35 results about "Optical radar" patented technology

The invention discloses a forest grass wet carbon sink metering method and system, and relates to the field of carbon sink metering, and the method comprises the following steps: 1, collecting and processing multi-source data, 2, fusing the data, aligning the multi-source data, adopting a geographic registration and time synchronization technology, and unifying a spatial resolution and a timestamp, and 3, extracting features. 4, constructing a carbon sink dynamic model; and 5, carrying out carbon sink visualization and decision support. According to the forest and grass wet carbon sink metering method and system, multi-source data collaboration is achieved, optical, radar and laser radar data are fused, the defect that traditional carbon sink metering depends on ground sample plot survey or single remote sensing data is overcome, carbon sink contributions of forests, grass and wet lands are accurately distinguished, the overall spatial resolution is higher, cloud and mist interference is avoided, the single data source error is solved, and the measurement accuracy is improved. Through multi-source data fusion and dynamic model optimization, high-precision measurement and real-time monitoring of forest grass wet carbon sink are realized.

The invention relates to the technical field of remote sensing image processing, in particular to a wetland information extraction method and system based on multi-source remote sensing data fusion, and the method comprises the following steps: obtaining and fusing a wetland optical radar image and water level time sequence data, extracting near-infrared and back-scattering multi-source characteristic parameters to discriminate water body pixels, and extracting a water body image; and carrying out statistics on spatial connectivity aggregation to generate a water body plaque boundary, calculating an area perimeter and shape index comprehensive model to classify wetland types, and adjusting mismatching labels in combination with vegetation coverage and soil moisture to form a wetland information extraction result map. According to the method, the water body differential expression is enhanced through combined reflection and scattering characteristics, the water body and peripheral differential expression is enhanced through combined reflection and scattering characterization, boundary transition aliasing is restrained through bidirectional threshold constraint, plaque space integrity is restored and maintained through connectivity analysis, and type classification sensitivity is enhanced through morphological parameter combination. And the wetland expression accuracy and the type stability are improved through ecological attribute consistency correction.

The invention belongs to the technical field of remote sensing image processing agricultural information, and particularly relates to a DS-xNet-based multi-source remote sensing time sequence data cultivated land utilization current situation extraction method. According to the method, the cultivated land and the water body can still be reliably recognized under the cloud or fog condition by combining Sentinel-1 and Sentinel-2, missing detection and misjudgment caused by cloud shielding are reduced, sNET captures short-term dynamic conditions, and mNET matrix memory enhances long-term dependence modeling, so that the recognition precision of seasonal and interannual changes is improved, supervision is applied to a branch and fusion layer, and the recognition accuracy of the cultivated land and the water body is improved. According to the method, each branch can learn independent discrimination capability and can cooperatively improve fusion output, over-fitting is reduced, generalization capability is improved, training convergence is accelerated, channel splicing retains discrimination information of each modal in a fusion stage, modal information conflict or loss caused by direct early fusion is avoided, classification accuracy is improved, and classification efficiency is improved. Various optical and radar indexes are combined and used to enhance the distinguishing capability of paddy fields, irrigation areas, different crops and non-cultivated areas.

The invention discloses a method for identifying an epimedium koreanum planting area based on multi-source remote sensing image fusion in the technical field of under-forest planting, and the method comprises the steps: obtaining multi-source remote sensing data of a target area, carrying out the preprocessing, and carrying out the recognition of an epimedium koreanum planting area based on the preprocessed multi-source remote sensing data; extracting multi-source feature data related to under-forest planting of the Korean epimedium, fusing the extracted multi-source features, inputting the fused multi-source features into a deep neural network classification model of a cross-modal attention mechanism, processing the fused multi-source features, and obtaining a deep neural network classification model of the cross-modal attention mechanism; according to the method, multi-source remote sensing data advantages of optics, radars, laser radars and the like are integrated, the limitation of a single data source in under-forest environment monitoring is overcome, and the method has the advantages of being high in accuracy, high in accuracy and high in reliability. And aiming at special growth requirements of the epimedium koreanum, key parameters such as canopy density and gradient are quantified, and accurate evaluation of ecological suitability is realized.

The invention discloses a land type intelligent identification and updating method and system for land investigation, and relates to the technical field of land investigation and remote sensing land type identification, and the method comprises the steps: carrying out the unified coding and weight fusion of optical, radar, terrain and auxiliary features on a standardized land block image stack through a feature fusion and dimension reduction model; generating plot-level fusion feature representation; jointly inputting the land block level fusion feature representation and the pixel statistical features in the land block into a land class recognition model, outputting a land block level land class category and confidence through a double-layer fusion structure, and generating a multi-temporal land class recognition result; and calculating a change credibility score of the land parcel based on a multi-temporal land class identification result and a time sequence observation index, and determining whether the land parcel belongs to a stable state, a suspected change or a confirmed change by comparing an index trend, class stability and space consistency. According to the method, collaborative identification of macroscopic structure information and microcosmic detail information is realized, and the accuracy and the spatial integrity of regional land class classification are improved.

The present invention provides a multi-modal retrieval method and device for flood events based on a semantic enhancer, which relates to the technical field of data retrieval. The method includes: performing multi-level semantic enhancement on keywords through a global flood event knowledge base and Internet news information included in the semantic enhancer, and then performing quality-first retrieval and preliminary screening to obtain multi-source remote sensing images to be matched. Next, corresponding optical and radar image features and context semantic features of the semantically enhanced text are extracted from the image modality and the text modality respectively. Then, the features of the image modality and the text modality are fused to obtain multi-modal fusion features, and the similarity between the semantically enhanced text and the multi-source remote sensing images to be matched is mapped. Finally, the retrieval result of the keywords is determined. Through this application, the problems of low retrieval matching degree and low retrieval efficiency caused by lack of semantics and difficulty in obtaining event-related spatio-temporal ranges in the retrieval of flood event remote sensing data are solved.

This invention relates to the field of optical imaging technology, specifically providing an optical radar co-aperture off-axis imaging system, comprising: an off-axis mirror assembly, a frequency-splitting device, a radar transceiver system, and an optical imaging system. The frequency-splitting device is disposed in the rear optical path of the secondary mirror and is used to reflect light waves and transmit microwaves. The frequency-splitting device includes a frequency-selective surface, which comprises an FSS pattern layer and a bias line layer. The FSS pattern layer includes periodically arranged FSS units. Nonlinear capacitors are electrically connected to the FSS units. The bias line layer applies a voltage to the nonlinear capacitors according to the received microwave band. By changing the voltage applied to the nonlinear capacitors, the resonant frequency of the FSS units is tuned, thereby changing the microwave passband frequency of the frequency-splitting device. This invention not only achieves a reflective wave-transmitting microwave design but also solves the problem that transmitting only a single band of microwaves in microwave-transmitting and light-reflecting methods is difficult to adapt to different task requirements.

The invention discloses a method for quickly and dynamically reconstructing an ultra-long-distance air-to-air killing chain, belongs to the technical field of ultra-long-distance air-to-air killing chains, and realizes dynamic recombination of the killing chain by using a self-organizing iterative clustering algorithm. In the execution process of the killing chain, if a reconstruction condition is triggered, all the combat platforms in normal operation are divided into six clusters according to the execution stages of discovery, positioning, tracking, aiming, combat and evaluation, each cluster is divided into different groups according to different loads loaded by the combat platforms, and the loading loads comprise ESM, light thunder and radar; for the combat platforms loaded with the same load, dividing the combat platforms in the same area into the same cluster by taking the current position as a division condition; all the combat platforms are subjected to dimension reduction clustering in sequence. According to the method, the high-dimensional complex calculation degree generated in the killer chain reconstruction process is subjected to dimension reduction processing, the calculation amount is remarkably reduced, and the reconstruction time is shortened.

The application provides a kind of full optical radar image target identification system and method based on MZI, the system includes: laser light source, for emitting laser;Beam splitter, for the received laser is divided into N road laser with equal power;Detection array, for converting target image information into n1 road radar receiving signal;MZI modulation array, for n1 road radar receiving signal is modulated to N road laser, and output M road modulated laser;Phase control unit, for output n2 road control signal;MZI operation array, for according to n2 road control signal, phase adjustment is carried out to M road modulated laser, and output n road adjusted laser;Photoelectric conversion unit, for converting n road adjusted laser into n road electric signal, according to n road electric signal realizes the identification and classification of target image information.The application can solve the technical problems that the hardware computing power of the electronic calculation of the identification system in the prior art is difficult to be greatly improved.

This invention discloses a method, system, terminal device, and storage medium for inverting crop lodging parameters. The method includes: acquiring satellite optical radar remote sensing information and UAV optical radar remote sensing information; extracting features from the satellite optical radar remote sensing information and UAV optical radar remote sensing information to obtain remote sensing image feature information; fusing multi-source heterogeneous information from the remote sensing image feature information to construct a remote sensing image dataset; inputting the remote sensing image dataset into a deep neural network model for model training to obtain a crop lodging parameter inversion model; acquiring crop lodging image data; and inputting the crop lodging image data into the crop lodging parameter inversion model to obtain crop lodging parameters. This invention obtains rich crop lodging information by fusing satellite optical radar remote sensing information and UAV optical radar remote sensing information, and then inverts the lodging parameters through a parameter inversion model to obtain high-precision crop lodging parameters.

The application provides a broadband wide-angle scanning microstrip antenna unit structure and an antenna array. On the basis of ensuring a low profile of the antenna, the broadband wide-angle scanning capability of the microstrip patch antenna is realized through structural design, meanwhile, space is reserved as a design area of an optical radar, and an antenna unit for integrated design of an optical / electrical radar array is realized. Technical problems that the antenna bandwidth is narrow in the prior art, and the profile, volume and weight of the antenna affect the performance of the radar are solved.

A system for establishing augmented reality includes an optical radar and a processor. The optical radar is used for scanning a real scene to obtain three-dimensional space information. The real scene includes a target object having a first size. The processor communicates with the optical radar. And the processor is used for converting the three-dimensional space information into a point cloud picture and running a virtual environment development engine. And the virtual environment development engine is used for establishing a virtual scene corresponding to the real scene and establishing a virtual object corresponding to the target object according to the point cloud picture. The virtual object has a second size. The virtual environment development engine is further used for setting a second size of the virtual object according to a proportional relation and establishing augmented reality elements around the virtual object to present the job content corresponding to the target object. According to the system for establishing the augmented reality, virtual-real integration of the augmented reality can be realized, the virtual construction object and the real scene are integrated, and the real scene operation is guided by virtual elements.

This invention relates to the field of remote sensing image processing technology, specifically to a method and system for wetland information extraction based on multi-source remote sensing data fusion. The method includes the following steps: acquiring and fusing wetland optical radar images and water level time-series data; extracting near-infrared and backscattering multi-source feature parameters to distinguish water body pixels; statistically aggregating spatial connectivity to generate water body patch boundaries; calculating a comprehensive model of area, perimeter, and shape index to classify wetland types; adjusting mismatched labels by combining vegetation cover and soil moisture; and forming a wetland information extraction result map. In this invention, the differences in water bodies are enhanced through joint reflection and scattering features; the differences between water bodies and their surroundings are enhanced through joint reflection and scattering characterization; boundary aliasing is suppressed through bidirectional threshold constraints; patch spatial integrity is restored through connectivity analysis; the sensitivity of type classification is enhanced through morphological parameter combinations; and the accuracy and type stability of wetland representation are improved through ecological attribute consistency correction.

The invention discloses an unmanned aerial vehicle optical radar detection system and method and an unmanned aerial vehicle, and belongs to the field of unmanned aerial vehicles. Comprising a detection subsystem, a turntable subsystem, an image processing subsystem and a display control subsystem. Wherein the rotary table subsystem comprises a rotary table, and the detection subsystem is loaded in the rotary table, so that when the rotary table rotates, the detection subsystem can obtain image information of different orientations and different pitching angles. In this way, images in multiple directions and angles can be obtained without installing multiple cameras, and the cost of the unmanned aerial vehicle is greatly reduced.

The invention discloses a disease and insect pest detection system for agricultural planting, and relates to the technical field of image analysis, the disease and insect pest detection system comprises a scanning module, an information processing module, a leaf segmentation module and a disease and insect pest qualitative module, the information processing module carries out space-time synchronization on original data from the visible light camera, the infrared thermal camera and the optical radar and carries out preprocessing on the original data, and the leaf segmentation module is responsible for inputting the processed data into a proper segmentation model so as to realize accurate identification and segmentation of crops in a planting area. The plant disease and insect pest qualitative module is responsible for carrying out qualitative treatment on plant disease and insect pest conditions according to leaf segmentation results, the scanning module comprises a visible light camera, an infrared thermal camera and an optical radar, the visible light camera is used for capturing high-resolution images above legume crops in a planting area, and the plant disease and insect pest qualitative detection system has the advantage of omnibearing detection.

The invention provides a laser transmit-receive system, an assembly method and an optical radar. The laser transmit-receive system comprises an optical chip used for receiving a light beam generated by a laser light source transmitted by an optical fiber array through an input coupling end; the input coupling end is step-shaped; grooves corresponding to the light beams in number are formed in the surface of the lower step and are used for correspondingly placing optical fibers for transmitting the light beams in the optical fiber array; a spot size converter is correspondingly arranged on the connected end face of the upper-layer step and the lower-layer step; waveguides are arranged in a manner of extending towards the upper step along the length direction of the corresponding groove, so that the cross sections of the optical fibers are coupled with the corresponding spot size converters, and light beams in the optical fibers are transmitted to the corresponding waveguides; the optical fiber is arranged on the base and is covered and pressed by the cover plate; the arrangement of the optical fibers on the base corresponds to the arrangement of the grooves; the side, in butt joint with the optical chip, of the optical fiber extends out of the base by a first length, so that pressure is applied to the optical fiber through a cover plate on the extended optical fiber, and the extended optical fiber is pressed into the corresponding groove. The production efficiency is improved.

An optical radar test system comprises a cavity, two arc-shaped slide rails, an environment control device, a ground structure, an erection platform, a slide rail system and a test target object. The arc-shaped sliding rail is located in the cavity. The environment control device is hung between the two arc-shaped sliding rails through a bearing and is provided with a plurality of scene control modules. The ground structure is located in the cavity and located between the two arc-shaped sliding rails and below the environment control device. The erection platform is located at a first endpoint of a midline of the ground structure and is configured to erect an optical radar. The sliding rail system is located above the center line of the ground structure and is horizontally arranged. A test target object is arranged on the slide rail system. The optical radar test system comprises a plurality of scene control modules, so that the performance of the vehicle-mounted radar on different test targets under different weather conditions can be simulated in the same cavity, a large amount of data feedback can be obtained in a short time, and the research and development speed is improved.

The utility model relates to the technical field of optical instruments, and particularly discloses a non-charged radar receiving device based on a laser reflection principle, which comprises a laser emission optical fiber, a reflection type optical thin film assembly and a laser receiving optical fiber. The laser emitting optical fiber and the laser receiving optical fiber are located on the two sides of the outer portion of the opening of the reflective optical thin film assembly respectively and are symmetrically distributed. According to the utility model, the optical fiber medium replaces an electronic loop, and a physical isolation type signal channel is established; optical modulation and spatial distribution optimization of laser signals are realized through the concave disc-shaped reflecting film; a symmetric optical fiber array is constructed to improve the optical signal capturing efficiency, and an all-optical radar receiving solution with interference resistance, electromagnetic pulse interference resistance and high fidelity is formed.

This application relates to a method and apparatus for optical-radar ISAR image conversion based on generative networks. The method includes: analyzing and modeling the physical characteristics of the target in the ISAR image, and using a deep learning network as the main technical means to incorporate the distribution characteristics of ISAR scattering points into the loss function of the network training, ultimately converting the optical image of the target into the corresponding ISAR image. The constraint that the scattering point position matrices extracted from the original ISAR image and the reconstructed ISAR image are equal is added to the loss function, enabling the deep learning network to generate more realistic ISAR images.

The invention provides a vegetation carbon income and expenditure evaluation method and system based on remote sensing image data, and belongs to the field of ecological environment monitoring. The method comprises the following steps: synchronously acquiring optical, radar and hyperspectral multi-source remote sensing images, and extracting characteristic parameters such as a vegetation index, a leaf area index, biomass and carbon reserve after preprocessing by radiation correction, geometric correction and atmospheric correction; and constructing a CNN-RNN hybrid model, fusing spatial-temporal characteristics to learn a carbon cycle rule, and outputting carbon absorption, carbon emission and net income and expenditure results. The system integrates a data acquisition module, a preprocessing module, a feature extraction module, a model operation module and a result output module, and full-process automation is achieved. The method breaks through the limitation that a traditional method is insufficient in space coverage and low in timeliness, improves the evaluation precision and efficiency, and provides powerful support for ecological protection and climate change research.

The present invention discloses a map discovery method and system. The map discovery method includes the following steps: scanning the surrounding area with a lidar having a scanning radius of A; defining the area that can be scanned by the lidar as the first layer; defining a circular area centered on the lidar with a radius of B as the second layer, where B is less than A; and moving the lidar to different positions until the second layer covers the first layer; thereby mapping while moving the lidar.

The application discloses a kind of air-to-air missile interception probability sensitivity analysis method based on agent model.Interception probability has important significance in missile composite guidance, determines the miss distance and hit probability of missile terminal guidance phase, to effectively improve the interception performance of missile during midcourse guidance and terminal guidance shift, it needs to carry out sensitivity analysis on each error that influences missile interception probability, through sensitivity analysis, the influence size of each error is quantified.However, the timeliness of traditional interception probability calculation method is poor, to solve this problem, the application establishes the support vector machine agent model of particle swarm optimization, to obtain the interception probability calculation model with higher timeliness and accuracy.Based on the agent model, the sensitivity coefficients of 18 kinds of errors are calculated by Sobol index method.The results show that radar angle measurement error and optical radar angle measurement error have the greatest influence on air-to-air missile interception probability.The method shortens the calculation time while ensuring the accuracy, and provides a basis for further sensitivity analysis.

The invention provides a pine wood nematode disease monitoring method and system based on a remote sensing satellite, and relates to the technical field of image data processing. The method comprises the following steps: firstly, acquiring and preprocessing optical, radar and thermal infrared remote sensing data of a forest region; then labeling the pine wood nematode disease infected wood sample in the optical image, and cutting all data sources into image tiles which are spatially aligned; then extracting physical features from each image tile, calculating a multi-modal infected index, and fusing the index into the optical image tiles at the same spatial position to construct a sample data set containing multiple features and labels for training and verifying a deep learning monitoring model; and finally, carrying out disease monitoring by using the trained model, and outputting a pine wood nematode disease monitoring result. And various remote sensing data are cooperatively fused as input features of the deep learning model, so that the monitoring reliability is greatly improved, and false alarms are avoided. Meanwhile, early-stage infected trees are found in time, and the monitoring timeliness is improved.

This paper proposes a method for inverting mangrove water content and dry matter content based on fractional-order assisted spectral angle mapping. The method includes: acquiring mangrove functional trait parameters, leaf hyperspectral data, and multi-source satellite remote sensing image data; proposing a novel fractional-order assisted spectral angle analysis method; proposing satellite-ground spectral matching and inversion verification methods to construct, reduce, and optimize the inversion dataset; and proposing multiple inversion schemes that fuse optical, radar, and thermal infrared data to construct a multi-source hybrid dataset and a hybrid estimation model for mangrove canopy water content and dry matter content. The method can match the sensitive spectral domain obtained from ground-based spectra with satellite bands, thereby enabling widespread and accurate inversion of mangrove water content and dry matter content, enabling low-cost, accurate, and rapid monitoring of mangrove growth status and coastal environment.

This system is designed for establishing augmented reality and includes the following components: an optical radar configured to scan a real scene to obtain three-dimensional spatial information, where the scene includes a target object of a first size; and a processor connected to the optical radar. The processor converts the three-dimensional spatial information into a point cloud map and executes a virtual environment development engine. This engine creates a virtual scene corresponding to the real scene and generates a virtual object corresponding to the target object based on the point cloud map. The virtual object has a second size, set according to a default proportional relationship, and the engine establishes augmented reality elements around the virtual object to present operational content related to the target object.

The utility model relates to the technical field of ocean optical radars, in particular to a laser radar device for seawater multi-parameter detection, which comprises a laser transmitting assembly, a signal receiving assembly and a data acquisition and signal processing assembly, and is characterized in that the signal receiving assembly comprises a coaxial receiving view field channel and a paraxial receiving view field channel; the laser emission assembly emits a laser beam, an echo light signal generated by interaction of the laser beam and a water medium is received by the signal receiving assembly and converted into an electric signal, and the data acquisition and signal processing assembly acquires the electric signal and performs data processing on the electric signal; the receiving optical axis of the coaxial receiving view field channel coincides with the emission optical axis of the laser beam, and the receiving optical axis of the paraxial receiving view field channel is parallel to the emission optical axis of the laser beam. By arranging coaxial and paraxial double receiving view field channels, 532nm parallel and vertical polarization signals, water Raman signals and chlorophyll fluorescence signals can be detected at the same time.

The invention relates to the technical field of optical imaging, and particularly provides an optical radar common-aperture off-axis imaging system, which comprises an off-axis reflector group, a frequency division light splitting device, a radar transceiving system and an optical imaging system, and is characterized in that the frequency division light splitting device is arranged on a rear-end light path of a secondary mirror and is used for reflecting light waves and transmitting microwaves; the frequency division light splitting device comprises a frequency selection surface, the frequency selection surface comprises an FSS pattern layer and a bias line layer, the FSS pattern layer comprises periodically arranged FSS units, the FSS units are electrically connected with a nonlinear capacitor, the bias line layer is used for applying voltage to the nonlinear capacitor according to the wave band of received microwaves, and the nonlinear capacitor is connected with the frequency selection surface. The resonant frequency of the FSS unit is tuned by changing the voltage applied to the nonlinear capacitor, so that the microwave passband frequency of the frequency division light splitting device is changed. According to the invention, the reflection wave and microwave transmission design is realized, and the problem that only single-band microwaves are transmitted and different demand tasks are difficult to adapt in a microwave and reflection wave transmission mode is solved.

The present invention relates to the technical field of lidar detection, and particularly to a measurement method, system and medium of an LED lidar based on pseudo-random modulation. The method modulates an LED beam generated by an LED light source based on a target pseudo-random code to obtain a modulated beam, and emits the modulated beam; receives the backscattered light of the modulated beam, preprocesses the backscattered light, and converts the preprocessed backscattered light into an electrical signal; uses a photon counter to perform high-speed integration operation compensation processing on the electrical signal; demodulates the electrical signal, and calculates the aerosol extinction coefficient in the environment to be measured according to the demodulation result. In this way, the influence of optical noise can be reduced, and the LED lidar system can be adapted to daytime use.

The present application discloses a type of optical radar, a mobile device, and a method for measuring an optical radar attachment. The optical radar comprises a transmit / receive assembly, a diffuser, a measurement module, and a control module. The transmit / receive assembly is used to emit a transmitted laser beam and to receive an echo laser beam. The diffuser is installed in an optical path corresponding to the transmit / receive assembly, and a portion of the transmitted laser beam emitted from the transmit / receive assembly is reflected by the diffuser to form a reflected laser beam. The reflected laser beam includes a mirror-reflected laser beam. The measurement module is used to receive the reflected laser beam and also to generate a corresponding electrical signal. The control module is electrically connected to the transmit / receive assembly and the measurement module, and the control module is configured to determine whether an attachment is attached to the diffuser based on the corresponding electrical signal. With this design, the presence of an attachment on the diffuser can be effectively tested, thereby improving the measurement accuracy of the optical radar.

The invention discloses a river water level time sequence encryption method for an observation station missing region based on a remote sensing virtual station, and the method comprises the steps: taking a measurement foot point of a satellite-borne satellite altimeter as a virtual station of a river channel, and extracting a river reach water area based on the satellite height measurement data of a river reach where the virtual station is located at the same time and a remote sensing image; and constructing an empirical model of the water level and the water area of the river virtual station. And encrypting a long-time-period, high-time-frequency and near-real-time river water level time sequence by using the empirical model and a water area time sequence observed by a remote sensing virtual constellation in a high-time-frequency manner. The method is mainly oriented to an observation station missing area, the defect of low time resolution of satellite height measurement is overcome through the high time frequency observation advantage of a virtual constellation constructed by multi-source optics and radar remote sensing satellites, and method support is provided for understanding the river hydrological situation time-space evolution characteristics of the observation station missing area.