19 results about "Satellite radar" patented technology

The invention discloses a residual agricultural film three-dimensional distribution inversion method based on satellite radar collaborative calibration, and belongs to the technical field of agricultural environment remote sensing monitoring, and the method comprises the steps: extracting surface environment characteristics and underground dielectric characteristics from a multispectral satellite image and a ground penetrating radar signal; inversion of surface agricultural film content hot area distribution is carried out by using a random forest and a Kriging interpolation model, and soil internal dielectric constant distribution is acquired from radar data based on a hybrid inversion method; the method comprises the following steps: constructing an encoder-decoder model based on Transform, and establishing a cross-modal mapping relation between satellite features and radar parameters through a multi-head attention mechanism; and fusing earth surface and underground inversion results to generate a three-dimensional space distribution diagram of the residual agricultural film. The method effectively overcomes the technical limitations that traditional optical remote sensing can only identify earth surface coverage and the on-site sampling space is discontinuous, and provides a reliable technical means for farmland residual film pollution assessment and treatment.

Embodiments of the present disclosure provide a method and system for satellite-ground radar cooperative observation based on sensitive targets, which are applied to the technical field of weather radar. The method comprises the following steps: acquiring satellite, radar and underlying surface data; identifying and processing the radar data to obtain the number, position, area of potential targets and the early warning level corresponding to each potential target, and comprehensively obtaining the satellite-ground joint early warning level; using the underlying surface data, potential targets and the satellite-ground joint early warning level to construct a sensitive target evaluation function and calculate the sensitivity score; and arranging and combining the sensitive targets and radar scanning modes, and performing optimization processing to select the optimal scanning mode. In this way, real-time tracking and dynamic monitoring of strong convective weather can be achieved, guiding multiple weather radars to efficiently carry out cooperative operation and improving the observation timeliness and early warning reliability of high-disaster strong convective weather.

The application discloses an artificial corner reflector for synthetic aperture radar interferometry calibration, and relates to the technical field of measurement and monitoring, and solves the technical problem that an existing corner reflector is not easy to adjust the angle after being fixed, and the technical scheme is as follows: the corner reflector comprises a corner reflecting plate, a vertical angle control device and a horizontal angle control device, the vertical angle control device has a movable part, the movable part of the vertical angle control device is connected with the corner reflecting plate, and is used for controlling the rotation angle of the corner reflecting plate in the vertical direction; the horizontal angle control device has a rotating part, the rotating part of the horizontal angle control device is connected with the vertical angle control device, and is used for controlling the rotation angle of the vertical angle control device in the horizontal direction, so as to control the rotation angle of the corner reflecting plate in the horizontal direction. The application can easily and accurately adjust the angles of the corner reflector in the horizontal and vertical directions, so as to satisfy the incidence of different satellite radar waves.

A ground system for satellite-borne synthetic aperture radar external correction comprises an antenna housing which is integrally provided with a receiving antenna and a transmitting antenna; the first azimuth angle adjusting device is used for adjusting the azimuth angle of the antenna shell; the second height adjusting device is used for controlling the height of the antenna shell; a satellite orientation control unit that receives a position of a satellite from the satellite or a satellite regulation server and controls the first azimuth angle adjustment device and the second height adjustment device such that the receiver and the transmitter point to the received position of the satellite; the receiving antenna is used for receiving a synthetic aperture radar signal of a satellite; the amplifier is used for amplifying the satellite radar signal of the receiving antenna; and a transmitting antenna that transmits the satellite radar signal amplified by the amplifier toward a satellite.

The application belongs to the technical field of meteorological information, and specifically discloses a meteorological big data intelligent diagnosis and early warning system and method. The system comprises a multi-source meteorological data acquisition device, an extreme event feature extraction unit, a tail correlation modeling module, a risk fluctuation quantification engine and a dynamic early warning response device. By fusing satellite, radar and ground observation data, high-order features of extreme weather are extracted, the nonlinear dependence relationship of multiple elements in the distribution tail is modeled by using a Copula function, the meteorological risk is quantified by introducing the financial option volatility rate idea, and a dynamic risk fluctuation index is generated. When the index exceeds the grading threshold, a conventional attention, high alert or emergency fuse type emergency response is triggered. Through the above technical scheme, the identification sensitivity and early warning timeliness of the "black swan" type extreme weather are improved, and high-precision and low-delay intelligent disaster prevention decision support is realized.

The application discloses a kind of synchronous satellite radar track initiation methods based on sky-wave gate correction, belong to the technical field of target tracking in radar data processing.This application is aimed at the problem of a large number of false tracks in track initiation in the target tracking of synchronous satellite radar.It includes establishing north-east sky right-angle coordinate system with sky-wave over-the-horizon radar receiving station as origin, determining the coordinates of synchronous satellite radar transmitting station, synchronous satellite radar receiving station and all measurement points in track initiation period;Determining the track tracking information of sky-wave over-the-horizon radar;According to the track information and state error of sky-wave over-the-horizon radar, establish the tracking gate of sky-wave over-the-horizon radar;Then, based on the traditional logical initiation method, establish the annular initiation gate of synchronous satellite radar;Finally, take the intersection of the annular gate of synchronous satellite radar and the tracking gate of sky-wave over-the-horizon radar as the correction gate of synchronous satellite radar, and perform track initiation, i.e.The starting track of synchronous satellite radar can be obtained.The application is suitable for track initiation in target tracking.

The application discloses a kind of lake satellite radar altimetry data screening processing method, device and electronic equipment.Therein, the method includes: obtaining random sample data from global lake satellite radar altimetry data;Wherein, the basic data required by random sample data includes global satellite altimetry data and lake boundary data;Random sample data is processed based on the preset graphical interface tool, and the echo waveform and multi-source auxiliary information corresponding to random sample data are shown;Wherein, multi-source auxiliary information includes multi-source footprint characteristic value and geographic location information;Random sample data is marked according to the category based on echo waveform and multi-source auxiliary information;Machine learning model training is carried out using random sample data of marked type, and the automatic classification model of lake satellite radar altimetry data is obtained.The application solves the technical problem of low sampling classification efficiency of lake satellite radar altimetry data.

The invention discloses an intelligent control method and system for an unmanned vehicle based on a satellite radar, and relates to the technical field of satellite radars, and the method comprises the steps: building a management and control system of the satellite radar based on each induction event, the working data of each radar module, and an interaction event between the radar modules; the dynamic control content of the unmanned vehicle is determined based on the management and control system of the satellite radar and the unmanned driving mode of the unmanned vehicle, the intelligent control event of the unmanned vehicle is determined according to the dynamic control content of the unmanned vehicle, the surrounding environment detected by the unmanned vehicle and the working process of the satellite radar, and the accuracy of the intelligent control event of the unmanned vehicle is improved. Therefore, the current control instruction of the unmanned vehicle is determined according to the intelligent control state of the unmanned vehicle, the driving scene where the unmanned vehicle is located and the previous control event of the unmanned vehicle, and the corresponding intelligent driving content is determined based on the current control instruction of the unmanned vehicle, the environment data detected by the satellite radar and the obstacle data. And the accuracy of the intelligent driving content is improved.

This utility model discloses an elevation angle adjustment device for satellite radar, belonging to the field of radar technology. It includes a fixed base with a fixing hole on one side. A support bar is connected above the fixed base, and a mounting plate is slidably mounted on the support bar. A connecting groove is formed on the mounting plate, and a fixing rod is connected above the mounting plate. A hollow column is connected to one side of the mounting plate, and a motor is fixedly mounted at one end of the hollow column. This elevation angle adjustment device for satellite radar, by starting the motor to rotate the threaded rod, causes a threaded sleeve that is threadedly engaged with the threaded rod to slide inside the hollow column. This causes the threaded sleeve to pass through the mounting plate and push a slider through the connecting sleeve, causing the slider to slide on a guide plate. Furthermore, due to the elongation of the threaded sleeve and the hollow column, a movable platform can simultaneously rotate around the fixing rod, thereby adjusting the angle of the movable platform and changing the elevation angle of the radar body. No manual climbing is required, making operation convenient.

The invention relates to the field of airport construction monitoring, in particular to an airport runway FOD recognition device and method.The airport runway FOD recognition device comprises a plurality of airport monitoring radars, satellite radars, infrared thermal imagers, wind speed sensors and wind direction sensors, and the airport monitoring radars, the satellite radars, the infrared thermal imagers, the wind speed sensors and the wind direction sensors are in signal connection with a monitoring system. The monitoring system is in signal connection with the meteorological system to obtain meteorological information, and the monitoring system is also in signal connection with an airport scheduling system. The method can predict the moving trajectory of the objects in the air, timely performs early warning in combination with the airport operation condition, realizes non-stop construction, and brings great help to the expansion of the airport.

The invention discloses an intelligent monitoring method and system for a waste dump slope and a related device, and relates to the field of area monitoring, and the method comprises the steps: obtaining a plurality of satellite images of the slope in an observation period through a satellite radar, and dividing the satellite images into measurement pairs; extracting pixel phase difference data of the target measurement pair, and converting the pixel phase difference data into initial deformation data; removing deformation interference data of the initial deformation data, and adjusting a phase value to obtain earth surface deformation data; calculating the accumulated deformation of the measuring points in the sight line direction of the satellite radar according to the earth surface deformation data of the measuring points in the target measuring pair, and obtaining the deformation field of the slope according to the accumulated deformation of the plurality of measuring points; and identifying a potential deformation area of the slope according to the deformation field of the slope, and evaluating the stability. Deformation monitoring is achieved through the satellite radar, large-scale image data are divided into measurement pairs, the calculation complexity during data processing is effectively reduced, and high-quality data are provided for deformation analysis. Therefore, slope deformation monitoring can be effectively carried out.

The invention discloses a landform deformation detection method and system based on a multi-satellite radar image, and the method comprises the steps: obtaining a radar image of a satellite, employing an interpretation neural network for the radar image, obtaining an interpretation image, inputting the interpretation image and the radar image to a preset image processing model, and obtaining a deformation video, and an image analysis model is adopted for the deformation video to obtain a detection result. According to the invention, the depth radar image and the fusion interpretation image are generated according to the radar images acquired by the satellite at different positions, so that the comprehensiveness or accuracy of landform detection space information is improved; and the deformation video is synthesized according to the depth radar images and the fusion interpretation images collected by the satellite at different times, so that the timeliness and the precision of deformation detection are enhanced.

The invention discloses a multi-satellite radar synchronous wave sending anti-interference method, system and platform based on time-frequency interleaving modulation, and the method comprises the steps: configuring trigger signals for satellite radars on a vehicle, and synchronously starting the wave sending of the radars in the same frame period; controlling a time difference t of a wave transmission start time delay between FOV overlapping radars satisfying [Delta] Fs + k * mod (t, T) gt; bIF, and tlt; the transmitting frequency difference of the FOV overlapping radar at any moment is larger than the BIF; [delta] Fs is the difference between the sampling starting frequencies of FOV overlapped radars, and a system and a platform corresponding to the method enable a plurality of radars to work simultaneously and do not interfere with each other. That is, all 76-79GHz bandwidths can be used without radars, and the range resolution is improved. Each radar can occupy the whole frame period to send waves, and the speed resolution and the signal-to-noise ratio are improved. The angle radar can adopt the same waveform, the number of calibration files and the storage space are reduced, and an additional MCU is not needed.

The invention relates to a system and a method for monitoring the impact of seismic events on the ground surface. The system includes a measurement infrastructure, a database and a computation layer and a data presentation layer. The measurement infrastructure consists of seismic sensors, global navigation satellite system (GNSS) receivers and a satellite radar interferometry system. Database and computation layer consists of a system trigger module, a file database, a pre-computation layer that processes data from the measurement infrastructure, a data processing modules, a relational database with spatial extension, which stores data about the shock that occurred and data obtained from data processing modules, an application layer, that prepares data from processing modules for visualization in graphical form. Data presentation layer provides an information portal with a graphical user interface (GUI), displaying in graphical form the data processed by data processing modules.

The invention provides a radar signal waveform optimization method and system based on a physical model and deep learning, electronic equipment and a storage medium, and relates to the technical field of physical models and deep learning, and the method comprises the steps: firstly, collecting the temperature distribution data and structural deformation data of each sub-array of a radar antenna array, synchronously acquiring an original beam directional diagram, and constructing a thermal deformation mapping database; calculating radar wavefront phase offset according to the database and the physical model, and performing phase compensation on the original beam directional diagram to generate a compensated directional diagram; then, a Riemannian manifold optimization algorithm is adopted to carry out optimization projection on the compensated directional diagram under constant modulus constraint, and a phase optimization waveform is formed; and finally, through adaptive threshold quantization processing of the lightweight deep learning network, discrete radar signal waveforms meeting satellite-borne requirements are output. According to the invention, the waveform fidelity and the imaging quality of the high-orbit satellite radar under the working condition of uneven solar irradiation are improved.

This invention relates to the field of functional composite materials and electromagnetic wave absorption technology, specifically to a Fe3O4-sulfonated phenylsilyl sesquioxane composite absorbing material, its preparation method, and its application. This invention involves blending magnetic Fe3O4 nanoparticles with porous sulfonated phenylsilyl sesquioxane. The magnetic Fe3O4 nanoparticles are uniformly distributed on the SOPS surface, improving the dispersion of the Fe3O4 nanoparticles and enhancing the lightweight nature of the composite absorbing material. The magnetic Fe3O4 nanoparticles and SOPS provide effective magnetic and dielectric losses, respectively. The heterogeneous interface between the magnetic Fe3O4 nanoparticles and SOPS improves polarization loss, enabling the composite material to possess both strong electromagnetic wave absorption and wide bandwidth characteristics. This meets the requirements of current satellite radar and electronic equipment for lightweight, strong absorption, wide bandwidth, and thin thickness in absorbing materials.

The present application belongs to the technical field of fire prevention monitoring, and specifically relates to a forest fire risk grade prediction method based on multi-source data, which acquires multi-source data of the micro environment in the forest, external meteorology, terrain and vegetation conditions through a gridded sensor network, satellite radar data and static geographic information, calculates a meteorological fire risk index, a ground condition index and a terrain fire risk index respectively after preprocessing, and introduces weight coefficients alpha, beta and gamma which dynamically adjust with the season, real-time weather, combustible material dryness and terrain, obtains a dynamic comprehensive fire risk index through weighted fusion, and improves the adaptability and accuracy of the method to different environmental conditions. While outputting the fire risk grade and early warning, data reliability evaluation is implemented to avoid misjudgment caused by data abnormalities or model limitations and to enhance the reliability and practical value of the method.

This invention discloses a method and system for identifying and interpreting short-duration rainstorms, belonging to the interdisciplinary field of hydrology, meteorology, and artificial intelligence. This invention integrates heterogeneous data from multiple sources, including FY-3GPMR satellite radar, IMERG satellite inversion, ground meteorological observations, and topographic data. After quality control, spatiotemporal matching, and bias correction, a high-resolution fused precipitation dataset is constructed. Based on a state machine model, short-duration rainstorm events with hourly rainfall ≥8mm are automatically identified, spatiotemporal features are extracted, and evolution patterns are analyzed. The three-dimensional vertical structure of the rainstorm is analyzed using satellite radar, and an EBOX interpretable Bayesian optimized XGBoost model is constructed. Combined with SMOTE equilibrium and SHAP interpretable analysis, accurate rainstorm identification and quantification of meteorological factor contributions are achieved, interpreting the convection development mechanism under key conditions such as low temperature and high humidity. This invention effectively improves the accuracy of local rainstorm identification and model interpretability, providing reliable technical support for urban meteorological early warning and disaster prevention and mitigation.

The invention discloses a graphene wave-absorbing material with a gradient porous structure and a preparation method thereof, the slow reduction characteristic of 1, 3-diaminoguanidine hydrochloride and the characteristic of different affinity of different solvents and graphene oxide are ingeniously combined, so that the 1, 3-diaminoguanidine hydrochloride can be converted into the graphene wave-absorbing material with the gradient porous structure. The 1, 3-diaminoguanidine hydrochloride solution is gradually distributed in the graphene oxide along with the mixed solvent, so that a structure of which the pore diameter is gradually reduced from the upper surface to the lower surface of the film to be nonporous is formed, and after low-temperature thermal reduction, carbonization and graphitization treatment, the electric conduction and heat conduction performance of a graphene skeleton is improved; therefore, the graphene material with efficient electromagnetic wave absorption and heat-conducting properties is successfully prepared and can play a key role in the fields of satellites, radars, stealth airplanes and the like.