4073 results about "Radar systems" patented technology

The invention relates to the technical field of radar control, in particular to an anti-interference control method applied to a radar, and aims to solve the problem that an existing radar anti-interference technology is insufficient in anti-interference capability in a complex electromagnetic environment. According to the method, multi-dimensional input data of a radar system are synchronously collected, interference feature extraction is performed on multi-dimensional data streams by using a dual-channel deep network, and interference fingerprint vectors are output to a dynamic feature library in real time. And based on the interference feature priority list, performing cooperative processing, including spatial filtering, frequency domain notch, polarization projection and residual extraction and sparse reconstruction of a target signal. And dynamically adjusting the processing parameters according to the real-time evaluation result. And data distribution processing is carried out on the suppressing interference and the deception interference, and final target trajectory information is output through result fusion. Parallel processing is also realized on the FPGA chip, and the processing speed is improved. On the whole, the anti-interference capability, the stability and the real-time performance of the radar system in a complex electromagnetic environment are improved.

The invention provides a forest fire early-stage intelligent early warning method based on multi-source remote sensing data, and the method comprises the steps: carrying out the data collection of a target forest through employing an airborne laser radar system and a plurality of sensors, carrying out the data preprocessing, obtaining a three-dimensional forest landscape model and related parameters of the target forest, carrying out the feature extraction, and carrying out the early warning of a forest fire. Obtaining a forest environment key feature library of the target forest, quantitatively evaluating the probability of fire occurrence of the target forest in a specific spatial-temporal scale in the three-dimensional forest landscape model, obtaining a fire risk index, constructing a fire early warning model to solve an optimal early warning strategy, and performing early warning on a target forest region of which the early warning level exceeds a preset threshold value. And automatically forming visual early warning information of the early warning area. Through advanced technologies such as multi-source data fusion, numerical simulation and deep reinforcement learning, a set of complete intelligent forest fire early warning scheme is formed, and reliable data support is provided for forest fire prevention.

The invention provides a laser radar data processing method for a complex forest environment, and the method comprises the steps: obtaining the original point cloud data of a target forest region through an airborne laser radar system or a backpack type laser radar system, carrying out the preprocessing of the original point cloud data, obtaining the preprocessing point cloud data, and filtering out the ground points in the preprocessing point cloud data, obtaining non-ground point cloud data, and classifying ground features in the non-ground point cloud data to obtain ground feature classification point cloud data; based on the ground feature classification point cloud data, constructing a three-dimensional canopy point cloud model, and based on an individual tree parameter extraction method, obtaining individual tree spatial positions and key forest parameters of individual trees in the target forest area, the individual tree parameter extraction method including but not limited to crown segmentation and different-speed growth equations. According to the method, the vertical structure information of the ground features is obtained through the radar system, the ground point data is removed, the ground features are classified, and high-precision obtaining of the horizontal parameters of the single tree and the forest stand in the complex forest environment is achieved.

Golf balls having one or more marks for improving the detection and tracking thereof by radar systems and methods of applying the marks to the golf balls are provided. The methods of the present disclosure involve applying the radar detectable marks to a layer of the golf ball by pad printing. The methods described herein utilize a plurality of pad printing stations having multi-impact capabilities and reorientation mechanisms to apply the radar detectable marks to the golf ball layer. The use of the multi-impact pad printers combined with the rotational capabilities of the reorientation mechanisms enables precise delivery of the radar detectable marks in a consistent and repeatable manner over the entire surface of the golf ball layer and multi-pole printing within a wide print area on the golf ball layer.

The invention relates to the technical field of bridge detection, and discloses a bridge array radar-based signal processing system and method, and the method comprises the steps: collecting a reflected electromagnetic wave signal at regular time through a bridge array radar system, and carrying out the preprocessing of the reflected electromagnetic wave signal, so as to improve the signal quality. A signal is accurately matched to a bridge model by using the spatial resolution capability of three-dimensional modeling and array radar, and an electromagnetic wave reflection image of an internal structure is formed. And according to the electromagnetic characteristics of the bridge material, setting a strength threshold value and a form identification rule to distinguish normal and defect structures, and analyzing the defect development trend. Furthermore, a deep learning algorithm is adopted to carry out feature extraction and classification on the reflection image, defect positions, types and sizes are automatically identified, and a detection report is generated. And finally, displaying defect space distribution in combination with geographic information (GIS), and making a targeted maintenance plan. According to the invention, the detection precision and efficiency of the internal defects of the bridge are improved.

A wind-finding method based on fusion of millimeter wave radar data and laser radar data, comprising: S1, acquiring wind-finding radar parameters; S2, on the basis of the wind-finding radar parameters, acquiring system state flag bits of wind-finding radars, determining whether the wind-finding radars work normally, and executing corresponding behaviors; S3, acquiring measurement data of the wind-finding radars at different heights, and caching related parameters; S4, by determining radial wind speed significant bits, selecting a corresponding wind-finding radar, and performing inversion on the wind speed; S5, fusing the wind speeds inverted by the millimeter wave wind-finding radar and the laser wind-finding radar to obtain a fused output wind speed; and S6, outputting a horizontal wind speed and a wind direction corresponding to each height level. According to the wind-finding method based on fusion of millimeter wave radar data and laser radar data, two types of wind-finding radar measurement data obtained simultaneously are fused, improving the data reliability of wind speed and wind direction measurement; and the advantages of different wind-finding radars are fully utilized, improving the overall measurement precision.

Techniques are discussed herein for analyzing radar data to determine that radar noise from one or more target detections potentially conceals additional objects near the target detection. Determining whether an object may be concealed can be based at least in part on a radar noise level based on a target detection, as well as distributions of radar cross sections and / or doppler data associated with particular object types. For a location near a target detection, a radar system may determine estimated noise levels, and compare the estimated noise levels to radar cross section probabilities associated with object types to determine the likelihood that an object of the object type could be concealed at the location. Based on the analysis, the system may determine a vehicle trajectory or otherwise may control a vehicle based on the likelihood that an object may be concealed at the location.

The invention relates to a migratory fly insect intelligent identification method based on trap lamp assisted radar database building. According to the method, insect monitoring data of the moth-killing lamp and the radar in the same night period are fused, the insect data set is established through matching of the two data, and the difficulty of a traditional insect data set database establishment mode in data acquisition is effectively overcome; secondly, a CL-GC-Swin Transform network model is provided, a contrast learning module and a global context block are introduced into the Swin Transform, and training is carried out by using the complete polarization time-frequency characteristic pattern of the insect, so that the characterization capability of the network on the time-frequency characteristic pattern of the insect is significantly enhanced, and the accuracy of insect type identification can be effectively improved. According to the method, the flight characteristics of the insects are directly utilized for identification, complex scattering characteristic calculation and accurate radar calibration are not depended on any more, the requirements for radar system precision and calibration are greatly reduced, and the adaptability and robustness of identification can be improved.

This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

The invention discloses a laser radar system for simultaneously measuring an atmospheric cloud height and a wind field. The laser radar system comprises an outer cover module and an inner cavity, the outer cover module comprises an automatic detection station shell, an all-in-one meteorological sensor connected with the automatic detection station shell, a cloud measurement window embedded in the automatic detection station shell and a wind measurement window embedded in the automatic detection station shell; a reference module, a control module, a cloud measurement optical receiving module, a cloud measurement laser transmitting module and a wind measurement optical transceiving module are arranged in the inner cavity; wherein the control module, the cloud measurement optical receiving module, the cloud measurement laser transmitting module and the wind measurement optical transceiving module are all integrated on the reference module; through the above structure, the laser radar system can obtain the wind profile data, the cloud height measurement data, the atmospheric extinction coefficient profile and the visibility of the current environment at the same time.

The invention provides an oil film detection method and system based on a hierarchical self-organizing network and scale adaptation, and relates to the technical field of oil film detection. According to the technical key points, the method comprises the following steps: preprocessing an obtained original radar image; performing oil film region identification on the preprocessed radar image by using a trained oil film identification model based on the improved growth layered neural gas network to obtain an oil film candidate region; and segmenting the oil film candidate region by using an improved multi-scale threshold segmentation algorithm to obtain a final oil film detection result. According to the method, a local feature enhancement mechanism, dynamic level adjustment, adaptive error attenuation, sparse constraint optimization and a real-time adaptive learning mechanism are introduced, so that the adaptivity, robustness and calculation efficiency of the detection model are remarkably improved. The method can be integrated in a shipborne radar system, is high in calculation efficiency, can meet the real-time processing requirements of shipborne equipment, and is suitable for practical application scenes such as marine oil spill monitoring and emergency response.

The invention discloses a networking X-band weather radar cooperative adaptive control method, and relates to the technical field of weather radars. The problems that in the prior art, real-time state data and historical data cannot be fully utilized to construct an accurate radar performance model, and deep analysis on environment characteristics is lacked when control parameters are dynamically adjusted are solved. According to the method, the operation state and historical data of the radar system are collected and analyzed, the radar performance model is established, and the control parameters are dynamically optimized, so that the observation performance and the resource utilization efficiency of the radar system are remarkably improved, state information sharing and cooperative adjustment among the radar systems are realized based on a cooperative control mechanism of a communication link, and the reliability of the system is improved. The adaptability and reliability of the system are effectively enhanced, main factors influencing the system performance can be identified by constructing an intelligent performance evaluation module, model parameters are dynamically adjusted, constraint conditions are optimized, and long-term efficient operation of the radar network under complex environmental conditions is ensured.

A radar system for determining target information of radar targets includes a first antenna array configured to emit a transmit signal and receive a first signal reflected by a radar target, and a second antenna array configured to receive a second signal reflected by the radar target. The system is configured to process the received signals to determine distance information and angle hypotheses associated with the radar target. Based on the distance information and angle hypotheses, the system applies optimal filters to generate target information related to the radar target. The disclosure also relates to a vehicle incorporating such a radar system.

A linear chirp radar system, apparatus and method use a radar control processing unit to control an LFM radar front end which generates analog-to-digital (ADC) sample signals from one or more target return signals received in response to transmitted linear chirp radar signals, where the radar control processing unit is connected and configured to mitigate range migration by directly filtering the ADC samples using a modified Doppler filter that is tuned to fast-time scaled, slow-time frequencies to generate a focused ADC Doppler cube, and by applying a Fourier Transform on each Doppler cell in the focused ADC Doppler cube to generate a focused range-Doppler cube.

The invention discloses a backpack and unmanned aerial vehicle laser radar single tree segmentation method and system based on deep learning. The method comprises the steps that tree multi-platform point cloud data is acquired and fused based on an unmanned aerial vehicle and a backpack type laser radar system; generating individual tree label data; constructing a single-tree segmentation model which comprises a feature extraction network, a feature sorting and clustering module and a feature screening module; and single-tree segmentation is carried out after the single-tree segmentation model is trained. In order to solve the problem of insufficient feature extraction capability of a traditional method under complex forest stand conditions such as canopy embedding and form approaching, a spatial attention mechanism and a hierarchical density clustering module are introduced, feature weights of different regions are dynamically allocated in a coding stage, and the sensitivity to a local geometric structure of a canopy embedding region is enhanced; and meanwhile, multilevel semantic information is reserved by utilizing a feature fusion strategy in a decoding stage, so that the three-dimensional space topological feature distinguishing capability and the crown boundary recognition capability are enhanced, and the accuracy of single tree segmentation is improved.

The invention discloses a dynamic unmanned aerial vehicle cluster electromagnetic characteristic modeling method and system based on a digital array radar, and the method specifically comprises the steps: setting radar system parameters, building a time-varying motion model of an unmanned aerial vehicle cluster, and obtaining the formation pose distribution of the unmanned aerial vehicle cluster under a global coordinate system; component decomposition is carried out on an unmanned aerial vehicle CAD model, shielding analysis is carried out under the radar sight line constraint condition, time-varying scattering center parameter extraction is carried out according to the dynamic electromagnetic effect between targets, scattering center space distribution of an unmanned aerial vehicle cluster is updated in a time sequence recursion mode, and construction of a time-varying scattering center model is completed; a radar system signal model is constructed according to digital array radar DAR parameters, multi-dimensional dynamic feature extraction and parameter mapping are carried out, digital array radar multichannel signal modulation and unmanned aerial vehicle cluster target radar echo construction are completed, and radar scattering electromagnetic characteristic modeling of a dynamic unmanned aerial vehicle cluster is realized. According to the method, the model description accuracy is improved, and the calculation process is more efficient.

The invention provides a self-adaptive calibration method, device and equipment for airborne radar and a storage medium, and the method comprises the steps: fusing multi-modal monitoring data, such as radio frequency signals, structural vibration and environmental parameters, through introducing a space-time attention mechanism, and generating unified feature representation; further constructing a digital twinborn body combined with Transform and LSTM based on the characteristic representation, realizing dynamic modeling of a nonlinear performance degradation rule of the radar system, and ensuring that a health index sequence accords with an actual degradation characteristic through physical constraint verification; the fault diagnosis report generated by residual analysis and an interpretable AI technology can realize interpretable positioning of abnormal features in a complex environment, and meanwhile, a diagnosis result is converted into a physical constraint cue word to be input into a large language model to obtain an optimization suggestion and feed back and update digital twinborn parameters, so that a closed-loop evolution mechanism is formed, and the diagnosis accuracy is improved. The key problem that the airborne radar is difficult to realize accurate health assessment and adaptive calibration in a complex environment is effectively solved.

The invention discloses a non-reference channel passive radar networking cooperative weak target signal level positioning method, and the method comprises the steps: firstly initializing system parameters, and building a target echo model, which is polluted by noise and direct wave interference, of a non-reference channel passive radar; then, a complete data set is established in combination with a distributed multi-station target echo model and an unknown signal of a non-cooperative external radiation source, a conditional likelihood function of the complete data set is derived, and finally, based on an expectation maximization principle, an expectation step and a maximum step of the conditional likelihood function are executed in a loop iteration mode so as to continuously update target position estimation and suppress direct wave interference. And the maximum likelihood estimation of the target position is obtained until the convergence condition of the expectation maximization algorithm is met, and combined direct wave suppression and target position estimation updating are realized. The method provided by the invention solves the problems that the current passive radar system is low in positioning precision, easy to be interfered by direct waves, unknown in non-cooperative external radiation source signal, strong in dependence on a reference channel and the like in weak target detection.

The invention discloses a high-reliability fire detection method and system, and relates to the technical field of fire alarm, and the detection method comprises the following steps: S1, setting a threshold value; s2, initializing a background value, updating the detection value at regular time, and updating the background value to initialize the background value; s3, identifying the aerosol type; s4, identifying the movement condition of the personnel; s5, identifying a high-humidity environment; s6, identifying a high-temperature environment; and S7, judging a fire alarm. The detection system comprises a threshold setting module, an initialization module, a smoke detection module, a radar system, a humidity detection module, a temperature detection module, a background value updating module and an alarm module. According to the invention, the radar system is used for judging and detecting the motion state of environmental personnel, detection is carried out in combination with factors such as smoke, temperature and humidity, and different levels of alarm thresholds are set for judgment, so that the identification capability of the fire detector on non-fire smoke is enhanced, and the false alarm probability under the non-fire smoke condition is reduced.

The invention belongs to the technical field of wind power generation, and discloses a wind power plant digital twin modeling system and a use method, the system comprises an equipment module, the equipment module comprises a biological bionic adaptive fan blade system, a quantum sensing network, a laser radar system, a high-resolution multi-modal imaging system and an intelligent autonomous flying robot group system; the network module comprises a 5G private network, a quantum communication network and an edge computing network; the data module comprises a distributed database system, a big data processing platform and an AI training platform; the AI module comprises a wind regime prediction model, a power prediction model, an equipment health state monitoring model and a self-adaptive control algorithm model; the application module comprises a digital twinborn visualization platform, a holographic mixed reality operation and maintenance system and an intelligent scheduling system. Modeling and intelligent management of the wind power plant can be realized, the power generation efficiency can be improved, the operation and maintenance cost can be reduced, and the service life of equipment can be prolonged.

The invention relates to the technical field of atmospheric remote sensing, in particular to a satellite-borne laser radar-based multi-feature attention cloud top height estimation algorithm, which comprises the following steps of: full-waveform laser radar data acquisition and preprocessing: acquiring an original echo signal through a satellite-borne full-waveform laser radar system; performing time domain alignment, noise suppression and saturated signal elimination on the signals; a median filtering and wavelet threshold denoising algorithm is combined to eliminate high-frequency noise, and background radiation interference is eliminated through dynamic baseline correction; according to the method, a multi-stage noise reduction strategy combining sliding window median filtering and self-adaptive wavelet denoising is introduced in the waveform feature extraction stage, pulse interference and signal oscillation are effectively restrained, meanwhile, through a terrain matching error compensation mechanism, the detection accuracy is improved, and the detection accuracy is improved. The physical consistency of the elevation residual error under the real terrain background is enhanced, and the authenticity and the checkability of the point elevation return are improved.

The invention discloses a multi-mode adaptive phase coding radar and a speed ambiguity resolution technology, and relates to the technical field of millimeter wave radars, and the radar comprises a radar signal processing system, a multi-mode adaptive control module, an adaptive phase coding module, a frequency modulation module, a PRF optimization module, a PMCW waveform generator, and a speed ambiguity resolution algorithm module. According to the multi-mode self-adaptive phase coding radar and the speed ambiguity resolution technology, the performance of a radar system is remarkably improved by integrating PRF optimization, phase coding integration and frequency modulation methods, the problem of speed ambiguity in high-speed target detection can be effectively solved, the accuracy of speed measurement and the maximum measurable speed are improved, and meanwhile, the speed ambiguity resolution technology can be applied to the field of high-speed target detection. According to the invention, the anti-interference capability and the multi-target separation capability of the radar in a complex environment are enhanced, high-precision and high-efficiency target detection and tracking are realized, and in addition, the multi-mode adaptive function enables the radar system to flexibly meet the detection requirements in different scenes.

The invention belongs to the technical field of antenna engineering, and particularly relates to an ultra-wide-band low-profile phased-array antenna, which realizes broadband impedance matching characteristics and effectively expands the working bandwidth of the antenna by optimizing a dipole arm structure and introducing a matching branch knot and linear tapered slot composite structure on a radiation unit layer; on the array architecture level, an electromagnetic metasurface technology is adopted, array current distribution is improved through a periodic artificial electromagnetic structure, the active standing-wave ratio is remarkably reduced, the scanning angle of an array is widened, and meanwhile high compression of a system profile is achieved; on the structural design level, a three-dimensional composite structure of a transverse metal floor, a longitudinal radiation layer and a transverse metasurface layer is innovatively constructed, and the overall section height is reduced to 0.137 lambda Low (lambda Low is the lowest working frequency wavelength) through electromagnetic coupling and space folding technologies; in conclusion, the ultra wide band (the relative bandwidth is greater than or equal to 90%) and the low profile (lt; and the method is suitable for a new generation of broadband phased array radar system.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing location tagging. The radar system has sufficient spatial resolution to recognize different external environments associated with different locations (e.g., recognize different rooms or different locations within a same room). Using the radar system, the smart device can achieve spatial awareness and automatically activate user-programmed applications or settings associated with the different locations. In this way, the radar system enables the smart device to provide a location-specific shortcut for various applications or settings. With the location-specific shortcut, the smart device can improve the user's experience and reduce the need to repeatedly navigate cumbersome interfaces.

Aspects presented herein may improve joint communication-radar system by providing a radar reference signal with GI-FMCW waveform. Aspects presented herein may be compatible with communication-centric waveforms and thereby may apply to UEs or network entities with minimal changes if specified. In one aspect, a wireless device transmits a set of communication signals. The wireless device configure one or more parameters associated with a set of radar reference signals for radar sensing based on the set of communication signals, each radar reference signal in the set of radar reference signals including a guard interval. The wireless device transmits the set of radar reference signals associated with the one or more parameters.

The invention discloses a radar deception jamming identification method based on adversarial game optimization. The method comprises the following steps: S1, acquiring radar echo signal data; s2, obtaining preprocessed radar echo signal data; s3, constructing an adaptive risk game model between the radar and deception jamming based on the preprocessed radar echo signal data; s4, training a deep learning recognition network by using the preprocessed radar echo signal data; s5, introducing a reinforcement learning module, and integrating the deep learning recognition network and the adaptive risk game model; and S6, the optimized radar identification strategy is applied to processing of real-time radar echo signal data, deception jamming signals are identified and classified in real time, and corresponding identification results are output. According to the method, the radar system can effectively avoid a high-risk strategy, so that the uncertainty in combat decisions is reduced.

The invention relates to the technical field of radar, and discloses a three-dimensional positioning life detection radar system, and the radar system comprises a phased array antenna unit which is used for transmitting radar waves and dynamically adjusting the wave beam direction according to the target position; the signal receiving unit is used for receiving a radar signal reflected by a target; the Doppler frequency shift analysis module is used for analyzing the frequency change of the received radar signal and extracting a micro-motion signal of the target; the target motion analysis module is used for tracking the motion of the target through a Kalman filtering technology; the three-dimensional reconstruction module is used for reconstructing the three-dimensional position of the target through an electromagnetic field integral equation and multi-source sensor information fusion according to the received signals; and the deep learning module is used for identifying the micro-motion signal and optimizing target classification. By adopting the phased-array antenna unit and the beam forming technology, the technical effects of carrying out accurate three-dimensional scanning and rapid dynamic beam adjustment on the target are achieved.

An example method for using antenna array calibration to adjust radar unit operation involves receiving radar data from a radar unit coupled to a vehicle during vehicle operation in an environment, where the radar unit receives the radar data from the environment via an antenna array of the radar unit. The method also involves detecting an object in the environment based on the radar data, determining that the detected object satisfies a set of conditions, and, in response to the set of conditions being satisfied, estimating a first phase array offset for the antenna array. The method also involves comparing the first phase array offset with a second phase array offset that represents a prior calibration for the radar unit, and, based on a difference between the first and second phase array offsets exceeding a threshold difference, adjusting operation of the radar unit according to the first phase array offset.

The present disclosure relates to an apparatus for measuring a heart rate of a target in a field of view of a radar sensor. The apparatus comprises processing circuitry configured to determine a frequency spectrum corresponding to time-domain data based on a receive signal. The processing circuitry is further configured to determine a breathing rate frequency based on a maximum amplitude of the frequency spectrum. Furthermore, the processing circuitry is configured to determine a plurality of section-frequency-spectra, each corresponding to a respective section of the time-domain data, based on the breathing rate frequency and to determine an average of the section-frequency-spectra to obtain an averaged-frequency-spectrum. Furthermore, the processing circuitry is configured to subtract the averaged-frequency-spectrum from the frequency spectrum to obtain a difference spectrum. Based on a maximum amplitude of the difference spectrum, the processing circuitry is configured to estimate a heart rate of the target.

The present application belongs to the technical field of wireless communications and radar systems. Disclosed are a dual-band fusion and multiplexing frequency source, chips, a radio-frequency transceiver, a system, and a device. The system comprises: a full-function millimeter-wave CMOS 4+1 phased array chip, which is connected to an antenna end, and is used for realizing signal processing and frequency conversion between a millimeter-wave signal and a C-band intermediate-frequency signal, performing phase control and gain adjustment on the millimeter-wave signal, and providing an internal frequency source and a calibration function; a C-band front end, which is connected to the antenna end, and is used for receiving or transmitting a C-band signal; a C-band / intermediate-frequency transceiver multiplexing chip, which is used for performing frequency conversion between a C-band or intermediate-frequency signal and a baseband signal in a multiplexing manner, and performing signal processing and gain control on the C-band intermediate-frequency signal; a dual-band fusion and multiplexing frequency source, which is used for providing a local oscillator signal; and an all-digital control logic circuit, which is used for providing a control instruction. The present application improves the efficiency and performance of dual-band joint communications.