference signal, and constructing a training sample set containing a labeled training sample and an unlabeled training sample; pre-training the CNN network based on the labeled training sample to obtain a pre-training model; using the pre-training model to predict the unlabeled training samples, generating pseudo labels, screening the pseudo labels, and using the retained unlabeled training samples with high confidence to calculate a semi-supervised loss value; performing category perception comparison learning on the pre-training model by using the unlabeled training sample, and calculating a category perception comparison loss value; calculating a total loss value based on the semi-supervised loss value and the category perception comparison loss value, and performing fine tuning on the pre-training model to obtain an identification model; and inputting the radar interference signal to be identified into the identification model to obtain an identification result output by the identification model.

The invention discloses a radar interference decision-making method, device and system and a storage medium, and the method comprises the steps: S1, obtaining a potential relation between radar working mode conversion and interference signal release of a jammer according to a radar-jammer confrontation environment; and S2, inputting the threat level corresponding to the current radar working mode as an environment state parameter into a competitive dual deep Q network decision structure based on adaptive greedy adjustment and priority dual experience playback for value evaluation, experience input, experience extraction and parameter updating operation to obtain a radar interference decision result. According to the technical scheme, the problems that a traditional reinforcement learning algorithm is poor in strategy convergence effect and insufficient in experience storage mode are solved.

A wireless transmit receive unit (WTRU) and methods are disclosed for mitigating radar interference on PUSCH transmission. The method may include: transmitting a message informing a network of PUSCH MIMO layer aggregation capability; receiving a MIMO rank; receiving an indication to use PUSCH MIMO layer aggregation; determining a PUSCH layer aggregation level based on the MIMO rank; and transmitting multiple redundancy versions of a PUSCH codeword comprising one or more code blocks based on the PUSCH layer aggregation level. The WTRU may be configured to transmit a message informing a network of PUSCH MIMO layer aggregation capability; receive a MIMO rank; receive an indication to use PUSCH MIMO layer aggregation; determine a PUSCH layer aggregation level based on the MIMO rank; and transmit multiple redundancy versions of a PUSCH codeword comprising one or more code blocks based on the PUSCH layer aggregation level.

The invention discloses airborne radar interference equipment of a phased array system in the technical field of radar countermeasure. The airborne radar interference equipment comprises an antenna array; a plurality of transmit-receive assemblies comprising a plurality of transmit-receive channels, wherein each transmit-receive channel comprises a numerical control attenuator and a numerical control phase shifter; the beam control unit controls the numerical control phase shifter and the numerical control attenuator; the power divider / combiner is used for combining or dividing the signals; the circulator is used for realizing one-way transmission of signals; the low-noise amplifier is used for performing low-noise amplification on the signal; the microwave frequency conversion unit is used for performing down-conversion and up-conversion processing on the signal; the digital processing unit is used for processing the intermediate frequency signal to form an interference signal; and the main control unit communicates with the digital processing unit to control an interference pattern, and communicates with the beam control unit to control beam pointing, frequency, attenuation and an enable signal of a transmit-receive assembly. The airborne radar interference equipment can realize interference signals with high power and beam scanning, and has the advantages of high equivalent radiation power and rapid interference scanning.

The invention discloses a phased array radar jammer system for multi-beam receiving and narrow-beam transmitting in the technical field of radar countermeasure, and the system comprises an interference host which is used for analyzing the azimuth and pitching information of an interfered radar according to a received signal, and modulating the output of an interference signal according to the azimuth and pitching information; the radio frequency distribution network is used for transmitting signals between the interference host and the transceiving switch assembly; the transceiving switch assembly is used for processing the received signal, processing and transmitting the interference signal and realizing multi-beam receiving or narrow-beam transmitting; the wave control unit is used for controlling the transmitting and receiving states of each transmitting and receiving channel and realizing the adjustment of the phase and the power of an interference signal; and the antenna array is used for receiving and transmitting the radar signal and is also used for transmitting an interference signal. The phased array radar jammer system can autonomously detect the radar signal orientation and adjust the interference signal emission orientation according to the radar signal orientation, the utilization efficiency of the phased array jammer is effectively improved, and high-power radiation and signal orientation reconnaissance capability are both considered.

The invention relates to a time frequency-image fusion distance joint azimuth SAR active interference identification method and device. The method comprises the following steps: inputting radar interference echo data to be identified into a trained interference identification network; wherein the to-be-identified radar interference echo data comprises a to-be-identified interference data time-frequency spectrum and a to-be-identified SAR interference image; the interference identification network comprises a first feature extraction network, a second feature extraction network, a feature fusion network and a classification network; the first feature extraction network and the second feature extraction network are connected in parallel to the feature fusion network, and the feature fusion network is connected to the classification network; and obtaining an interference type identification result corresponding to the radar interference echo data to be identified. The method can effectively extract and fuse features from different modes to realize interference identification, and has high identification accuracy.

The invention discloses a radar interference resource allocation method based on MADDPG and an auction algorithm, and the method comprises the steps: firstly building an interference confrontation model and a radar detection model, and achieving the target allocation through the auction algorithm based on the interference confrontation model. Secondly, establishing a state space of the jammer, wherein the state space comprises information of the jammer, information of other jammers and target radar information; then, a multi-agent decomposition method is adopted to decompose each jammer into three decision-making agents, and an action space of each decision-making agent is established; and finally, on the basis of the state space and the action space, in combination with an allocation matrix of target allocation in an auction algorithm, realizing interference resource allocation through an MADDPG algorithm. According to the method, the interference resources of the jammer are dynamically distributed in real time, and real-time and efficient distribution of the interference resources of the jammer in a high-dimensional action space is realized.

The invention discloses a radar interference resource allocation method based on a grey wolf algorithm. The method mainly solves the problems that in the prior art, interference resource allocation efficiency is low, combination explosion occurs, and engineering implementation is not facilitated. The scheme comprises the following steps: 1) constructing an interference task scene, and constraining a solution space through a coding strategy optimization method; 2) constructing an interference resource allocation objective function, and initializing an allocation scheme according to a good point set theory; 3) on the basis of the grey wolf algorithm, a nonlinear convergence factor, a dynamic weight and a reverse learning method are introduced to complete updating of a grey wolf position, namely updating of a distribution scheme is completed; and 4) repeating the iterative updating process in the step 3) until the algorithm converges, and taking the wolf pack position corresponding to the currently obtained interference benefit as a final interference resource allocation result. The method can effectively improve the optimization speed in the resource allocation process, avoids falling into a local optimal solution, and can be used for improving the resource allocation task efficiency in a radar cooperative interference scene.

The invention discloses an active phased array system radar cognitive interference signal generation method, a medium and equipment, and relates to the technical field of radar electronic countermeasures, and the active phased array system radar cognitive interference signal generation method mainly comprises the steps: constructing a radar electronic countermeasure simulation model, obtaining a signal style state conversion table by using a TOPSIS sorting algorithm and the minimum interference-to-signal ratio data table; according to the radar electronic countermeasure simulation model, obtaining an interference pattern selection model by using the signal pattern state conversion table and a DDQN network; and performing optimal interference pattern decision by using the interference pattern selection model. By implementing the active phased array system radar cognitive interference signal generation method, the medium and the equipment provided by the invention, the accuracy and applicability of radar interference decision can be improved.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may include a radar which is used for object detection, such as a vehicle UE detecting other vehicle UEs in a vehicle-to-everything (V2X) communications system. The UE may be configured for coordinated interference, where radars transmit a common waveform while applying different delays to prevent negative co-channel interference effects, such as false or ghost targets. The techniques described herein support configuring a common configuration for network-assisted coordinated interference by considering capabilities of UEs and radars within a geographic area controlled by a network entity. The network entity may identify and indicate a waveform configuration which is used by radars within the geographic control area of the network entity.

The invention discloses a dynamic modeling method of a hidden Markov model, which comprises the following steps of: defining a radar-jammer master-slave confrontation mode, namely, when a radar is not interfered, setting an HMM-based information scheduling strategy matrix A and a transmitted pulse time-frequency parameter control strategy matrix B in coherent processing time according to a target detection task of the radar; a transmission pulse sequence is generated. An interference party extracts radar state parameters by using intercepted radar pulses, estimates a radar information scheduling strategy matrix A and a transmitting pulse time-frequency parameter control strategy matrix B, formulates an interference strategy matrix Aj and an interference signal time-frequency parameter control strategy matrix Bj, sends interference signals to the radar, and estimates Aj and Bj of the interference party after the radar receives the interference signals. And judging whether interference is valid or not, correspondingly adjusting the matrix A and the matrix B, and repeating the process to realize dynamic modeling of cognitive radar countermeasure.

The invention discloses a networking multifunctional radar interference decision-making method based on threat level sorting. The method comprises the following steps: A, determining the working mode of each radar of a networking multifunctional radar; b, performing threat level sorting on the radar according to the working mode; c, inputting the interference pattern mask matrix and the one-hot code of the radar with the highest threat level into an interference decision network according to the radar sorting, so that the network outputs an interference pattern; d, updating the interference pattern mask matrix according to the interference pattern selected at the previous moment, and performing interference decision on the radar of the next threat level; repeating the step D until the interference patterns of all radars are obtained; and the interference decision network is used for realizing a networking multifunctional radar formation anti-interference decision based on a Markov decision. According to the method, the algorithm learning efficiency is effectively improved, the decision-making precision is improved, and the cooperative interference resource scheduling strategy can be quickly and effectively generated under the conditions that the number of jammers is not equal to that of radars and interference resources are limited.

The present invention discloses an electronic countermeasure offline decision-making method, system, device and storage medium. Due to the fact that in a complex electromagnetic environment, the radar state information obtained by the jammer is partially observable and has deviations, the jamming strategy obtained by the general decision-making method is often difficult to guarantee performance when deployed in a real environment due to its limitations. Therefore, the solution provided by the present invention models the electromagnetic environment into an opponent intelligent agent, and the jammer intelligent agent and the opponent intelligent agent are interactively trained to obtain the final jammer intelligent agent. This can better make radar jamming decisions, making the jammer's decision-making in a complex electromagnetic environment more efficient and safe.

The invention discloses a radar anti-interference decision generation method and system based on experience playback and strategy gradient, a medium and a product. The method comprises the following steps: constructing an experience playback pool; a reinforcement learning GPPO model is constructed; training the reinforcement learning GPPO model by using the experience playback pool to obtain a trained reinforcement learning GPPO model; and the trained reinforcement learning GPPO model is used to generate an optimal anti-interference strategy for an interference signal to be suppressed. According to the method, the current state of the linear frequency modulation radar can be better estimated by using the current and historical radar interference data, so that the online generation of the optimal anti-interference decision is realized, and the anti-interference decision generation performance in the dynamic electromagnetic countermeasure environment is also improved.

Methods systems, and devices for wireless communications are described. A first wireless device may transmit a first radar signal in a first frame, and may receive a reflected signal corresponding to the first radar signal in a second frame. The first wireless device may also receive a number of different transmissions including at least a second transmission from a second wireless device. To determine which signals are reflections from the first radar signal and which signals are interference. the first wireless device may monitor a third frame that is subsequent to the first and second frames for one or more interfering signals during a silence interval. In some other cases, the first wireless device may transmit a request for the second wireless device to modify a timing offset for the second transmission, and may monitor for the second transmission which may be shifted in frequency according to the timing offset.

The invention provides a forest vertical structure information inversion method and system based on radar interferometry, and the method comprises the steps: carrying out the small-view processing of high-resolution SAR interferometry data with a space baseline, calculating the small-view InSAR phase height, extracting the statistical distribution of the small-view interferometry phase height in a set space window, and carrying out the calculation of the small-view interferometry phase height. Generating a small-looks interferometric phase height histogram; establishing an under-forest ground elevation regression estimation model based on the statistical characteristics of the small-looks interferometric phase height histogram, and determining model parameters to invert the terrain; and two canopy top indexes are extracted, two index results are fused by setting a threshold value, and final forest vertical structure information is generated. The method has the advantages that more canopy internal and under-forest information can be captured only by using single-baseline and single-polarization radar interference data, and the sensitivity to a forest vertical structure is improved; and the forest vertical section, the tree height and the terrain can be synchronously inverted.

The invention discloses a radar interference effect evaluation method based on a constraint learning dynamic Bayesian network, is applied to the field of radar interference evaluation, and aims at solving the problem that the accuracy of interference effect evaluation is reduced due to radar detection data missing in a complex electromagnetic environment. Meanwhile, parameter constraints of five types of evaluation indexes and interference effect grades are defined; secondly, constructing a constraint learning dynamic Bayesian network, and learning a conditional probability and a transition probability under a data missing condition; then, proposing a prior constraint expectation maximization algorithm, converting parameter learning into an optimization problem with constraint by combining convex optimization, and overcoming the defects of a traditional expectation maximization algorithm; secondly, a cloud model is introduced to quantify discrete probability distribution into a continuous interference degree value; finally, simulation shows that the method can effectively improve parameter learning stability and evaluation accuracy under the conditions of suppressing and deception jamming and single index deficiency, and provides a reliable scheme for radar jamming effect evaluation in a complex environment.

The invention discloses a radar active composite interference signal identification and parameter measurement method of a Yolov8 network based on a convolution attention mechanism and rejection loss, and aims to solve the problems of single working mode and poor robustness of the existing interference signal identification method and convert the interference identification problem into the target detection problem. And a target detection framework is applied to detect, identify and measure parameters of interference signals, and a CBAM attention mechanism is introduced, so that the image feature extraction capability of the network is enhanced, and the identification rate is improved. In addition, a rejection loss function is also introduced, so that a good regression prediction effect can be kept when the interference signal time-frequency images are overlapped more frequently. The network provided by the invention has good detection and identification performance on most of signals under the condition of low interference-to-noise ratio. The invention belongs to the technical field of radar interference signal detection and identification.