168 results about "Interferometric phase" patented technology

The invention discloses an intelligent data processing method and system for geological disaster early warning, and relates to geological disaster early warning, and the method comprises the steps: collecting multi-source heterogeneous data; extracting topographic features of the geological disaster area according to the optical satellite image data and the laser radar data; performing differential interference processing on the synthetic aperture radar data to obtain differential interference phase data of the geological disaster area; performing phase unwrapping by using an improved minimum cost flow algorithm to obtain a continuous absolute phase value # imgabs0 #; performing nonlinear estimation on the estimation result of the surface deformation quantity to obtain state parameter estimation of the geological disaster area; and performing early warning detection by using a support vector machine (SVM). In order to solve the problem of low geological disaster prediction precision caused by difficult phase unwrapping in the prior art, the unwrapping problem is converted into a space-time network flow graph, space-time continuity constraints are introduced, the incidence relation between data in different periods is considered, a multi-scale strategy is adopted for solving and the like, and the prediction precision is improved.

The invention discloses a full-field-domain structure high-precision deformation and vibration measurement system based on a microwave interference radar, and the system comprises an observation configuration module which is used for obtaining radar observation parameters and completing the signal transmission and reception; the signal processing module is used for preprocessing the echo signal and constructing an interference phase matrix; the phase unwrapping module is used for generating a continuous phase sequence and calculating the displacement of a reflection point; the frequency spectrum extraction module is used for extracting the frequency component and the vibration amplitude of each reflection point; the response clustering module is used for extracting reflection point clusters with similar frequency responses and constructing a vibration distribution diagram; the modal identification module is used for generating a vibration modal feature vector and marking a difference region; and the track generation module is used for generating a dynamic deformation track diagram of the full field domain structure. According to the invention, high-precision deformation and vibration mode synchronous measurement of a complex structure under full-field-domain and non-contact conditions is realized, and the precision, efficiency and intelligent level of structure monitoring are effectively improved.

According to the single-frame high-quality shearing speckle interference phase extraction method and device, the quality of the obtained phase is comparable to that of a traditional multi-frame phase solution algorithm, and single-frame high-quality phase extraction of shearing speckle interference is completed. The method comprises the following steps: (1) making a data set; (2) constructing a neural network; (3) neural network training; (4) detecting the detected piece: when the detected piece is static, carrying out N-step phase shift method shooting to obtain N frames of speckle interferograms when the detected piece is static; applying an external force to the measured piece, and recording light intensity information by using a camera to obtain a frame of interferogram when the measured piece is deformed; (5) single-frame phase extraction: phase extraction is carried out according to an N + 1 time phase shift method, and on the basis of N frames of phase shift interferograms when the measured piece is static, phase extraction is carried out by using one frame of interferograms after the measured piece is deformed, so that low-quality phase distribution is obtained; and (6) phase repairing.

The invention discloses a method and system for constructing an interferometric phase unwrapping model based on discrete wavelet transform, and relates to the field of image phase unwrapping, and the method comprises the specific steps: constructing an InSAR synthetic data set based on an SRTM DEM, a two-dimensional Gaussian curved surface and an InSAR measurement error source; an interferometric phase unwrapping model based on discrete wavelet transform is constructed, the interferometric phase unwrapping model comprises an encoder network, a bottleneck layer, a decoder network and an output layer which are connected in sequence, and the encoder network comprises a plurality of cross-stacked dual-channel data down-sampling modules and pyramid pooling modules; and training the interferometric phase unwrapping model based on the InSAR synthetic data set, and optimizing model parameters by minimizing a loss function to obtain a final interferometric phase unwrapping model. According to the method, the interferometric phase unwrapping of the low-coherence region is realized under the condition of lightweight parameters, the phase continuity hypothesis is not depended on, and the interferometric measurement precision of the synthetic aperture radar is improved.

The invention discloses a construction period landslide disaster advanced prediction and rapid networking monitoring method, and the method comprises the steps: collecting synthetic aperture radar data, digital elevation model data and satellite precision orbit data of a monitoring region, carrying out the data preprocessing, and obtaining a single-view complex data image set; constructing an interference image pair connection graph, performing interference processing, and generating a differential interference graph and a coherence coefficient graph; performing interferometric phase unwrapping processing on the differential interferogram and the coherence coefficient graph according to a minimum cost flow algorithm to obtain earth surface deformation information; ground control points are selected, and the surface accumulated deformation quantity and the surface deformation rate are obtained; interpreting and delineating a potential deformation area, establishing an interpretation mark, selecting a typical deformation area, and extracting a time sequence deformation data set; and analyzing the time sequence deformation data set according to the neural network model to obtain a deformation prediction result and a disaster risk assessment result. According to the invention, the monitoring accuracy and prediction capability of landslide disasters can be improved.

The invention discloses a phase feedback all-optical non-magnetic temperature control device and method based on an FPGA, the device comprises an interferometer module, an FPGA system module and a temperature control module, and through the coordination work of the interferometer module, the FPGA system module and the temperature control module, magnetic noise can be reduced and high-precision stable temperature control can be completed on the basis that a traditional temperature sensor is not used. According to the method, a corresponding state-space equation is constructed by using a corresponding relation between an interferometric phase and temperature in an interferometer, a segmented Kalman filtering algorithm is executed through an FPGA, temperature information hidden in an interferometer signal is extracted, the temperature information is converted into a voltage signal, and a stable temperature control effect is achieved through interaction with a temperature control chip.

The invention relates to the technical field of landslide geological recognition, in particular to a reservoir area landslide geological disaster recognition method and system, and the method comprises the steps: collecting SAR images and DEM data of a reservoir area at each time point; forming the SAR images of the adjacent time points into master and slave SAR images, obtaining an interferogram of the master and slave SAR images, and dividing the interferogram of the master and slave SAR images into an incoherent water area, a terrain transition area and a high-coherence stable area; determining a terrain phase gradient of each pixel point in the interferogram, obtaining a terrain gradient amplitude of each pixel point, correcting an objective function of a least square phase unwrapping algorithm, and obtaining an interferometric phase after phase unwrapping; elevation information corresponding to the interferogram is determined, the average deformation rate of each pixel point is calculated, and the potential landslide risk of the reservoir area corresponding to each pixel point is identified. Therefore, the accuracy of reservoir area landslide risk identification is improved.

The invention relates to the technical field, and discloses a ground-based synthetic aperture radar atmospheric phase correction method and system, and the method comprises the steps: sequentially carrying out the permanent scattering point selection and phase unwrapping of collected time sequence single-view complex image data, and obtaining the first time sequence interference phase data of a permanent scattering point in the time sequence single-view complex image data; performing time sequence clustering analysis on the first time sequence interferometric phase data to obtain a plurality of permanent scattering point homogeneous regions, and performing atmospheric phase local correction on the first time sequence interferometric phase data of the permanent scattering points in each permanent scattering point homogeneous region by adopting a pre-constructed atmospheric phase correction linear model to obtain a plurality of permanent scattering point homogeneous regions; and performing time sequence low-pass filtering processing on the obtained second time sequence interference phase data corresponding to the permanent scattering points in each permanent scattering point homogeneous region to obtain corrected deformation image data corresponding to each permanent scattering point homogeneous region. According to the method, the precision of atmospheric phase correction is effectively improved.

The invention discloses a phase unwrapping method for an SAR (Synthetic Aperture Radar) interferometric phase diagram. The phase unwrapping method comprises the following steps: acquiring prior information of the interferometric phase diagram; based on prior information, unwrapping the interferometric phase diagram to obtain an absolute phase; elevation information is extracted according to the absolute phase; according to the elevation information, the prior information is reversely optimized. The acquisition of the prior information is based on image segmentation of the interferometric phase diagram. According to the phase unwrapping method for the SAR interferometric phase diagram and the related product, all segmented areas are executed one by one, all reconstruction results are further geocoded and integrated, fine three-dimensional reconstruction of a building can be achieved, target extraction is conducted by fusing structural features in the two-dimensional imaging direction, and the construction efficiency is improved. And the accuracy of building identification is obviously improved. The structure auxiliary information of image segmentation effectively reduces the risk of phase discontinuity in the phase unwrapping process, significantly reduces the unwrapping error, and achieves the high-precision and low-cost three-dimensional reconstruction of a building under the condition of a double-track long baseline.

The invention discloses a glucose metabolism dynamic monitoring method and system based on multispectral imaging, and relates to the technical field of glucose metabolism dynamic monitoring, and the method comprises the following steps: obtaining polarization state distribution data and interferometric phase data of a target tissue, and constructing a Jones matrix; performing inverse polarization transformation compensation on the Jones matrix to obtain a polarization interference signal and extract a phase distribution diagram; dividing the phase distribution diagram into a plurality of sub-regions, extracting a phase gradient feature of each sub-region, obtaining a plurality of phase resolving threshold candidate sets, and performing ambiguity suppression to obtain a plurality of first phase mapping features; constructing a three-dimensional glucose metabolism activity model by adopting a feature fusion algorithm, and carrying out glucose metabolism abnormality identification; and data analysis is performed on an identification result to obtain an optimal phase solution threshold value, and the optimal phase solution threshold value is applied to the glucose metabolism monitoring process, so that the problem that the accuracy of noninvasive, dynamic and spatial resolution and high-precision monitoring of the tissue glucose metabolism process is reduced due to the fact that the precision of phase solution ambiguity of a traditional method is unstable is solved.

The invention relates to the technical field of radar remote sensing, and discloses a high-precision deformation monitoring and target imaging method based on MIMO-SAR. The method comprises the following steps: receiving an original MIMO-SAR echo data stream and a Beidou navigation system positioning data stream acquired by an image sensor; performing standardized preprocessing on the original echo data to generate standard radar data blocks; aligning radar data blocks and Beidou positioning data time and space, and establishing a mapping relation between data and a spatial position; performing sub-aperture division on the aligned data blocks to generate a multi-sub-aperture data set; performing beam forming processing on each sub-aperture data set to obtain a multi-view complex image; extracting an interference phase of a plurality of images and carrying out geometric correction by using Beidou data; unwrapping the corrected phase to obtain an absolute phase field; inverting a millimeter-level deformation sequence based on the absolute phase field; dynamically updating imaging focusing parameters according to the deformation sequence time evolution characteristics; and performing high-resolution imaging on subsequent data blocks by using the updated parameters, and outputting a deformation monitoring result and a target image.

The invention provides a forest vertical structure information inversion method and system based on radar interferometry, and the method comprises the steps: carrying out the small-view processing of high-resolution SAR interferometry data with a space baseline, calculating the small-view InSAR phase height, extracting the statistical distribution of the small-view interferometry phase height in a set space window, and carrying out the calculation of the small-view interferometry phase height. Generating a small-looks interferometric phase height histogram; establishing an under-forest ground elevation regression estimation model based on the statistical characteristics of the small-looks interferometric phase height histogram, and determining model parameters to invert the terrain; and two canopy top indexes are extracted, two index results are fused by setting a threshold value, and final forest vertical structure information is generated. The method has the advantages that more canopy internal and under-forest information can be captured only by using single-baseline and single-polarization radar interference data, and the sensitivity to a forest vertical structure is improved; and the forest vertical section, the tree height and the terrain can be synchronously inverted.

The invention discloses an iron tower PS pixel point simulation and differential interference deformation monitoring method and system based on three-dimensional point cloud data, and the method comprises the steps: obtaining the point cloud data of an iron tower body structure under a radar coordinate system through a radar distance Doppler positioning method through the three-dimensional point cloud data of the iron tower body structure; identifying pixels containing the iron tower point cloud data in the SAR image as iron tower PS pixel points; constructing a radar scattering weight model based on elevation information of the iron tower point cloud data, and obtaining an iron tower PS pixel point scattering intensity value through weighted summation in combination with a weight adjustment parameter; constructing a complex value of the point cloud data of the iron tower according to the interferogram parameters and a radar scattering weight model, and obtaining a simulation interference elevation phase of the PS pixel point of the iron tower by using complex field summation; differential interferometric phases of iron tower PS pixel points in the interferogram are obtained through difference; and performing statistical analysis on the differential phase map of the iron tower PS pixel point set region in the time sequence interferogram to obtain a deformation result.

The invention relates to the technical field of geodetic surveying instruments and geological disaster monitoring, and discloses a geological environment displacement surveying system based on a GNSS multipath effect, and the system comprises a signal collection unit which is used for receiving a satellite signal and extracting a signal-to-noise ratio sequence; the interference feature separation unit is used for stripping a direct signal power component and generating a residual oscillation sequence; the geometric inversion calculation unit is used for generating a reference interferometric phase template in a height search domain, and generating a height-correlation map to lock the current vertical height by calculating and superposing correlation coefficients between the residual oscillation sequence and the reference interferometric phase template; according to the invention, through a spatial domain geometric matching mechanism, high-precision distance measurement is realized in a complex environment in which a satellite visual segmental arc is broken, dependence of a traditional spectral analysis method on observation duration is broken through, and signal-to-noise ratio data endogenesis is utilized to decouple observation station attitudes and environmental medium attributes. And the stability and the multi-dimensional perception capability are improved.

The invention relates to a speckle interferometric phase diagram filtering method based on a conditional diffusion model, and belongs to the technical field of optical measurement. The method comprises the following steps: S1, obtaining training data: generating or collecting multiple groups of paired speckle interferometric phase diagrams including noisy speckle interferometric phase diagrams and corresponding denoising reference phase diagrams; s2, constructing a conditional diffusion model; S3, training the conditional diffusion model: training the diffusion model in a supervision mode; and S4, taking the to-be-processed phase diagram as a conditional image, and generating a denoised phase diagram through a back diffusion process. According to the invention, the noise processing accuracy of the phase diagram in laser speckle interference measurement can be improved.

The invention discloses an adaptive multi-loop network InSAR phase unwrapping method and device, and relates to the technical field of interferometric synthetic aperture radar measurement. The method comprises the following steps: acquiring an interferometric phase diagram and a topographic map of a complex topographic region; calculating coherence, a topographic gradient map, a phase gradient standard deviation and residual density based on the interferometric phase map and the topographic map; based on the coherence, the terrain gradient map, the phase gradient standard deviation and the residual density, dynamically selecting the size of a ring through a decision function, and constructing a multi-ring network; determining the connectivity of the multi-ring network according to a bridging strategy and a connectivity detection method, and outputting a global connected network; on the basis of the global connected network, layered residual optimization is carried out by adopting a local absorption and global planning double-layer strategy, and an optimized residual is output; and based on the optimized residual error, unwrapping all rings in the global connected network through an in-ring local unwrapping and global optimization strategy, and outputting an unwrapping result. According to the invention, the problem of network connectivity in a complex area can be solved.

The application provides a complex terrain area elevation inversion method based on small unmanned aerial vehicle borne interferometric SAR. N-track small unmanned aerial vehicle flight tracks are set, the X-axis and Y-axis coordinates of the starting point and ending point of each track small unmanned aerial vehicle are unchanged, and the value of the Z-axis is gradually increased along the vertical direction. N-track echo data are obtained by the small unmanned aerial vehicle borne SAR according to the set tracks, and BP algorithm is used for imaging processing to obtain N SAR images. The offset of the SAR images of adjacent short baseline small unmanned aerial vehicles is obtained. The offset of the SAR images of long baseline small unmanned aerial vehicles is calculated based on the offset of the SAR images of small unmanned aerial vehicles, and the SAR images of long baseline are image matched. The SAR images after image matching are processed to obtain corresponding interference phase images, and the interference phase images are filtered by using Goldstein algorithm. Multi-baseline phase unwrapping is performed based on the interference phase of the interference phase images. The complex terrain area elevation inversion method of SAR is realized.

The invention discloses a high-precision InSAR (Interferometric Synthetic Aperture Radar) deformation monitoring method combining polarization information and deep learning, and particularly relates to the crossing field of radar remote sensing and deep learning technologies. The method comprises the following steps: acquiring multi-temporal complete polarization or dual polarization SAR original data, generating single-view complex data through radiometric calibration, registration and multi-view processing, and extracting a polarization coherence matrix; constructing a sample set containing polarization features and interferometric phase labels; designing a double-branch deep learning network model composed of a polarization feature extraction branch and a phase optimization branch, and processing a polarization matrix and a phase sequence by adopting a three-dimensional convolution structure and a long and short term memory-convolution hybrid structure; the deep polarization features and the optimized phase information are fused through the trained model, and the deformation quantity is output through regression calculation; and finally, generating a deformation graph under a geodetic coordinate system through geocoding. The polarization scattering characteristic is effectively utilized, and the monitoring precision and reliability in a complex scene are improved.

The embodiment of the application provides an interferometric phase denoising method and device, relates to data processing technology, and the interferometric phase denoising method comprises the following steps: performing multi-scale frequency decomposition on an original interferometric phase map based on a preset frequency domain filtering window to obtain hierarchical phase signals containing different frequency components; calculating residual components of adjacent levels according to the difference between principal component signals of adjacent levels to obtain residual domain signals corresponding to each level respectively; performing denoising processing on the residual domain signals by using a pre-trained denoising model to obtain denoised residual domain signals corresponding to each level respectively; and performing phase reconstruction on the denoised residual domain signals corresponding to each level respectively to obtain a target interferometric phase map.The application can effectively maintain the authenticity and integrity of the phase structure while suppressing noise, effectively reduce the generation of artifacts and improve the convergence stability, and ensure the reliability of phase unwrapping and subsequent deformation inversion.

A method for decoupling azimuth and elevation angles of a two-dimensional cross array. The elevation angle of the target is solved by using the interference phase difference of the data received by the cross array elements. The data is compensated according to the phase generated by the elevation angle, and the azimuth angle of the target is calculated by using a one-dimensional angle measurement algorithm for the compensated data. The present invention has a small amount of calculation and increases the unambiguous range of angle measurement, provides a new idea for measuring angles by millimeter-wave vehicle-mounted radars, and is applicable to improving the real-time performance of angle measurement and increasing the field of view of millimeter-wave vehicle-mounted radars.

The invention discloses a small-scale deformation InSAR time sequence inversion method and system based on multiple stable points, and the method comprises the following steps: S1, carrying out the small baseline interference processing of multi-temporal synthetic aperture radar data, and screening high-coherence pixel points, S2, recognizing a stable point candidate set with dense spatial distribution; s3, constructing an initial atmospheric delay phase model covering a full interferogram range; s4, obtaining an interferometric phase after atmospheric correction; and S5, inverting the deformation rate and the deformation time sequence parameters of the InSAR again. According to the method, dense stable points are screened based on a deformation rate threshold value, and a space atmosphere model is constructed, so that the problem that atmosphere delay and nonlinear deformation are difficult to separate in InSAR time sequence analysis is effectively solved, and high-signal-to-noise-ratio and high-precision time sequence monitoring of small-scale weak deformation of the earth surface is realized.

The application discloses a high-order overtone DOR measurement method, system, device and medium, relates to the technical field of information acquisition and processing, and comprises the following steps: performing local correlation processing on a carrier channel signal acquired through a satellite antenna to obtain interference phases in multiple first integral periods, and determining a first phase polynomial of a carrier model based on all the interference phases; determining a high-order overtone model based on the phase polynomial of the carrier model; correcting multiple high-order overtone signals acquired through the satellite antenna based on the high-order overtone model; determining a residual phase corresponding to each high-order overtone signal through the multiple corrected high-order overtone signals; and determining a DOR time delay observation corresponding to each high-order overtone signal through a multi-side tone DOR time delay calculation method based on the residual phase corresponding to each high-order overtone signal. The application can realize acquisition of a DOR measurement time delay observation, and has a wide application prospect in the field of deep space interferometric measurement.

The application discloses an InSAR atmospheric delay phase correction method along a slant range direction, comprising the following steps: S1, acquiring two SAR image subsets covering a research area and acquiring two clean water vapor data; S2, performing differential interference processing on the two SAR image subsets covering the research area to acquire differential interference phases; S3, accurately calculating atmospheric delay phases by using an atmospheric delay phase correction model; and S4, accurately obtaining real deformation of the ground along a radar line-of-sight direction. The application gives the latest weight value of the zenith path delay difference of each ground pixel on the slant range direction of the ground by correcting the sampling mode of the water vapor product along the ground distance direction, finally proposes an accurate and efficient slant range phase total delay calculation method along the ground distance, further optimizes and improves the repeat orbit synthetic aperture radar differential interferometry method, so that the measurement result is more scientific and reasonable, and therefore the application has a wide application prospect in the field of repeat orbit InSAR atmospheric phase correction.

The invention discloses a vibration drift removal and compensation method for atom interference measurement, which sequentially comprises the following steps of: carrying out atom interference continuous measurement, acquiring a voltage signal by an accelerometer, enabling the voltage signal to pass through a band-pass filter circuit, acquiring the voltage signal by a main control system, converting the voltage signal into an acceleration signal, and converting the acceleration signal into a vibration phase. The acceleration signal average value is converted into a vibration phase, vibration phase linear fitting, interference measurement period vibration phase drift removal and interference fringe fitting are carried out to obtain an interference phase, and the interference phase calculates a measured physical quantity; according to the method, data processing such as filtering, smoothing, linear fitting and deduction is carried out on signals collected by the accelerometer, suppression of time drift and temperature drift existing in relative acceleration measurement of the accelerometer is achieved, and measurement noise introduced by ground vibration is greatly reduced.

The present invention is applicable to the field of surveying and mapping science and technology, and relates to a method for correcting the atmospheric interference phase of a ground-based circular arc interferometric synthetic aperture radar, including: constructing a differential interferometric phase model of the ground-based circular arc interferometric synthetic aperture radar; eliminating phase noise; screening permanent scatterers; dividing the obtained interferometric phase in the azimuth direction into subspaces, then dividing the subspace grids according to a set window size, and performing phase weighted average processing on the permanent scatterers in the grids according to the correlation coefficient and amplitude deviation, and taking it as the atmospheric interference phase sample point of the grid center point; screening the obtained atmospheric interference phase sample points to obtain available sample points; using the available sample points to estimate the parameters of the atmospheric interference phase error model, and further obtaining the atmospheric interference phase error of the detection area; and obtaining the deformation phase. The method of the present invention is simple and efficient, does not require the introduction of external auxiliary data, but only relies on the interferometric phase to correct the atmospheric interference phase, and has a high correction accuracy.

This invention discloses a self-supervised learning-based atmospheric phase compensation method for InSAR images, belonging to the field of differential interferometry (DI) technology for synthetic aperture radar. This method does not rely on external ground truth data. By establishing constraints for solving the atmospheric phase and integrating them into the network training process, it achieves self-supervised learning for atmospheric phase compensation. The method includes: constructing an atmospheric phase estimation network, which takes a time-series unwrapped phase image and related auxiliary data as input, and outputs the atmospheric phase estimation result or intermediate variables used to calculate the atmospheric phase; constructing differentiated constraint loss terms for reference points with different phase change modes based on the phase component composition of the interferometric phase; embedding physical prior constraints in both network structure and loss terms; combining various loss terms into a total loss function, and completing self-supervised training through iterative optimization to achieve atmospheric phase estimation and compensation.

The present invention discloses an interferometric circular SAR three-dimensional imaging method and device for complex structure buildings. The method includes: obtaining a set of sub-aperture images corresponding to antenna phase centers, where the set of sub-aperture images is obtained by imaging the sub-aperture data of each antenna phase center on a reference height plane; performing interferometric processing on the set of sub-aperture images to obtain a wrapped interferometric phase; determining multiple phase ambiguity numbers according to the wrapped interferometric phase, the scene height range, and the pre-established relationship between the height difference and the wrapped interferometric phase; calculating multiple three-dimensional positions under each sub-aperture according to the multiple phase ambiguity numbers by using the range-Doppler equation; selecting from the multiple three-dimensional positions under each sub-aperture by using the correlation coefficient algorithm; and performing interferometric circular SAR three-dimensional imaging of the complex structure building according to the selection result. The present invention effectively reduces the data storage amount and the calculation amount and improves the imaging efficiency.

The present invention discloses a SAR image overlap detection method, apparatus, device, and storage medium. The method includes: obtaining SAR time-series image data, external DEM data, and external surface classification coverage data of a current detection area; obtaining a regional amplitude map of the current detection area based on the SAR time-series image data, and normalizing the regional amplitude map; obtaining a corresponding interferometric phase map based on the SAR time-series image data, and calculating a coherence coefficient; normalizing the external DEM data, and then band-splicing the normalized regional amplitude map, interferometric phase map, coherence coefficient, normalized external DEM data, and external surface classification coverage data to generate corresponding data blocks, and inputting the data blocks into a preset overlap recognition model to obtain an overlap recognition result for the current detection area. The present invention can improve the accuracy of SAR overlap recognition.

The invention discloses an interferometric synthetic aperture radar image registration method based on phase diagram quality evaluation, and the method comprises the following steps: S1, obtaining an interferometric synthetic aperture radar interferometric image pair, and selecting a plurality of registration control points which are uniformly distributed in the interferometric image pair; wherein the image pair comprises a main image and an auxiliary image; s2, respectively setting a matching window and a search window by taking each registration control point as a center; s3, performing quality evaluation on the interferometric phase diagram between the main image and the auxiliary image in the matching window to obtain position offsets, and performing quality control on each position offset and a corresponding registration control point; s4, fitting a function relationship between the position offset of each registration control point subjected to quality control and the image coordinate of the registration control point, and re-sampling the auxiliary image to realize accurate registration of the whole interference image pair; according to the method, the quality of the interferometric phase diagram is continuously evaluated in the registration process, and high-precision registration of the main image and the auxiliary image in the interferometric phase diagram is achieved.

The invention discloses an MZI (Mach Zehnder Interferometer) electro-optical modulator with a high extinction ratio and integrated with double photoelectric detectors, which is applied to the fields of photoelectron technology, optical communication and microwave photonics, and aims to overcome the structural defects of the existing modulator and the problem that the output optical power cannot reach the maximum value due to inevitable errors existing in the manufacturing process. The problem that the extinction ratio of the modulator is not large enough due to the fact that the minimum value close to zero cannot be achieved is solved. The modulator comprises a 1 * 2 coupler 1, a 2 * 2 coupler 2, a 2 * 2 coupler 3, a pre-bias area, an electro-optical modulation area and a 2 * 1 coupler 4 which are sequentially connected through waveguides, and further comprises thermal tuning electrodes 11, 12, 21, 22, 31 and 32, a cladding optical signal collection waveguide 1, a waveguide 2, a metal absorption layer and an end face patch type detector. Different voltages are applied to the thermal tuning electrodes 11, 12, 21 and 22, so that the distribution ratio of any optical power of the power divider is realized; light leaked from the 2 * 1 coupler 4 when light in two arms of the MZI electro-optical modulator is subjected to destructive interference is collected through coupling of the waveguide 1 and the waveguide 2, the light is transmitted to the photoelectric detectors PD1 and PD2, and electric signals output from the photoelectric detectors PD1 and PD2 are used for bias point feedback control; by combining the two aspects, the leakage light is fully used for bias point feedback control while the high extinction ratio of the MZI electro-optical modulator is finally realized.