40 results about "Radar backscatter" patented technology

A method and tool using a continuous electromagnetic wave from a transverse magnetic-dipole source with a coaxial electric-dipole receiver is described for the detection of external sidewall cracks and other anomalies in boiler tubes and other enclosures. The invention utilizes the concept of radar backscatter rather than eddy-currents or ultrasound, which are sometimes used in prior art crack-detection methods. A numerical study of the distribution of the fields shows that the direct transmission from the source to the receiver is reduced from that in free space. Further, if the diameter of the receiver dipole is made sufficiently small, it should be possible to detect cracks with a scattering loss of up to -40 dB in thin-walled boiler tubes.

The present invention relates to a polarimetric calibration technique based on natural distribution scenes and a rare calibrator, which is used for the calibration and correction of distorted polarimetric synthetic aperture radar (SAR) data. The present invention breaks the calibration bottleneck of domestic machine-borne polarimetric SAR data, and develops a technique which utilizes widely distributed natural ground objects for the crosstalk calibration of polarimetric data without the help of an artificial corner reflector and needs only one or a small amount of triple-sided corner reflectors for the calibration of the imbalance of polarimetric receiving channels. In addition, the technique uses the strength change of natural ground object scenes with wide similar radar backward scattering properties in the distance direction to fit out an antenna directional pattern, and fully utilizes polarimetric ground object information to correct all the polarimetric SAR channel data with the same antenna directional pattern, thereby retaining the polarimetric scattering characteristics of ground object targets before and after correction.

The invention discloses a combined optimization algorithm of an inheritance multi-output support vector machine. The combined optimization algorithm combines with measured radar back scattering data for fast inversion of single-layer earth surface (root-mean-square height ksigma<1.5, and root-mean-square slope s<0.3) dielectric parameters and roughness parameters. The algorithm includes: using single-layer earth surface HH and VV measured polarizing radar back scattering coefficient data to obtain homo-polarization ratio; using a rough earth surface electromagnetic scattering small slope approximation method to calculate back homo-polarization ratio; combining a genetic algorithm with the small slope approximation homo-polarization ratio and the measured data to invert the earth surface dielectric constant; substituting the inversion result into an electromagnetic scattering integral equation model to generate a data file of back scattering coefficient changing with roughness; combining two kinds of measured polarized radar back scattering data to form a target function, using M-SVR optimization algorithm to invert the earth surface roughness parameters, and evaluating inversion errors and efficiency. By the combined optimization algorithm, real-time prediction of earth surface parameters can be achieved while inversion precision is guaranteed.

The invention discloses an ocean wind-field retrieval method of a double-frequency coplanar synthetic aperture radar (SAR), relates to the technical field of remote sensing, and aims at developing a new ocean wind-field retrieval method according to the ocean detection characteristics of the double-frequency coplanar SAR. The method comprises the steps of performing radiometric calibration for an SAR image to obtain the calibrated SAR image; analyzing calculating backscattering coefficients through L-waveband and C-waveband geophysical model functions; then performing simultaneous restructuring for the L-waveband and C-waveband geophysical model functions to obtain the minimum cost functions; directly solving to obtain the ocean wind speed and wind direction; removing fuzzy wind direction. With the adoption of the method, the problem that the SAR ocean wind-field retrieval method depends on the background field wind direction data and wind stripes can be effectively solved, high-precision ocean wind speed and wind direction can be inverted directly through the back scattering of the radar, and therefore, the support is provided to the service application of the SAR ocean wind-filed detection.

The invention discloses a low-altitude wind shear three-dimensional backscattering wave simulation method for an airborne meteorological radar. The low-altitude wind shear three-dimensional backscattering wave simulation method comprises the following steps: establishing a three-dimensional meshed computational domain by utilizing scene parameters including a scene range and boundary conditions; performing fluid simulation on the computational domain to generate original wind field data; correcting the original wind field data; establishing an simulation scene and reading the corrected wind field data according to settings of the scene parameters; according to the simulation scene, simulating low-altitude wind shear of the airborne meteorological radar, and performing coherence stack on scattering points within a radar beam to form a radar backscattering wave signal of a scanning direction; respectively updating airplane position information, corrected wind field data and radar beam angle scanning information by utilizing the airborne parameters, the scene parameters and the scanning parameters; judging whether the scanning is completed or not according to a scanning range of the radar parameters. The method can be used for truly reflecting meteorological characteristics of the wind shear three-dimensional backscattering wave signal, so that the simulation data is effective and reliable.

The invention relates to a rapid analogue method of SAR large range forest scene remote sensing data, belonging to the technical field ofremotely sensing the SAR forest. The method comprises the following steps of: defining parameters, dividing scenes, acquiring the central position of a virtual scattering unit and equivalent radar backward scattering coefficients, and calculating SAR forest remote sensing analogue data. The method in the invention performs equivalent to SAR echo signal response of a plurality of real scattering units of the forest scene by the echo signal response of the virtual scattering unit through the equivalent scattering processing method so as to reduce the quantity of forest scene virtual scattering unit, achieve the purpose of improving the data analogue efficiency of SAR original echo data and realize rapid high-precise analogue of the large range forest remote sensing original data under a high resolution SAR system.

The invention discloses a leaf area index acquisition method and a system. The method comprises the following steps of firstly, acquiring the SAR images and the optical images of crops to be tested, carrying out ground control point registration on the SAR images and the optical images and acquiring image data; according to the image data, a vegetation water content measured actually, surface soilmoisture and a roughness parameter, determining an attenuation coefficient in an improved water cloud model and a radar backscattering coefficient when a crop canopy is closed and acquiring a crop total backscattering coefficient model; and then, according to the image data and the crop total backscattering coefficient model, inverting so as to obtain the vegetation water content, and then estimating the leaf area index of the crops to be tested. In the invention, radar remote sensing and optics are combined and are applied to the improved water cloud model; the advantages of the radar remotesensing and the optics are fully used to invert crop biological parameters; and vegetation coverage and effects of bare soil on radar signals are separated and inversion precision is increased.

The invention discloses a numerical simulation method for a radar backscattering section of a wave-current coupling sea surface. The method comprises the following steps: setting sea surface simulation parameters and radar parameters to establish a wave-current coupling electromagnetic scattering model according to a sea surface state to be simulated by a user and an adopted radar sensor type; acquiring a wave-current coupling sea surface evolution process and a representative transient sea surface; further inversing a radar backscattering coefficient gamma and deducing a normalized radar backscattering section sigma 0 according to the wave-current coupling electromagnetic scattering model by virtue of the Huygens principle, Kirchhoff approximation and a Dirac green function. According to the method, a wave-current coupling sea surface and electromagnetic wave interaction mechanism can be acquired, researches on wave-current coupling electromagnetic scattering characteristics can be promoted, and the method can be adopted as a technical means for research and development of sea current radar retrieval.

A synthetic aperture radar hybrid-quadrature-polarity method and architecture comprising transmitting both left and right circular polarizations (by alternately driving, at the minimum (Nyquist) sampling rate, orthogonal linear feeds simultaneously by two identical waveforms, +/−90° out of phase), and receiving two orthogonal linear polarizations, coherently. Once calibrated, the single-look complex amplitude data are sufficient to form all Stokes parameters, which fully characterize the radar backscatter.

The invention provides an anisotropic sea surface radar back scattering simulation method and system. The method comprises the steps of: observing a data sample according to a plurality of satellite radars, carrying out fitting calculation on parameters in a to-be-configured anisotropic sea surface radar back scattering model which is established on the basis of a small slope approximation method,so as to obtain a configured anisotropic sea surface radar back scattering model, in the model, expressing asymmetric influences, on radar back scattering coefficients, of along wind and dead wind through a deflection function, and expressing autocorrelation of a sea surface height by adoption of an index-like type function; and obtaining data of a to-be-simulated field, and calculating and outputting a target radar back scattering coefficient corresponding to the data of the to-be-simulated scene according to the configured anisotropic sea surface radar back scattering model. According to the method and system, the characteristics of anisotropic sea surfaces can be truly reflected, and the calculation precision and calculation efficiency are both reasonably considered, so that the methodand system have important application value in the aspects of satellite-borne radar parameter design, sea surface wind field inversion and the like.

The invention relates to a wireless sensor suitable for health monitoring of a concrete structure. The wireless communication comprises a communication antenna, an energy extracting antenna, a variable matching network, a demodulator, a backscattering modulator, a controller, a physical energy extracting module, a memory and a sensor. The wireless sensor has the characteristics that the whole circuit is supplied with electric energy by the energy extracting antenna and the physical energy extracting type, a built-in power source is not needed, the difficulty in failure to replace the battery in the later period is avoided, and the manufacturing cost and later maintenance cost are greatly reduced; the variable matching network can complete the power matching at different input signal frequency according to the digital signal adjusting center frequency obtained by a frequency digital converter, so as to improve the reliability of the wireless sensor in working under the complicated concrete environment; the backscattering modulator is based on the radar backscattering principle, the zero-power consumption modulation is realized, and the circuit structure is simple.

The invention provides a pixel screening and filtering method and system for wind vector retrieval under precipitation situations. The pixel screening method comprises the steps of correcting interference of precipitation on observed signals of a scatterometer to obtained a relatively accurate wind-derived radar backscatter cross section area; according to the obtained wind-derived radar backscatter cross section area, determining every fuzzy solution of the pixels in the wind vector retrieval under the precipitation situations and the total grey level of every fuzzy solution; finding out a target fuzzy solution closest to numerical wind data; judging whether the total grey level of the target fuzzy solution is greater than a preset grey level threshold; if so, marking the corresponding pixel. The filtering method comprises the steps of screening the pixels in the wind vector retrieval under the precipitation situations through the pixel screening method. Due to the fact that the interference of the precipitation on the observed signals of the scatterometer during the screening process, the pixels with relatively large wind vector retrieval errors can be effectively eliminated, and the precision of the wind vector retrieval can be improved.

The invention discloses a wave-absorbing simulated banyan and a method for manufacturing the same. The wave-absorbing simulated banyan and the method are used for solving the technical problem of poor wave-absorbing characteristic of an existing simulated tree. The technical scheme includes that each single twig of the wave-absorbing simulated banyan comprises a plurality of tree leaves (5) and tree branches, each secondary branch (4) comprises two corresponding single twigs, each primary branch (3) comprises a plurality of secondary branches (4), the multiple primary branches (3) and a tree trunk (2) are fixedly connected with one another to form the simulated banyan, a steel tube (1) is fixedly connected to the lower end of the tree trunk (2), metal blended yarns which are of grid structures are woven in polyester base fabrics of the tree leaves (5), and a layer of weak-conductivity radar wave-absorbing coatings is arranged on the surface of each tree leaf (5) by means of blade coating. The wave-absorbing simulated banyan and the method have the advantages that a wave-absorbing characteristic of the simulated banyan can be improved owing to the weak-conductivity radar wave-absorbing coatings on the surfaces of the polyester base fabrics of the tree leaves and the metal blended yarns which are of the grid structures and are arranged in the polyester base fabrics of the tree leaves, and the average radar backscattering coefficient difference of the wave-absorbing simulated banyan is only 0.01dB within the range of 1-18GHz as shown by contrast tests.

The invention pertains to the technical field of marine microwave remote sensing, and specifically relates to a method for calculating electromagnetic scattering of oil spilled sea. The method for calculating the electromagnetic scattering of the oil spilled sea comprises the following steps: step1, calculating a JONSWAP frequency spectrum of clean sea according to marine environment parameters; step2, calculating a frequency spectrum of the oil spilled sea according to an oil spill inhibition function; step3, calculating a directional spectrum of the oil spilled sea according to a dispersion relation of Marangoni waves and the frequency spectrum of the oil spilled sea; step4, calculating a radar backscattering coefficient of the oil spilled sea by adopting a two-scale method. The method solves the directional spectrum of the oil spilled sea through the dispersion relation of the Marangoni waves and the oil spill inhibition function, and calculates the radar backscattering coefficients of the oil spilled sea by adopting the two-scale approximation method. Compared with the prior art, the method has advantages of wide application range, accurate calculation, and less computation.

The invention discloses a multi-load remote sensing image-based rice yield estimation method for cloudy and rainy areas, and belongs to the field of remote sensing image agricultural application. The method includes: using an optical remote sensing satellite and a synthetic aperture radar remote sensing satellite to monitor a certain rice planting area; then, extracting a rice planting area of a working area by utilizing a GIS technology, and storing related information in an attribute table; then distinguishing the rice planting time; then calculating a radar backscattering coefficient Mean RSC corresponding to each field parcel; correcting a rice field area value influenced by the strong reflection point; carrying out manual sampling and yield measurement on the field to obtain the measured acre yield of the rice in the field; establishing a rice yield estimation model; and finally, calculating the estimated yield of the field according to the yield estimation model and the time-phase radar backscattering coefficient. The practical application problem of rice yield estimation in cloudy and rainy areas is solved.

The invention relates to a lunar surface flat region selection method based on fractal dimension and polarization decomposition. The method comprises the following steps: step 1, obtaining complete polarization SAR data; step 2, calculating a fractal dimension D according to the total back scattering power of the radar to obtain a fractal dimension graph; step 3, binarizing the fractal dimension graph, setting pixel values greater than a fractal dimension mean value to be white, setting pixel values smaller than the mean value to be black, and obtaining a binarized fractal dimension graph; 4, all continuous N * N pixel areas which do not contain white pixels are screened out from the fractal dimension graph after binaryzation to serve as candidate areas selected coarsely, and N is the width of the pixel areas; 5, performing polarization decomposition on the SAR echo by using a Yamagguchi four-element decomposition method to obtain the sizes of a single scattering component, a secondary scattering component, a volume scattering component and a spiral scattering component; and step 6, for each candidate region, screening out an n * n pixel region with the maximum single scattering component proportion, i.e., a selected and extracted flat region.

The invention discloses a farmland soil moisture simulation method based on Sentinel data and a deep learning model, and belongs to the technical field of microwave remote sensing, the simulation method comprises the following specific steps: (1) Sentinel data acquisition; (2) data preprocessing; (3) analysis of soil moisture; simulation of soil moisture. According to the method, the Sentinel-1 satellite is used for obtaining synthetic aperture radar data, regression learning is carried out based on the deep learning model, and simulation of farmland soil moisture is realized by researching the relationship between the radar backscattering coefficient and the soil volumetric water content. The influence of factors such as a soil dielectric constant, surface roughness and vegetation coverage in a radar backscattering coefficient is considered, elimination is carried out through an Alpha model, the farmland soil moisture calculation precision is guaranteed, and the method has the advantages of large-area real-time observation, high efficiency, low cost and the like, the farmland soil moisture can be simulated all day long in an all-weather manner, so that the real-time protection aiming at agricultural production is facilitated.

The invention provides a method and a system for inverting ocean vortex dynamic parameters in an SAR (Synthetic Aperture Radar) image, which are used for inverting and extracting vortex dynamic characteristics based on a vortex SAR imaging theoretical model and constructing a quantitative relation between a radar backscattering coefficient of the SAR image and a vortex physical model. Different from previous digital image processing, machine learning and other methods, only the position and radius characteristics of the vortex can be extracted. Vortex dynamic parameters obtained through inversion of the method include the vortex center position, the suction intensity, the viscosity coefficient, the speed circulation, the maximum vortex rotation speed radius, the maximum rotation angular speed, the maximum vortex intensity and other dynamic parameters.

The embodiment of the invention provides a satellite microwave scatterometer radar backscattering coefficient acquisition method and a corresponding device. The method comprises the following steps: acquiring an internal calibration measurement value, a background noise measurement value and an echo measurement value output by a microwave scatterometer in each rotation period; screening the internal calibration measurement value and the background noise measurement value based on a preset quality evaluation standard, and performing moving average processing on the internal calibration measurement value and the background noise measurement value obtained through screening to obtain a target internal calibration measurement value and a target background noise measurement value; and obtaining a corresponding radar backscattering coefficient based on the target internal calibration measurement value and the target background noise measurement value corresponding to each rotation period. According to the scheme, the measured value corresponding to each rotation period is more accurate, so that the calculated radar backscattering coefficient is more accurate. Meanwhile, according to the scheme, the calculation efficiency is improved, and the real-time performance of obtaining the radar backscattering coefficient is improved.

The invention discloses a stony desertification determining method based on a radar backscattering coefficient time series. The method comprises firstly performing multi-temporal radar data selectionon a region with to-be-extracted rocky desertification information; then performing radiometric calibration, terrain radiation correction and speckle noise filtering on the radar data; constructing atime series based on a backscattering coefficient by using the processed radar data; and finally, determining the rocky desertification category of the target region by a DTW algorithm. The method hashigh rock desertification determining precision and solves defects that optical remote sensing is liable to be affected by cloudy and rainy weather and a single-temporal radar may cause the lack of information due to speckle noise.

The invention provides a rainfall inversion method based on a synthetic aperture radar. The rainfall inversion method comprises the following steps: S1, obtaining an original spaceborne SAR image and rainfall data measured by a TRMM satellite, and calculating to obtain a normalized radar back scattering cross section value of the original spaceborne SAR image; S2, using the improved composite surface radar backscattering model based on the Bragg scattering theory to simulate and obtain a simulated normalized radar backscattering cross section value; S3, determining a relationship between a difference value between the normalized radar backscattering cross section value and the simulated normalized radar backscattering cross section value and the rainfall capacity; and S4, constructing an inversion algorithm. The rainfall inversion method based on the synthetic aperture radar is high in precision and small in calculation amount.