491 results about "Wave radar" patented technology

This application provides an automatic control method, a first electronic device, and a system based on human perception, relating to the field of automatic control. The system includes a first electronic device and a second electronic device. The first electronic device includes a first ultra-wideband module and a millimeter-wave radar module. Based on the position measurement of the second electronic device by the first electronic device, and the measurement and conversion of the human body's position, the location information of the second electronic device and the user's location information are obtained. According to the user's location information and the location information of the second electronic device, at least one of the second electronic devices automatically executes a preset operation. This application eliminates the need for the user to carry the device, enabling automatic control of IoT devices conveniently and quickly.

This invention discloses an airport FOD (Foreign Object Debris) detection and removal system and method based on multi-source sensing fusion. The system includes a mobile transport chassis, a multi-source heterogeneous sensing unit, a six-degree-of-freedom collaborative robotic arm, a composite cleaning end effector, and an edge computing platform. During operation, environmental data is first collected using LiDAR, millimeter-wave radar, and a binocular camera. Spatiotemporal fusion and state estimation algorithms are used to achieve all-weather, high-precision positioning and attribute calculation of FOD. The composite cleaning end effector integrates a high-negative-pressure suction port, a ring-shaped electromagnetic adsorption array, and a flexible mechanical claw. Subsequently, the system adaptively switches between magnetic suction, suction pickup, or gripping modes based on the material, volume, and shape characteristics of the FOD, and combines a visual closed-loop feedback mechanism to automatically upgrade and verify the cleaning strategy. This invention effectively solves the problems of poor perception robustness under complex weather conditions and insufficient adaptability of single cleaning methods, significantly improving the intelligence level and operational efficiency of airport pavement foreign object removal.

The application discloses a kind of millimeter wave radar living body identification methods based on neural network, comprising: obtaining package original ADC data, signal pre-processing is carried out, and three-dimensional radar point cloud is generated;Three-dimensional radar point cloud is respectively subjected to space geometry feature enhancement and dynamics mode feature enhancement, and enhanced feature is obtained;Three-dimensional radar point cloud and enhanced feature are parallelly input into multimodal heterogeneous feature decoupling network, and the deep physical property feature of target is respectively decoupled and extracted;Cross-modal interaction and adaptive weighted fusion are carried out to the deep physical property feature, and obtain fusion feature vector;Fusion feature vector is input into classifier, and the discrimination result whether the target in package is living body is output.The deep physical property feature of target is extracted by the multimodal heterogeneous feature decoupling network of the application, and adaptive depth fusion is carried out using cross-modal attention mechanism, so as to effectively suppress non-living interference in complex dynamic environment, and the accuracy of living body detection is significantly improved.

The utility model discloses a wireless remote two -way intelligent control electricity device, include: mechanical arm, millimeter wave radar, visual camera, cleaning component and rotating component, millimeter wave radar sets up at the top of mechanical arm, visual camera sets up at the top of mechanical arm, and millimeter wave radar and visual camera are provided with the fixing piece for fixing millimeter wave radar and visual camera position at the junction of mechanical arm, and cleaning component sets up at one side of visual camera, and cleaning component is used for cleaning visual camera. The utility model discloses through the design of mechanical arm, millimeter wave radar and visual camera, when using, through the mechanical arm drive millimeter wave radar and visual camera and move, and through millimeter wave radar and visual camera accurate identification super -large material, millimeter wave radar penetrates dust and adds visual compensation identification technology, and combine mechanical arm and clean the material and dredge, and through this design solves the failure problem of traditional single sensor in the mine bad environment.

1. The name of the design product: millimeter wave radar human body sign detector. 2. The use of the design product: the electronic detection instrument for monitoring the vital signs of the rescued person. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The present application relates to a kind of road fog dangerous working condition identification processing method based on multi-sensor fusion, the method includes: step 1, camera, millimeter wave radar and laser radar specificity degradation features under fog environment are extracted in parallel;Step 2, based on the feature real-time evaluation sensor confidence and dynamic weighted fusion, obtain comprehensive visibility estimation V final =η*[W cam *V vis +W rad *φ(C rv )+W lid *ψ(1 / λ)], And dangerous working condition level;Step 3, according to dangerous working condition level, establish the accurate mapping lookup table of grade and vehicle control instruction, according to accurate mapping lookup table, execute the vehicle active safety control strategy corresponding to dangerous working condition level;Step 4, comprehensive visibility estimation and dangerous working condition level are packaged as standard car-road cooperation message, broadcast through vehicle-mounted communication unit, realize the vehicle-vehicle, vehicle-road early warning of over-the-horizon.This technical scheme solves the technical problems such as the present technology fusion level is shallow, information utilization rate is low, output result is rough, lack of adaptive ability etc.

This invention discloses a co-integrated device for a low-crosstalk RF front-end and array antenna for millimeter-wave radar, comprising a main board, a shielding plate, an RF module, and an array antenna module. The shielding plate is horizontally positioned above the main board, and a frame is provided outside the shielding plate. Support columns are vertically mounted at the four corners of the frame and between the shielding plate and the main board. A sub-plate is mounted on the surface of the shielding plate, and the array antenna module is mounted on the surface of the sub-plate. An antenna cover is mounted on the sub-plate to cover the array antenna module. The RF module is mounted on the side of the main board away from the shielding plate, and the pins of the RF module are soldered and fixed to the main board. Pressure bars are provided on both sides of the pins to hold them in place. This invention has a simple structure and actively manages and reduces electromagnetic crosstalk between the array antenna and the RF front-end through a combination of increased distance, physical shielding, and adjustable position; at the same time, the pin-fixing structure enhances the mechanical reliability of the RF module.

This invention discloses a data processing method and system for surface trauma and subcutaneous tissue injury. The method includes: using millimeter-wave radar to perform non-contact signal acquisition of the trauma area to obtain echo signal information; performing two-dimensional data analysis and processing on the echo signal information to obtain target trauma signal information; and performing three-dimensional data analysis and processing on the target trauma signal information to obtain target identification result information.

The application provides a millimeter wave radar and video fusion tower clearance real-time monitoring method, which comprises a video monitoring camera system and a millimeter wave radar system; first, the two systems are installed at the bottom of the cabin and rotated to point to the blade clearance area, realizing image acquisition and radar reflection point data acquisition in the blade movement cycle; then the controller system calculates the blade tip clearance value according to the collected image data and radar reflection points, qualitatively evaluates the deviation of the two according to the spatial relationship between the blade tip trajectory line and the blade tip reflection point, and ensures the high-precision clearance monitoring of the blade tip and the tower. The clearance monitoring method of the fusion of the two sensors can realize the functions of mutual checking of the accuracy between the systems in normal weather, selection of the clearance for unit control in severe weather, stronger environmental adaptability and working condition adaptability, and avoids the problems of failure of a single sensor due to environmental influence or low clearance accuracy.

This invention discloses a driver state monitoring and safety early warning method based on millimeter-wave radar, comprising: acquiring driver physiological micro-motion signals and driver macro-behavioral signals respectively through millimeter-wave radar to obtain driving environment information in real time; denoising the driver physiological micro-motion signals and extracting features to obtain driver physiological feature signals; constructing a time-frequency spectrum using driver macro-behavioral signals; determining the driver physiological arousal index and driver emotional state risk value based on the physiological feature signals; obtaining the driver dynamic behavior risk value based on the time-frequency spectrum; calculating an environmental complexity index based on driving environment information; constructing a driver state risk field model based on the driver physiological arousal index, driver emotional state risk value, and driver dynamic behavior risk value; calculating the driver state risk value using the driver state risk field model and environmental complexity index; and providing graded early warning based on the driver state risk value.

This invention provides a 4D radar odometry method for high-dynamic scenarios, relating to the field of autonomous driving perception and sensor fusion technology. The method includes: acquiring raw point cloud data using a 4D millimeter-wave radar-based perception system; extracting corresponding clustering parameters from the raw point cloud data, wherein the clustering parameters include search radii in different directions and minimum neighborhood density; clustering the raw point cloud data using the DBSCAN clustering method based on the clustering parameters to obtain different point cloud clusters; extracting static points from the different point cloud clusters; and calculating the vehicle speed based on the static points using an angle-distance weighted least squares method. This technical solution effectively improves the accuracy of vehicle speed measurement.

The application relates to an object size estimation method, device, electronic equipment and medium. The method can comprise: acquiring cumulative edge point cloud data corresponding to a target object, the cumulative edge point cloud data comprising position information of a plurality of edge points, the number of the plurality of edge points being greater than a first quantity threshold; predicting the contour of the target object based on the plurality of edge points to obtain contour information of the target object; determining a relative rotation direction and a relative rotation angle of the target object relative to a previous collection orientation of the target collection orientation; the target collection orientation is a collection orientation at the end of the collection time sequence; and estimating the size of the target object according to the contour information, the relative rotation direction and the relative rotation angle to obtain size information of the target object. According to the technical scheme provided by the application, the point cloud obtained by the millimeter wave radar is no longer sparse, and the accuracy of the size estimation of the target object is improved.

This application discloses a method for fabricating a microcoaxial transmission structure and the microcoaxial transmission structure itself. By directly forming grooves and metal conductors on a substrate and then bonding them together, the microcoaxial transmission structure is effectively formed, avoiding complex steps such as ultra-thick photolithography, repeated electroplating and polishing, and long-term sacrificial layer release. This simplifies the process and reduces equipment and time costs. Simultaneously, it eliminates the enormous internal stress that may be generated during the sacrificial layer release process, thereby avoiding defects such as interlayer peeling, collapse, and deformation of the microcoaxial transmission structure. This improves the mechanical integrity, dimensional stability, and electrical connection reliability of the microcoaxial transmission structure in millimeter-wave radar and high-speed communication systems, ultimately enhancing the stability of signal transmission.

This application relates to the fields of SAR signal processing and marine remote sensing applications, and provides a method and apparatus for sea surface current field inversion based on electromagnetic vortex wave radar data. The method determines the Doppler spectrum using electromagnetic vortex wave radar image data, obtains the measured frequency position of the trough feature point in the Doppler spectrum, and determines the theoretical frequency position using the position and angle of the two main lobes and the angle of the trough feature point in the radar antenna pattern. Then, the difference between the measured frequency position and the theoretical frequency position is used to obtain the anomalous frequency offset. Next, the Doppler frequency offset caused by wind and wave motion is removed from this anomalous frequency offset to obtain the target Doppler frequency offset. Finally, the radial velocity of the sea surface is calculated using the Doppler frequency offset, thus realizing sea surface current field inversion. This effectively expands the applicability of the Doppler frequency shift-based ocean current inversion method and improves the application potential of electromagnetic vortex wave radar in sea surface current field detection.

This invention discloses a fall detection method, apparatus, device, and medium. The method includes: determining target noise point detection information corresponding to the target radar detection information of a target person based on personnel radar detection information detected by millimeter-wave radar and noise point detection information detected by an acoustic detection device; determining the detection mode of the target person based on the target radar detection information, and determining target detection information from the target radar detection information and target noise point detection information based on the detection mode; wherein the detection mode includes an obstruction mode, a stationary mode, and a motion mode; and detecting the fall state of the target person based on the target detection information. This invention uses a combination of millimeter-wave radar and acoustic detection for fall detection, enabling continuous fall state detection even when the target person is obstructed by objects indoors, improving the accuracy and efficiency of fall detection; and since both millimeter waves and acoustic waves are invisible waves, user privacy can be effectively protected.

The application discloses a kind of intelligent unmanned vehicle environment perception systems based on multi-sensor information fusion, it is related to unmanned vehicle technical field.The system includes: sensor module, for collecting multi-source heterogeneous data, including GPS / IMU, laser radar, camera and millimeter wave radar;Data acquisition and fusion module, through the Kalman filter to multi-source data space-time synchronous fusion;Environment perception module, based on deep learning identification road boundary, obstacle and traffic sign, constructs dynamic perception model;High-precision map construction module, using SLAM technology and semantic information constructs and updates semantic three-dimensional map;Positioning algorithm module, fusion visual odometry, fusion data and high-precision map, calculates vehicle real-time pose;And control module, according to positioning and perception result carries out path planning and navigation control, the application provides a kind of intelligent unmanned vehicle environment perception systems based on multi-sensor information fusion, can be autonomously navigated and stably driven under complex and severe environment.

The present application provides a kind of vital signs detection signal denoising method and device, it is related to physiological perception and signal processing technical field, including: based on millimeter wave radar's Doppler technique, obtains the original phase signal containing physiological signal;Original phase signal is carried out variational mode decomposition based on the search algorithm of variational mode decomposition super parameter optimization algorithm optimized by particle swarm optimization algorithm, obtain the vibration modal function information corresponding to the original phase signal;Wherein, the particle swarm optimization algorithm uses permutation entropy and fuzzy entropy as fitness function;After denoising processing is carried out to the vibration modal function, the vibration modal function after denoising processing is recombined, and high-precision denoising processing is obtained after physiological signal;From the high-precision denoising processing physiological signal, extract respiratory and heartbeat physiological signal.

The invention provides a vehicle scene reconstruction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring image data acquired by a vehicle, multi-frame millimeter wave radar data and inertial measurement unit data; when it is recognized that the weather state of the environment where the vehicle is located is severe weather, the severity level of the severe weather is determined; according to the severity level, performing fusion processing on the multiple frames of millimeter wave radar data to obtain accumulated radar data; performing enhancement processing on the accumulated radar data to generate enhanced radar data; performing dedegradation processing on the image data according to the enhanced radar data to generate an enhanced image; and generating three-dimensional scene reconstruction data of the surrounding environment of the vehicle according to the enhanced image, the enhanced radar data and the inertial measurement unit data. Therefore, a stable and accurate three-dimensional scene reconstruction result can be output in severe weather.

This invention discloses a method for identifying hazardous targets in millimeter-wave security gates based on intelligent correction of misclassification. Belonging to the field of hazardous target identification technology for millimeter-wave security gates, it solves the problem of misclassification caused by the similarity of features between different categories during the classification of millimeter-wave radar imaging data in existing technologies. The method includes: batch acquisition of historical millimeter-wave radar imaging data and their corresponding target categories, constructing a training set and an evaluation set; iteratively training a hazardous target identification model for millimeter-wave security gates using the training set; evaluating the trained hazardous target identification model using the evaluation set, filtering out all misclassified data, and forming several sets of misclassified pairs; correcting the misclassification of the target identification model using the misclassified pairs; and using the corrected hazardous target identification model for real-time millimeter-wave radar imaging data.

The invention discloses a virtual multi-view fusion millimeter wave point cloud imaging method, which belongs to the field of millimeter wave radars, and realizes three-dimensional point cloud imaging of a target by constructing a virtual observation view angle and fusing perception data of different view angles: establishing a multi-view synthetic aperture radar imaging model; a single-bit compressed sensing framework is introduced to construct a sparse imaging optimization problem, an accurate relay angle is solved by minimizing a model error, and a relay plane model error is corrected; and high-precision 3D point cloud imaging of the region of interest is realized based on the accurate angle. According to the method, a three-dimensional point cloud of a target is constructed by fusing virtual visual angle detection shielding characteristics formed by reflection of a plurality of relay surfaces, joint estimation of relay surface angle prior and 3D point cloud is realized by a nested iteration method, and artifacts and offset caused by prior errors are eliminated; the sparsity and the target continuity of the three-dimensional point cloud can be improved through the additional composite norm constraint, and the accuracy of virtual multi-view 3D point cloud imaging is effectively improved.

The utility model relates to the technical field of wiring harness fixer, and disclose a millimeter wave radar wiring harness fixer, including lower clamping plate, one side of lower clamping plate top rotatoryly connected with upper clamping plate, the opposite side of lower clamping plate and upper clamping plate all are established with a plurality of rectangle slot, every rectangle slot's inside wall all are provided with U type sheet piling, the inner top wall of rectangle slot is established with mounting groove, the inside of mounting groove is provided with connecting assembly, the fixed component that is provided with between lower clamping plate and upper clamping plate. This millimeter wave radar wiring harness fixer, through replacing the clamping block and connecting assembly, make the same set of fixer can be compatible with different diameter's wiring harness, reduce the type of fixer in the development of vehicle type, reduce mould cost and inventory pressure, simultaneously, different function's wiring harness, such as power cord, signal line and ground wire can be fixed through different clamping block partition, be convenient for the quick identification and overhaul when maintaining later period, promote the efficiency of after-sales.

This invention discloses a method and system for amphibious vehicle navigation perception fusion in complex environments, relating to the field of amphibious vehicle waterborne perception technology. The method includes the following steps: acquiring point cloud data in different multimodal regions; preprocessing the point cloud data, with different regions including the water surface region, the above-water region, and the below-water region; performing feature-level fusion on the multimodal point cloud data and assigning comprehensive credibility to the fused feature-level targets; using a fuzzy logic algorithm to perform decision-level fusion on the feature-level targets to generate the final comprehensive environmental perception result; and performing environmental modeling, path analysis, and collision risk assessment based on the final comprehensive environmental perception result. This invention utilizes the complementary advantages of deep collaborative sonar and millimeter-wave radar to achieve stable and accurate detection of obstacles on, below, and above water in complex environments.

This invention relates to the field of dynamic replanning technology for multi-UAVs in heavy-duty logistics, and particularly to a method for dynamic replanning of multi-UAVs for heavy-duty logistics. The method includes: accessing UAV information, cargo information, and initial map information; constructing an initial route and calculating its length after field checks, coordinate unification, and obstacle avoidance processing; generating a candidate route set; then sequentially performing distance, battery power, payload, and charging time constraints to obtain a static planning model; solving the model using a fusion of simulated annealing and ant colony optimization to obtain an initial path solution; updating the map information by real-time acquisition of unknown obstacle information using millimeter-wave radar; identifying the original path obscured by obstacles to generate an old solution; and finally, dynamically updating the old solution by performing path deletion, path addition, and objective function comparison based on operator weight probabilities to obtain a replanned path solution. This invention effectively shortens the maximum time of multi-UAV missions and significantly improves the robustness and adaptability of heavy-duty logistics transportation.

The utility model relates to traffic detection technical field in intelligent traffic system especially, more particularly to a kind of traffic detection device based on millimeter wave radar, comprising: the picture acquisition mechanism of being set to device front end;First trigger radar and picture acquisition mechanism are sequentially arranged, detect vehicle entry condition;Second trigger radar and first trigger radar are sequentially arranged, confirm vehicle existence state;Transaction identification antenna is set after second trigger radar;Third trigger radar and transaction identification antenna are installed in same position, identify vehicle transaction success and send signal;Flow radar and third trigger radar are sequentially arranged;Gate lever and third trigger radar are communicatively connected, perform lifting action;Anti-smashing radar and gate lever are set in same position, detect vehicle after passing through and carry out relay attraction to complete gate lever pole falling action;Display is set in whole device end. The utility model greatly reduces installation complexity and long-term maintenance cost, and improves the comprehensive detection capability of the system.

The application relates to the technical field of air conditioner control, and discloses an air conditioner indoor unit control method, device, equipment and storage medium, the method realizes the cooperative control of the air conditioner indoor unit and the lighting mechanism in the night scene, and a complete logic chain of scene recognition, information collection, state determination and accurate control is constructed; through the combination of a millimeter wave radar sensor and a human state detection model, the accurate perception of the human state is realized, non-target interference can be effectively filtered, and three states, i.e., frequent rotation, sitting up and getting out of bed, can be distinguished, so that the false touch rate is greatly reduced; the air conditioner parameter adjustment or the lighting control is respectively performed according to different states, the problems of high false touch rate and unsuitable brightness of a traditional night light can be solved, the defects of the fixed parameter operation of a traditional air conditioner can be made up, and the user's night sleep comfort and night convenience are significantly improved; meanwhile, a high-frequency scanning mode is adopted, the real-time performance and the accuracy of state determination are ensured, and a reliable data basis is provided for subsequent parameter adjustment and lighting control.

The application discloses a sleep apnea detection method based on a millimeter wave radar, and relates to the technical fields of radar signal processing and vital sign detection.The method comprises the following steps: transmitting a detection signal to a target through a millimeter wave radar to obtain an intermediate frequency signal and a signal transformation matrix; calculating a dynamic energy change value based on the preprocessed signal transformation matrix, and determining a target distance bin of each frame according to a statistical result of the dynamic energy change value; determining whether the target is in a position stable state according to the discrete degree of the target distance bin of each frame in a preset time window; extracting a phase signal at the target distance bin of each frame in the window in the position stable state, obtaining a breathing signal waveform curve based on the phase signal, and detecting a sleep apnea event.The application can realize high-precision detection of the sleep apnea event under various complex conditions, and effectively solves the problems of unstable target locking, large noise interference and lack of distance adaptability in state determination.

The application provides a calibration method and device of a vehicle-mounted millimeter wave radar, electronic equipment and a storage medium. The calibration method of the vehicle-mounted millimeter wave radar comprises: acquiring a radar position ID of the vehicle-mounted millimeter wave radar, the radar position ID being used to indicate an installation position of the vehicle-mounted millimeter wave radar; determining a search reference angle based on the radar position ID; searching for a calibration object in a specific area based on the search reference angle; after the calibration object is searched in the specific area, the vehicle-mounted millimeter wave radar transmits a radar signal to the calibration object and receives a return signal reflected by the calibration object; and the vehicle-mounted millimeter wave radar is calibrated based on the return signal. According to the application, the calibration object arranged at different positions can be calibrated, so that the production line of different customers can be adapted.

An in-vehicle application transfer method and a terminal relating to the field of intelligent terminals provides for automatically establishing a correspondence between an in-vehicle passenger space and a mobile terminal. An application on the mobile terminal is automatically transferred to a display in front of a passenger seating area to improve application use experience. A position of the mobile terminal is detected through an ultra-wideband (UWB) base station, and position of the passenger space is detected through a millimeter wave radar. A correspondence between the mobile terminal and the passenger space is established when the position of the mobile terminal coincides with the position of the passenger space and transferring an application running on the mobile terminal to a vehicle-mounted terminal including a display on the vehicle-mounted terminal corresponding to the passenger seating area.

The utility model discloses a 5G early warning vehicle display system, including car body, the millimeter wave radar in car body outside, with millimeter wave radar communication connection's 5G signal receiving device and be located on the display screen of car body, car body top is equipped with the mounting seat, is equipped with angle adjusting mechanism on the mounting seat, is equipped with the display screen on angle adjusting mechanism, angle adjusting mechanism includes L type rotating lever, first mobile link and second mobile link, is equipped with the rotating block on first mobile link and second mobile link, and L type rotating lever both ends respectively through two rotating blocks setting, through millimeter wave radar calculation to and fro vehicle speed and through 5G signal to carry out communication transmission to the display screen and remind to and fro vehicle deceleration, and the display screen can realize angle adjustment through angle adjusting mechanism, improve early warning range.