263 results about "Microwave radar" patented technology

The invention relates to a human motion data processing method, and belongs to the technical field of data processing. Comprising the following steps: controlling a microwave radar to emit a detection signal, and detecting a heart rate signal and a respiration signal of a human body; performing clustering analysis on the data according to the collected heart rate and respiratory rate, and extracting heart rate, respiratory rate change, duration and exercise intensity characteristics; according to the extracted heart rate change, duration, exercise intensity and other characteristics, the exercise stage is recognized, and according to the neural network model library, an energy consumption result is output in combination with data analysis. According to the human motion data processing method provided by the invention, the microwave radar is combined with the intelligent wearable device, so that the detection precision of heart rate and respiration signals is remarkably improved, multi-modal data fusion is realized, personalized heart rate prediction is performed, motion stage division is optimized in combination with acceleration data, and the accuracy of motion data processing is improved. The accuracy of motion mode recognition is improved, and personalized motion suggestions can be provided for the user.

The invention provides a real-time human body detection method and system based on a microwave radar, and is applied to the field of signal data processing. By constructing a sparse reconstruction model and combining multi-dimensional feature decomposition, the method effectively relieves the recognition difficulty caused by target signal aliasing, continuously outputs and receives radar signals, extracts distance, Doppler and angle features, constructs target distribution point clouds in a three-dimensional feature space, further utilizes angle continuity judgment and point cloud density analysis, and improves the recognition accuracy of target distribution point clouds. According to the method, the number and distribution of overlapped targets are accurately estimated, a Kalman filter is introduced for dynamic tracking for a scene in which a continuous area is not formed, continuous separation and pseudo-color image reconstruction of multiple targets are realized, and thus the resolution precision and target positioning capability of a radar in a multi-person close-range aggregation scene are remarkably improved.

The invention discloses a full-aviation life intelligent detection and emergency rescue decision-making method and system. The method comprises the following steps: dividing emergency rescue scene gridding partitions; identifying the disaster degree and the number of affected people; combining an identification result with the gridding partition map to form a red, yellow, blue and green post-disaster gridding partition map; a full-aviation transient electromagnetic method life detector, an optical personnel detection device and a microwave radar life detection device are sequentially adopted to carry out step-by-step detection on the potential affected area, and a final replacement result of red, yellow, blue and green gridding target marking is formed; determining the priority level of ground rescue entering search and rescue according to the gridding partition map and the final replacement result; searching and inputting rescue result information of ground rescue entering search and rescue, and forming box counting statistics of grid information; a rescue decision suggestion is automatically generated according to a box counting statistical result, and efficient cooperation with a ground rescue team is formed; the method can effectively overcome the limitation of a single detection method in complex terrains and extreme environments.

The invention discloses a microwave laser composite radar cloud identification method and a computer program product, and the method comprises the steps: removing ground clutters based on transfer learning and an R-FCN network, and eliminating the noise caused by the ground clutters of a microwave radar; a deep learning model is constructed by using transfer learning and R-FCN algorithms, microwave radar and laser radar echo images are input, an attention mechanism is optimized and used in the model to realize adaptive feature extraction, a multi-scale feature pyramid is introduced on the basis of an RPN network, and the recognition and detection capability of cloud regions with different scales is enhanced. Single-result joint inversion of microwave radar and laser radar cloud identification is realized by utilizing cloud boundary self-inspection, cloud feature marking, initial matching and joint inversion of cloud boundaries, and a composite identification cloud area is obtained. The method has a cloud identification function under complex atmospheric conditions such as multilayer clouds and equipment noise interference, is accurate in inversion result, is not sensitive to ground clutter and daytime background noise, and fully integrates the identification advantage of a laser radar on a thin-roll cloud area and a cloud bottom and the cloud top identification advantage of a microwave radar.

The invention provides a self-adaptive microwave radar navigation system for an unmanned aerial vehicle, and the system comprises a route planning module which provides basic comprehensive navigation information; an image acquisition module; the feature extraction module is used for generating feature data; the target identification module is used for providing real-time data for the navigation information generation module; the image fusion module is used for generating a comprehensive image representing accurate environment information; the navigation information generation module controls the unmanned aerial vehicle to efficiently complete an inspection task; and the result output module is used for visually displaying the inspection task. According to the invention, by introducing the key area marking and identifying unit in the route planning module and utilizing the feature correlation value and the polygon intersection judgment formula, accurate identification and marking of the key area are realized, and the problem of inaccurate identification of the key area in the prior art is solved.

The invention provides a building construction measurement method and system, electronic equipment and a storage medium, and relates to the technical field of building construction measuration.The building construction measurement method comprises the steps that steel structure nodes are shot at multiple angles through image acquisition equipment, and original images are fused to obtain a target image containing a weld joint contour and a bolt spacing; calling a twinning neural network to compare the twinning neural network with geometric features of corresponding nodes of a preset BIM model to obtain weld joint and bolt distance difference information; a phased array microwave radar scans the surface of the component, the distance is measured to form multiple sets of data, a three-dimensional point cloud grid is generated through three-dimensional reconstruction, and the three-dimensional point cloud grid is compared with theoretical coordinates of corresponding nodes of the BIM model to obtain space coordinate deviation; and associating the three types of data to obtain a comprehensive deviation, fusing the point cloud to generate an installation quality evaluation report, collecting data through images and radars, combining a twin neural network and a three-dimensional reconstruction technology, comparing actual characteristics of a steel structure with a BIM model, and integrating deviation information to generate a quality evaluation report, thereby realizing comprehensive measurement and evaluation of construction quality.

The invention belongs to the technical field of road tunnel illumination, and particularly relates to a control method and system for adjusting road tunnel illumination based on dynamic traffic, which comprises the following steps: firstly, acquiring vehicle information through a high-definition camera array, a microwave radar detector and an illumination intensity sensor in a multi-source manner, then preprocessing the multi-source data, and applying an algorithm to adjust the illumination of a road tunnel; traffic flow statistics and trend prediction, vehicle driving state analysis and vehicle type accurate classification statistics are realized; based on this, the traffic flow is counted and predicted in real time through the dynamic traffic information acquisition and analysis module, the illumination brightness reference value is set and corrected based on the traffic flow by combining the multi-dimensional illumination parameter intelligent decision module, and then the illumination execution and dynamic adjustment module accurately executes the brightness instruction. The method has the advantages that the illumination brightness is dynamically matched with the traffic flow, the traffic safety requirement during high traffic flow is met, and energy waste during low traffic flow is avoided.

The invention relates to a method for processing medical images of human tissue of an area of a patient's body and in particular of the breast by means of a medical imaging device (1) comprising a microwave probe array consisting of K>1 probes spaced apart from one another, the array comprising P>1 different configurations defining transmitting probes and receiving probes for one or more position(s) around the area, in which the transmitting probes are configured to transmit microwave signals so as to illuminate an area of the body and the receiving probes are configured to receive microwave signals after scattering and reflection in the area, the probes being capable, in a complementary manner, of being configured to transmit and receive simultaneously.

The invention relates to the technical field of LED induction lamps, in particular to an LED induction lamp intelligent control method and system based on wireless networking, and the method comprises the following steps: S1, enabling a plurality of LED induction lamp nodes to be interconnected through a wireless Mesh network mode of a multi-node, self-organizing and self-healing distributed communication architecture; s2, performing linkage detection by using PIR and a microwave radar, and identifying activity information in the environment; s3, after the effective activity is sensed, lighting triggering and adjusting operation is executed locally; s4, the trigger node broadcasts a linkage instruction to other nodes in the group, so that the plurality of LED induction lamps respond synchronously; s5, in the synchronous response process of the multiple LED lamps, the working mode is dynamically adjusted according to the environment and activity conditions; according to the LED induction lamp intelligent control method and system based on the TSCH self-organizing self-healing Mesh network, through PIR and microwave dual-technology fusion (time difference and temperature compensation is utilized) and RSSI + TOA dual-distance filtering, false alarms and cross-regional linkage are greatly reduced.

The invention relates to the technical field of soil change characteristic analysis, in particular to a soil pH spatial-temporal change characteristic analysis method which comprises the following steps: scanning a target area through a vehicle-mounted microwave radar to obtain a soil dielectric constant distribution diagram, and identifying a jump critical point of which a dielectric constant gradient value is greater than a gradient threshold value; s2, taking the jump critical point of S1 as a center, laying sampling clusters in a preset radius range, detecting the soil colloid content and the actually measured pH value, correcting the pH values of multiple points in each sampling cluster, performing difference judgment, and marking a jump confirmation cluster based on a judgment result; taking the jump confirmation cluster as a spatial interpolation breakpoint, performing partition independent interpolation based on the actually measured pH value, and generating a soil pH spatial-temporal change map with a jump boundary; according to the method, the buffer zones are arranged on the two sides of the breakpoint, and the enhancement correction model based on dielectric gradient driving is introduced, so that a clear and visible abrupt change boundary zone is successfully formed in the atlas, and the expression of color gradation sharpening of the abrupt change area is realized.

The invention discloses a target for microwave radar and computer vision fusion displacement measurement, a calibration method and a system thereof, belongs to the technical field of structural displacement measurement, and solves the problem that a proper target is lacked when microwave radar and computer vision are used for measuring displacement at the same time. The target covers a transparent calibration plate on the open surface of the corner reflector, and a uniform light diffuse reflection plate is attached to the interior of the transparent calibration plate; and a light source is arranged on the corner reflector. The transparent calibration plate is provided with special mark points and common mark points, the special mark points are distributed on two intersecting straight lines, the intersection points are the special mark points, and the spacing distances among all the special mark points are different. According to the calibration method, the position of the special mark point is verified by utilizing cross ratio invariance and simple ratio invariance. The measurement system adopts the target and the calibration method. According to the invention, three-dimensional displacement testing based on microwave radar and computer vision fusion can be realized, and the three-dimensional displacement change condition of a space point can be accurately obtained, so that the vibration displacement of an engineering structure can be monitored and early warned.

The invention discloses a 3D (three-dimensional) perimeter security system and an operation method thereof, the system comprises a server terminal, a front-end sensing system, a data transmission system and a central control system, the front-end sensing system is networked in multiple groups of partitions, and each group of partitions of the front-end sensing system is provided with a nine-axis sensor, an edge computing all-in-one machine and a switch; and lighting, wind and rain sensor, broadcasting, microwave radar and camera equipment. The data transmission system transmits data; the central control system comprises an application server and a data server. The system forms a first defense line for active detection of the microwave radar and the camera and a second defense line for vibration sensing of the nine-axis sensor, and a monitoring blind area is eliminated through three-dimensional data fusion. The operation method comprises four groups of subsystem modules. According to the method, 'sky-ground-fence 'dead-corner-free monitoring is realized, the false alarm rate is reduced by combining multi-modal data fusion with an intelligent algorithm, self-evolution is realized by edge-cloud federal learning, and threat disposal efficiency is improved by automatic linkage response.

The utility model discloses an Internet of Things tunnel interval controller combined with a digital microwave radar, and the controller comprises a radar module which is used for obtaining traffic flow information in a non-contact manner; the control module is used for executing logic judgment and generating a control instruction according to the traffic flow information acquired by the radar module; the data storage module is used as a nonvolatile storage space of the Internet of Things tunnel interval controller; the radio frequency communication module is used for realizing networking and remote management through an Internet of Things communication protocol; the power supply module is used as a power supply basis of the Internet of Things tunnel interval controller, and the power supply module is connected with the radar module, the control module, the data storage module and the radio frequency communication module; a tunnel interval control solution with high integration level, accurate vehicle detection, intelligent dimming decision, flexible wireless communication and high-reliability data management is jointly realized.

The invention provides a microwave and laser radar collaborative sensing adaptive perimeter monitoring method, and relates to the technical field of security monitoring and perimeter protection, a microwave radar array and a laser radar array are arranged in a perimeter area to be monitored, and a static environment three-dimensional baseline model is constructed by combining two types of radar data; filtering the microwave radar original signal, extracting target distance and speed information, denoising and smoothing the laser radar point cloud, and outputting a synchronous multi-source data stream; constructing an attention mechanism feature fusion network, respectively mapping the preprocessed features of the two types of radars into channel and space attention weights and carrying out weighted fusion, reasoning by using a lightweight target detection model, and outputting a target classification result, confidence and position information in real time; adjusting the weights of the two types of radars in the fusion network and laser radar scanning parameters according to a preset mapping relation based on real-time environment parameters, and dynamically updating a confidence threshold value of target detection at the same time; and when the target confidence exceeds a threshold value and the positioning error reaches the standard, triggering a grading alarm.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention discloses an unmanned aerial vehicle low-altitude target radar detection and recognition system, and belongs to the technical field of radar detection and target recognition. Comprising a quantum entanglement laser emission module, a quantum multi-dimensional receiving module, a multi-source heterogeneous data fusion module, a quantum-classical hybrid calculation module, a self-adaptive anti-interference module and an environment self-adaptive correction module, the quantum entanglement laser emission module is used for generating entanglement photon pairs carrying orbital angular momentum (OAM) and emitting the entanglement photon pairs to a detection airspace; and the quantum multi-dimensional receiving module demodulates the distance, the angle, the OAM attenuation spectrum, the polarization state and the reflection spectrum of the echo signal through coincidence measurement. The quantum entanglement-OAM combined modulation technology is adopted, and the non-locality of entanglement photon pairs and the multi-dimensional information bearing capacity of a 9-path orthogonal OAM mode are improved by more than three times compared with a traditional microwave radar; single-photon-level coincidence measurement is combined with quantum Fourier transform signal processing, the signal-to-noise ratio is increased by 3dB, and stable detection of a weak target is achieved.

The invention discloses a microwave radar-based particle uniform distribution adjustment feedback method, and relates to the technical field of ore particle size detection, and the feedback method comprises the following specific steps: S100, system construction and equipment installation: forming a linkage system by a vibration feeding motor, a feeding tray, a hopper, a belt conveyor, an FMCW radar and an image shooting assembly, by introducing combined application of the FMCW radar and the MVDR beam forming method, accurate positioning and speed measurement of ore particles in a three-dimensional space are achieved, the accuracy and real-time performance of ore particle distribution adjustment are improved, the FMCW radar emits triangular measurement waves and receives reflected waves, radar data are processed by combining the MVDR beam forming method, and the accuracy and real-time performance of ore particle distribution adjustment are improved. The position coordinates and the speed information of the ore particles on the X axis, the Y axis and the Z axis can be accurately calculated, accurate data support is provided for follow-up adjustment of the particle spacing, and the whole adjustment process is more intelligent and automatic.

The invention relates to the technical field of intelligent bathrooms, in particular to an intelligent toilet bowl and a human body position detection method, device and system for an intelligent bathroom space, the intelligent bathroom space is divided into at least one static interference area and a dynamic detection area, and a cross-domain detection window is arranged at the boundary of the static interference area; a reflection signal in the intelligent bathroom space is detected through a microwave radar; analyzing a reflection signal in a preset peripheral distance range of the static interference area to generate human body target trajectory data; when it is judged that the human body target enters the static interference area, the position information of the human body target is locked in the static interference area, and interference filtering processing is carried out on reflected signals detected in the static interference area. Through the method, it can be effectively determined that the target human body is located in the static interference area, misjudgment caused by interference influence in the static interference area is avoided, and the accuracy of human body position detection is improved.

The invention discloses a forest biomass nondestructive testing device and method in forestry carbon sink measurement, and relates to the technical field of forestry resource monitoring and carbon sink evaluation, the device comprises a multi-mode sensing unit, an underground biomass monitoring module and a data processing unit, the multi-mode sensing unit collects forest stand data through cooperation of a microwave radar, a laser radar and a hyperspectral imaging assembly. The underground biomass monitoring module collects acoustic impedance data of a root system; the data processing unit comprises an environment feature recognition module, a dynamic calibration engine, an organ recognition unit, a dynamic carbon distribution unit and a carbon sink metering module, the method comprises the following steps: cooperatively acquiring data through an air base and a foundation, analyzing environment features, dynamically calibrating, segmenting organs and generating a carbon distribution coefficient, and finally calculating the carbon sink amount of a single tree according to a formula. According to the invention, non-contact multi-parameter synchronous acquisition is realized, environmental changes are adapted through dynamic calibration, accurate metering is realized by means of organ-level carbon distribution, and the precision and reliability of forestry carbon sink metering are improved.

The invention relates to the technical field of zone control of illumination, in particular to a zone control method of an airplane passenger cabin scene illumination system, which comprises the following steps: acquiring real-time external natural light parameters of each porthole area in a passenger cabin and real-time passenger distribution data of each zone in the passenger cabin, and generating a first illumination distribution diagram through a ray tracing algorithm; real-time biological rhythm feedback signals of the passenger groups in all the partitions are obtained based on a non-imaging microwave radar sensor, the biological rhythm feedback signals comprise a first type of signals and a second type of signals, the current overall activity state of the passenger groups in all the partitions is judged based on the first type of signals, and the rest state depth is subdivided based on the second type of signals; and when the adjustment amplitude of the illumination parameters of the adjacent partitions exceeds a fifth preset threshold value, generating a natural transition zone of the illumination parameters between the adjacent partitions. By arranging the transition zone, the visual boundary is eliminated through gradient change of the transition zone of the adjacent partitions, and discomfort is reduced.

The present invention discloses a space-time inversion method for ocean wave parameters using a shipborne coherent S-band radar, comprising the following steps: obtaining a space-time Doppler spectrum and extracting the average Doppler frequency deviation; estimating a space-time radial velocity sequence and converting it into a wavenumber frequency spectrum; estimating the wavefield energy and group line energy distribution and designing an adaptive filter; filtering the wavenumber frequency spectrum and reconstructing a space-time radial Doppler velocity sequence; estimating the wavenumber directional spectrum; repeating the above process to obtain six wavenumber frequency spectra and inverting an undirected ocean wave spectrum; and finally inverting the ocean wave parameters. This method addresses the impact of breaking waves and ship motion on the accuracy of ocean wave parameter inversion. It not only retains the advantages of shore-based coherent microwave radar but also overcomes its shortcomings in spatial scalability and temporal continuity, significantly improving the robustness and accuracy of ocean wave parameter inversion using shipborne coherent S-band radar.

The invention discloses an intelligent electric power perimeter early warning and diagnosis method and equipment based on microwave radar shooting control, and the method comprises the steps: firstly collecting multi-dimensional data through a plurality of sensors, including microwave radar, video images, environment monitoring, electric power system operation, facility static information and the like; the microwave radar and video image data are preprocessed and subjected to space-time fusion, and target sensing information is obtained. Thirdly, constructing a three-dimensional digital twinborn model based on the static information of the facility, mapping the fused target sensing, environment monitoring and operation data into the model in real time, and generating a real-time twinborn situation; meanwhile, an electric power knowledge graph library is constructed, real-time twinning situations are associated, perimeter safety risks are recognized through semantic reasoning, grades are determined, and root causes are positioned through causal reasoning during faults. And based on the risk level and the real-time situation, dynamically evaluating the risk, generating adaptive early warning information, predicting the potential risk, giving a maintenance suggestion, and intelligently matching an emergency plan. The objective of the invention is to solve the defects of the prior art in the aspect of electric power perimeter safety early warning, realize the conversion from passive response to active prediction and intelligent decision, and improve the safety protection level and operation and maintenance efficiency of electric power facilities.

The present invention provides a wave inversion method and system based on the time Doppler spectrum of an S-band wave measuring radar. The method comprises the following steps: comparing and estimating the left and right bandwidth boundary frequencies of an ocean echo signal in a single Doppler spectrum to obtain the bandwidth frequency of the single Doppler spectrum; calculating the average bandwidth frequency of the entire time Doppler spectrum; adding a constraint factor to obtain a corrected average bandwidth frequency; re-determining the bandwidth boundary frequencies based on the corrected average bandwidth frequency; obtaining a single Doppler spectrum frequency shift based on a spectral moment method to obtain a velocity time series, thereby eliminating the influence of other velocity components; obtaining a wave spectrum at a radar illumination direction angle based on the velocity time series of a fixed distance element; and fusing the complete undirected wave spectrum to obtain a wave inversion result. The method effectively eliminates the influence of wave breaking by performing correlation processing only on time domain data, thereby improving the accuracy of microwave radar wave inversion.

The present invention discloses a method for denoising the displacement of bridge measurement points based on microwave radar echo energy and VMD. When using microwave radar to synchronously monitor the displacement time history of multiple measurement points on a bridge, snapshot data is collected and FFT transformation is performed to obtain the echo energy information of each measurement point; the measurement point with the maximum echo energy is selected as the reference measurement point, and the VMD algorithm is used to decompose the displacement time history information of the reference measurement point to obtain several intrinsic mode functions. The correlation between each order of intrinsic mode function and the original signal is defined, and a threshold is set as the judgment condition to determine the decomposition mode order. Based on the frequency domain information of each level of intrinsic mode function after decomposition of the reference measurement point, the VMD decomposition is performed on the displacement time history data of the remaining measurement points to obtain the intrinsic mode functions after decomposition of the remaining signals; the effective displacement signals of each measurement point on the bridge are restored by using the intrinsic mode functions after decomposition of each measurement point, improving the signal-to-noise ratio of the displacement signals of each measurement point on the bridge monitored by a unified microwave radar.

The invention discloses an automatic platform door opening and closing system adopting non-contact sensing, which belongs to the field of rail transit and comprises a multi-sensor fusion system, a multi-sensor data fusion algorithm, a self-adaptive algorithm module, an environment change prediction and adjustment module, an intelligent fault diagnosis system and a multi-sensor fusion system. An infrared sensor, an ultrasonic sensor, a microwave radar sensor and an electromagnetic induction sensor are integrated and are used for cooperative work under different environmental conditions; by means of the multi-sensor fusion technology, the system can intelligently select the optimal sensor data source according to different environmental conditions, and the environmental adaptability of the system is greatly improved. In complex environments such as rainy days, snowy days and strong illumination, the system can still accurately judge the surrounding environment condition, and it is ensured that the platform door is accurately opened and closed; the adaptive algorithm module monitors and dynamically adjusts the working state of the sensor in real time, optimizes the detection precision according to the environment change, and effectively reduces the false alarm and the missing alarm.

The invention relates to a remote non-contact heart rate monitoring system used in a severe railway environment, and the system comprises a microwave radar sensing module which is used for transmitting and receiving a microwave signal, measuring the heart micro-motion information of a worker in a non-contact manner, and transmitting the heart micro-motion information to a signal fusion module in the form of time sequence data; the inertial measurement unit is used for monitoring the body movement state of a worker to obtain body movement data and transmitting the body movement data to the signal fusion module; the signal fusion module is used for carrying out data fusion on the heart micro-motion information and the body motion data to generate a fused heart rate time sequence signal; the feature extraction module is used for receiving the fused heart rate time sequence signals, extracting heart rate feature data and removing pseudo signals to obtain pseudo-removed heart rate feature data; and the classification module is used for processing the de-falsification heart rate feature data by adopting a pre-trained BiLSTM network structure to obtain a predicted label corresponding to the de-falsification heart rate feature data.

The invention belongs to the technical field of microwave radar image processing, and relates to a wind wave significant wave height inversion method based on a wind wave period, which comprises the following steps: firstly, establishing a significant wave height calculation model taking the wind wave period as input; then, acquiring a sea surface microwave remote sensing image, and performing coordinate transformation, such as preprocessing of a shore-based sea observation radar image, a shipborne navigation radar image, noise suppression and the like; thirdly, inverting a wind wave period from the preprocessed image through a spectrum analysis technology; and finally, substituting the wind wave period obtained by inversion into a pre-established model, and calculating to obtain the significant wave height. According to the method, the wind wave period is introduced to serve as a key intermediate variable, the image features and the sea wave physical parameters are closely associated, the defect that an existing direct inversion method is insufficient in precision and stability is overcome, and an effective wave height obtaining means which is clear in physical significance, high in inversion precision and easy to popularize in a business mode is provided.

The invention relates to the technical field of man-machine interaction, in particular to an intelligent screen turning-on and turning-off control method and system based on a microwave radar, which completely eradicates the risk of privacy disclosure and realizes high privacy protection through an identification mode of not collecting optical image information and only analyzing motion and vital signs through electromagnetic waves, and is not influenced by the environment, so that the intelligent screen turning-on and turning-off control method and system based on the microwave radar can be applied to intelligent screen turning-on and turning-off control. The system can stably work in severe environments such as all black and strong light, has super-strong environmental adaptability, and enables the judgment of screen opening to better conform to the real intention of a user by sensing the accurate postures of person existence, no person existence, approaching, departing, right facing or side facing, reduces false triggering to the greatest extent, improves the accuracy of system judgment, and improves the user experience. The instrument does not need to be kept in a bright state all the time in the operation process, when no person is in front of the instrument, the screen is automatically turned off at proper time, and when an operator comes to the front face of the instrument and prepares to operate the screen, screen display is automatically turned on, energy is saved, environment is protected, and the instrument is convenient to operate.

The invention belongs to the technical field of molten salt heat storage tank liquid level measurement, and discloses a device for measuring the liquid level height of a molten salt heat storage tank and a working method of the device. According to the device for measuring the liquid level height of the molten salt heat storage tank, an installation block is used for being installed on the top of the molten salt heat storage tank with the liquid level height to be measured, a distance measuring device is integrally arranged in the installation block, and the distance measuring device comprises a laser distance measuring unit and a microwave radar distance measuring unit; the rail rod is used for being vertically installed in a fused salt heat storage tank to be subjected to liquid level height measurement. The floating disc is used for being arranged in a fused salt heat storage tank to be subjected to liquid level height measurement and is slidably installed on the rail rod. The dynamic air curtain protection assembly is used for forming a protection air curtain near the distance measuring device in the liquid level height measuring process; and the operation output unit is used for calculating and outputting the liquid level height value of the molten salt heat storage tank by adopting a weighted average algorithm. According to the method, the measurement robustness and the measurement accuracy can be remarkably improved.

The invention relates to a cloud detection method based on combination of a laser radar and a microwave radar, and belongs to the field of radio. The detection method comprises the steps that a coordinate system where a laser radar radiation antenna is located is used as a reference, and system pointing angle deviation caused by the installation position of a microwave radar extension set is corrected in the mode that angle tracking parameters are calculated according to laser-microwave radar extension set antenna installation differences, and scanning space angle synchronization is guaranteed; time synchronization is guaranteed by controlling the time of a radar terminal issuing a control signal to a laser radar extension set and a microwave radar extension set, so that radar beams arrive at meteorological particle echo information to be consistent; after the radar terminal collects data, characteristic parameter extraction and data fusion are carried out on the composite observation data of the laser radar and the cloud radar. According to the method, the problem of target angle deviation caused by spatial distribution difference of the laser radar and the microwave radar during composite observation of the laser-microwave radar system is solved, and the consistency of observed targets is improved.