38 results about "Satellite radar" patented technology

The present invention relates to a method and system for estimating forest carbon storage that combines artificial intelligence algorithms and multimodal remote sensing data. This approach comprehensively utilizes laser radar satellites, multi- / hyperspectral satellites, radar satellites, high-resolution optical imagery, etc. A hybrid technical system is employed for different forest coverage areas, resulting in high-precision forest carbon storage mapping with a resolution of 10 meters and area coverage. This provides technical support and assurance for assessing global forest carbon storage and supporting forestry carbon sequestration transactions.

The invention discloses a river and lake water level and flow prediction method and system in the field of remote sensing hydrology and hydraulic engineering, and the method comprises the steps: obtaining satellite radar altimeter data, river and lake water system data, rainfall inversion data and surface temperature inversion data based on a target river, a target lake and a watershed range file; taking the cross interval as a virtual hydrometric station observation point, extracting and processing waveform data, calculating water surface elevation information through a wavelet tracking algorithm, constructing an elevation profile group to establish an initial water level time sequence, and generating a river and lake water level inversion data set through fitting and elevation reselection. Meanwhile, NDWI data are obtained from satellite radar altimeter data, water surface width data are extracted, an inversion data set is formed by combining actually-measured river channel section data and a Manning formula inversion river channel flow rate, and finally various kinds of data are input into a pre-constructed intelligent prediction model to obtain future river and lake water level and flow rate change conditions. According to the invention, the precision of river and lake water level and flow prediction in areas lacking data is effectively improved.

The invention relates to a forest cultivation dynamic monitoring method and system based on a remote sensing technology, and the method comprises the steps: collecting point cloud and multi-source topographic data of a complex topographic region through the fusion of an airborne laser radar and a satellite radar technology, and generating a high-precision point cloud and topographic parameter matrix through denoising and registration; a segmentation threshold value is dynamically optimized in combination with topographic features, the canopy point cloud penetration rate of abrupt slope and valley areas is improved, and the problem of canopy missegmentation caused by uneven point cloud density under a complex terrain is solved; constructing a penetration rate compensation model driven by terrain influence factors, correcting laser radar point cloud deviation and inverting high-precision tree height, crown breadth and biomass parameters; and based on fusion analysis of the multi-temporal vegetation index and a machine learning model, early warning of diseases and insect pests and fire hazards and dynamic evaluation of a man-made forest cultivation effect are realized. According to the method, the bottleneck of complex terrain monitoring is broken through, the forest parameter inversion precision and the real-time response capability are remarkably improved, and technical support is provided for precise management of forestry resources.

The invention discloses a special terrain extraction method for water conservancy based on a laser radar and satellite remote sensing. The method comprises the following steps: acquiring satellite radar data and satellite remote sensing data of a preset area; performing comparison and discrimination area division according to the radar data and the remote sensing data to obtain a live area and a fuzzy area, and performing water conservancy boundary and terrain extraction on the live area to obtain first data; carrying out collaborative complementary measurement on the fuzzy region to obtain covered water conservancy data, and carrying out water conservancy boundary and terrain extraction on the covered water conservancy data by adopting a closed contour line to obtain second data; according to the first data and the second data, constructing a time sequence water conservancy topology dedicated terrain extraction model, and extracting water conservancy terrain data DEM1 of a preset area; and constructing a two-dimensional hydrodynamic model on the basis of the topographic data and the water conservancy boundary of the preset area to perform flood inundation simulation, extracting a wading area according to an inundation range, and generating water-land integrated HDEM data of the preset area.

The invention discloses a two-stage short temporary rainfall prediction diffusion model method based on a satellite cloud picture and an autoregression mechanism, and the method specifically comprises the following steps: firstly, inputting the monitoring data of the satellite cloud picture at the previous T1 moment, carrying out the interpolation processing, and finally carrying out the normalization processing; in the first stage, a satellite radar inversion network is utilized to invert an input satellite cloud picture sequence to obtain a radar echo picture sequence at a corresponding moment; in the second stage, aiming at time sequence features of a radar echo map sequence, through a constructed time sequence projection module based on a multi-scale partitioning technology and a KAN network and a motion module based on causal attention, aiming at space texture features, through splicing a previous time step inversion feature and current noise, a new input noise tensor is formed, and the new input noise tensor is input into the radar echo map sequence; fusing the captured features in the denoising network, and outputting a prediction result of the current target time step; and finally, gradually generating a video sequence with complete T2 duration. The problem of error accumulation in prediction can be effectively relieved, and the precision of rainfall prediction is improved.

The invention provides a radar sensing road monitoring data processing system and method, and relates to the technical field of radar data processing, and the system comprises the steps that a multi-source data collection module collects first radar data in a road field domain and second radar data of a designated local field domain through a satellite radar and an unmanned plane radar; a rockfall scale identification module performs scale feature identification of rockfall according to the second radar data to obtain rockfall scale features; the confidence coefficient analysis module analyzes the satellite radar confidence coefficient of the first radar data according to the rockfall scale features and local historical radar data of a specified local field domain, and performs rockfall scale feature recognition to obtain the rockfall scale features; and the data processing output module performs analysis according to the rockfall scale features, the rockfall scale features and the field historical radar data to obtain identification confidence, and analyzes and compensates the rockfall disaster rate as a monitoring data processing result. The technical problem that dynamic field domain highway disaster early warning reliability is insufficient in the prior art is solved.

The invention belongs to the technical field of earth surface monitoring, and particularly relates to a mine earth surface three-dimensional deformation continuous monitoring and early warning method which comprises the following steps: S1, InSAR monitoring data; meanwhile, the GNSS monitors the data; meanwhile, ground coordinates of the monitoring points are obtained; s2, establishing a fusion model; and S3, fusing the GNSS data and the InSAR data. According to the continuous monitoring and early warning method for the three-dimensional deformation of the mine earth surface in the technical scheme, the most advanced satellite radar technology is adopted to carry out time sequence monitoring on the earth surface and the structure of the mine area, high-precision three-dimensional data provided by the GNSS and continuous space monitoring data obtained by the InSAR are combined, and the defect that the InSAR can only obtain the deformation in the sight line direction can be effectively overcome; the fusion not only improves the precision of a monitoring result, but also enhances the reliability and practicability of data, and provides reliable technical and data support for regional surface deformation.

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 present invention discloses a satellite radar ground wheel speed measurement unequal spacing intelligent control electric seed drill, which relates to the technical field of seed drills, including a machine body, a satellite radar ground wheel speed measurement component installed on the machine body, a placement table and a support frame fixedly installed on the machine body, a seed box fixedly installed on the placement table, a tube 1 fixedly connected to the support frame, a plurality of tubes 2 slidably connected to the support frame, and a feeding component installed between the tubes 1 and 2 and the seed box. The advantages are: the satellite radar ground wheel speed measurement component facilitates the adjustment of the seed spacing before or during seeding according to the specific sowing area and the driving speed of the machine body, which facilitates better precision sowing, and with the cooperation of the seed drop sensor, the reseeding drive component and the control change component, the sowing can be effectively monitored. When missed sowing is detected, reseeding can be quickly carried out, effectively improving the uniformity and efficiency of seed sowing.

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.

The present application belongs to the technical field of aircraft guidance and landing design, and specifically relates to a method and system for guiding an aircraft to land on a ship deck. The method is designed to dynamically adjust the fusion weights #imgabs3#, #imgabs4#, and #imgabs5# of the guidance deviations detected by satellites, radars, and optoelectronic guidance equipment based on the relative sizes of the guidance deviations #imgabs0#, #imgabs1#, and #imgabs2# detected by satellites, radars, and optoelectronic guidance equipment. The guidance deviations detected by satellites, radars, and optoelectronic guidance equipment are fused, and the fused guidance deviations are used to automatically control the aircraft to land on the ship deck, thereby achieving non-similar triple-redundant configuration of the guidance deviations. The method can fully utilize the anti-interference capability and measurement accuracy of satellites, radars, and optoelectronic guidance equipment within different distance ranges to ensure the accuracy of the calculated fused guidance deviation #imgabs6#, achieve accurate guidance of the aircraft landing on the ship deck, and improve problems such as uneven data switching.

The invention belongs to the technical field of radar moving target detection, and particularly relates to a complex environment distributed spaceborne radar moving target adaptive fusion detection method, which comprises the following steps of S1, constructing amplitude and phase fusion detection quantity of each spaceborne radar; s2, estimating statistical distribution characteristics of amplitude and phase fusion detection quantity of each spaceborne radar; s3, optimally designing the detection false alarm probability of each spaceborne radar; s4, determining a detection threshold value of each spaceborne radar; s5, obtaining a binary detection result of each spaceborne radar; s6, performing optimal weighted fusion on binary detection results of all spaceborne radars in the distributed system to obtain a global detection quantity; and S7, judging a moving target through global detection. According to the method, the airspace freedom degree of the distributed multi-star radar can be better utilized, and the problem that the detection probability of the weak and small moving target under the strong clutter background is low in the prior art is solved.

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 provides an end-to-end meteorological prediction large model, and belongs to the technical field of meteorological prediction. According to the end-to-end meteorological prediction large model, original observation data of a satellite, a radar, a ground station and the like are directly accessed, and multi-source data feature fusion is realized through a space-time attention mechanism. Layers comprise a macroscopic layer, a microscopic layer and a physical constraint module, the macroscopic layer adopts a three-dimensional convolutional neural network to capture global atmospheric circulation features, and the microscopic layer introduces a graph neural network to process complex boundary conditions such as terrains and urban underlying surfaces. According to the end-to-end meteorological prediction large model, the precision is improved, and under a 100-meter grid, the root-mean-square error of temperature, wind speed and other elements is reduced. And the real-time performance is enhanced: the five-minute-level update supports real-time applications such as power load scheduling and low-altitude logistics route planning. And economical efficiency optimization: deploying based on edge computing nodes without a super computer, so that the hardware cost is reduced.

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 application discloses an interface modification method for enhancing mechanical properties of a wave-absorbing coating, an absorbent and a wave-absorbing coating, and belongs to the technical field of electromagnetic wave absorbing materials. The method is characterized in that: the surface of flaky magnetic metal micropowder is activated to improve the reaction activity of the surface of the absorbent; the flaky absorbent after activation is modified on the surface by fluorosilane; the grafting amount of fluorosilane is controlled, so that the surface of the flaky magnetic metal micropowder absorbent is grafted with appropriate fluorosilane, and part of active hydroxyl sites are reserved, thereby forming semi-fluorine modified absorbent in a semi-fluorine and activated state; and the semi-fluorine modified absorbent is used as an electromagnetic wave absorbing material for the wave-absorbing coating, so that the mechanical properties of the wave-absorbing coating can be enhanced. The semi-fluorine modified absorbent prepared by the application has good filling rate, mechanical properties and electromagnetic properties, effectively solves the problem that the existing wave-absorbing coating is difficult to consider mechanical properties and wave-absorbing properties at the same time, and has important uses in the fields of electronics, airplanes, satellites, radars, communication and the like.

The invention relates to the technical field of mountain building measurement, and discloses a mountain building measurement surveying instrument and method.The mountain building measurement surveying instrument comprises a base, a rotating assembly is arranged on the outer wall of the base, a telescopic rod is installed at the bottom of the base through a connecting handle, a connecting disc is fixedly assembled on the outer wall of the telescopic rod, and a sliding rod is installed at the bottom of the base; and the bottom of the sliding rod is in threaded connection with a rotary knob, an inserting body is fixedly assembled at the bottom of the telescopic rod, and a surveying and mapping assembly is arranged at the top of the rotating assembly. According to the measuring and surveying instrument and method for the mountain building, the bubble observer and the round bubble as well as the eyepiece and the objective lens are matched for use, errors generated during measurement can be effectively reduced, and in addition, due to the characteristic that the satellite radar is embedded in the inner cavity of the connecting base, the measurement accuracy is improved. And the safety degree of workers during mountain building measurement can be further improved, dangerous accidents are reduced, and the safety of the device is improved.

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.

A system and a computer-implemented method of monitoring railway infrastructure are provided. The system comprises a memory storing processor-executable instructions; and a processor communicatively coupled to the memory. The instructions configure the processor to: receive sensor data from multiple sensors indicating a condition of the railway infrastructure and a subsurface associated with the railway infrastructure; receive satellite radar data indicating terrain stability associated with the railway infrastructure; identify a defect associated with the railway infrastructure by inputting the sensor data and the satellite radar data into one or more trained machine learning models; and provide, via a user interface, a monitor output for the railway infrastructure based on the identified defect.

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 embodiment of the invention provides a satellite-ground radar collaborative observation method and system based on a sensitive target, and is applied to the technical field of weather radars. The method comprises the following steps: acquiring satellite, radar and underlying surface data; performing identification processing on the radar data to obtain the number, the position and the area of potential targets and the early warning level corresponding to each potential target, and comprehensively obtaining a satellite-ground joint early warning level; constructing a sensitive target evaluation function and calculating a sensitivity score by using the underlying surface data, the potential target and the satellite-ground joint early warning level; and permutation and combination are carried out on the sensitive target and the radar scanning mode, and optimization processing is carried out to select an optimal scanning mode. In this way, real-time tracking and dynamic monitoring of severe convective weather can be achieved, a plurality of weather radars are guided to efficiently carry out collaborative operation, and the observation timeliness and early warning reliability of the highly-disaster-causing severe convective weather are improved.

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.