277 results about "Imaging algorithm" patented technology

The invention discloses an array type optical fiber ultrasonic imaging system based on multi-path delay parallel detection, and belongs to the technical field of ultrasonic detection and imaging. The main working process of the system is as follows: continuous laser output by a laser is modulated into pulse laser to be transmitted to an optical fiber ultrasonic detector array, and ultrasonic waves emitted by an ultrasonic wave generating device act on each detection array element to cause the property change of a detection optical signal; through multi-path time delay with the optical fiber as the medium, the detection optical signal forms different transmission time in each channel, is distinguished in a time division mode and is combined into a single path to be output. After photoelectric conversion, electric signals containing multi-channel detection information are collected in parallel, the signals are analyzed at a terminal processor by means of an imaging algorithm with an array parallel architecture, information of a to-be-detected target is obtained, and image reconstruction is completed. The array type optical fiber ultrasonic imaging system has the advantages of being accurate and rapid in scanning detection, simple and compact in system structure and efficient and high-quality in image reconstruction, and large-scale and low-cost array type optical fiber ultrasonic imaging is achieved.

The invention relates to a GIS (Geographic Information System) basin-type insulator defect detection method, electronic equipment and a storage medium, belongs to the technical field of intelligent image identification and processing of power equipment, and solves the problem of how to improve the accuracy of GIS basin-type insulator defect detection. The method effectively improves the resolution and information integrity of defect images, constructs a MobileNetV2 and YOLOv11n lightweight network structure for the technical bottlenecks of large FMC data volume and complex imaging calculation, achieves the intelligent closed-loop process from defect identification, positioning and classification to segmentation evaluation, achieves the automatic identification and geometric quantity extraction of defect areas, and improves the accuracy of the detection result. A data support is provided for subsequent early warning judgment and decision making; according to the method, the ultrasonic detection identification precision and the imaging quality are effectively improved.

The invention provides a high-frequency electromagnetic excitation cable detection image reconstruction method and system, and belongs to the technical field of underground facility multi-field coupling detection and imaging, and the method comprises the steps: applying high-frequency electromagnetic excitation to an underground medium; receiving an electromagnetic signal transmitted through an underground medium, synchronously collecting a sound signal generated by electromagnetic excitation, and preprocessing the electromagnetic signal and the sound signal; performing structure imaging on the electromagnetic signal by adopting a frequency wave number migration imaging algorithm to obtain medium structure distribution; performing electrical parameter imaging on the electromagnetic signal by adopting a Born approximate inverse scattering imaging algorithm to obtain medium electromagnetic characteristic parameter distribution; sound source distribution reconstruction is carried out on the sound signals through a time reversal algorithm, and medium sound source response characteristic distribution is obtained; and inputting imaging results of the three algorithms into a pre-constructed deep reinforcement learning model for dynamic fusion to generate an underground medium comprehensive parameter reconstruction image.

The invention discloses an image stabilization method and system based on inertial measurement data, and the method comprises the steps: obtaining video frame motion optical flow data in real time through a video collection device, obtaining video optical flow motion information through image algorithm processing, and recording and transmitting motion inertia data of a camera through an IMU (Inertial Measurement Unit); the two types of data are preprocessed, and then time axis alignment is completed; accurate video data motion information is obtained through bidirectional correction; kalman filtering is introduced for forward compensation, and a motion model is established to solve a rotation translation matrix; dividing the image into local pixel spaces, calculating a transformation matrix of each region, and obtaining a radiation transformation matrix by adopting neighborhood weighting; and finally, triangular region filling is realized through an OpenGL graphic rendering library, and a stable image is output. According to the method, IMU data and visual information are creatively fused, the real-time performance and accuracy of video image stabilization are remarkably improved through multi-level motion compensation and local optimization, and the method is particularly suitable for meeting the requirement for high-quality image stabilization in a motion scene.

The invention relates to the technical field of magnetic material injection molding, and discloses an injection molding magnetic powder orientation optimization method and system based on rheology-magnetic field coupling. The method comprises the following steps: deploying a distributed sensing network at key positions of a mold runner and a mold cavity, and synchronously capturing dynamic viscosity change gradient and magnetic field intensity space distribution of a melt in real time in a filling process. The captured data are input into a multi-physics field coupling simulation engine based on micromechanics, an instantaneous orientation vector field of the magnetic powder in the cavity is obtained through calculation, then an orientation order degree topological graph is constructed through tensor analysis and an image algorithm, and a weak orientation area and the boundary of the weak orientation area are accurately recognized. And finally generating a composite regulation and control instruction of the magnetic field and the injection parameters according to an identification result. According to the method, online diagnosis and active compensation regulation and control of the orientation state of the magnetic powder can be realized, and the orientation uniformity and consistency of the injection molding magnet are improved.

The invention discloses a cable trench fireproof cover plate performance detection device and method based on multi-band electromagnetic waves. The device comprises a microwave detection module, a terahertz imaging module, a high-precision two-dimensional mechanical scanning platform, a synchronous control and data fusion unit and a comprehensive data analysis platform. The microwave module is used for transmitting and receiving 1-10GHz electromagnetic waves to realize deep structure detection; the terahertz module works at a frequency band of 0.1-3 THz and is used for acquiring near-surface time-domain spectral information. And the scanning platform drives the modules to perform two-dimensional rasterization scanning on the surface of the cover plate. And the synchronous control and data fusion unit coordinates the time sequence action of each module to ensure the time-space consistency of data acquisition. And the comprehensive data analysis platform performs fusion processing on the multi-source data through an inversion and imaging algorithm to generate a comprehensive evaluation report covering internal macroscopic defects, near-surface microdefects and coating thickness. According to the invention, through collaborative integration of microwave and terahertz technologies, multi-scale and integrated nondestructive testing and performance evaluation of the fireproof cover plate from a deep layer to a surface layer are realized.

The invention discloses a self-adaptive underwater single-pixel imaging technology based on Fourier modulation, belongs to the technical field of computational optical imaging, is used for ocean detection and improvement of ocean surveillance and defense efficiency, and adopts a self-designed LED array to replace an expensive DMD and a four-quadrant detector composed of common photodiodes to replace an expensive barrel detector. And high-speed illumination and parallel acceptance are realized while the cost is greatly reduced. The technical route comprises a high-speed underwater single-pixel imaging device, a high-speed Fourier single-pixel imaging algorithm and an adaptive sampling strategy based on Fourier single-pixel imaging. The high-speed single-pixel imaging device comprises a self-designed LED array light modulation module, a converging lens module and a receiving module. The high-speed Fourier single-pixel imaging algorithm comprises a binarization algorithm based on error diffusion and an algorithm based on adaptive compressed sensing. According to the innovative self-adaptive sampling strategy based on Fourier single-pixel imaging, a specific sampling path is generated by fusing circular sampling and random sampling according to the characteristics of an image in a Fourier spectrum, so that Fourier coefficients which have great influence on image quality are acquired as much as possible under water with low sampling rate and high turbidity, and the image quality is improved. Therefore, the high-efficiency imaging of the underwater target object is realized, and the imaging speed and quality are both considered.

The invention discloses a satellite-borne SAR (Synthetic Aperture Radar) real-time imaging method based on FPGA (Field Programmable Gate Array) high-speed transposition, which comprises the following steps of: in FPGA data writing operation, carrying out row splitting on SAR echo data in a matrix form to obtain a plurality of small matrix blocks with consistent row and column sizes, and forming a recombination matrix; writing the small matrix blocks into a memory in sequence; performing skip reading operation on the recombination matrix, and repeating the operation until the reading operation of the SAR echo data is completed; imaging is carried out based on the CS imaging algorithm, real-time output is carried out, according to the method, the transposition operation read-write efficiency of a memory is high, and the imaging real-time performance is guaranteed.

The invention provides an unmanned aerial vehicle dynamic path planning method and system for a strong electromagnetic interference environment, and relates to the field of unmanned aerial vehicle navigation and interference resistance. The method mainly solves the problem of robust positioning of an optical sensing system in a strong electromagnetic environment. The core of the method lies in a spectrum anti-noise technology of a visual SLAM module, and spectrum separation of visible light and near-infrared band electromagnetic noise is realized through electromagnetic shielding packaging and an adaptive imaging algorithm of a multispectral camera. According to the method, a time-frequency double-domain filtering algorithm is adopted, the phenomena of light intensity abrupt change and frequency spectrum aliasing generated by electromagnetic pulses are eliminated in the feature extraction stage, and the electromagnetic interference mismatching rate of ORB feature points is reduced to 2% or below. The optimized feature point cloud keeps electromagnetic immune characteristics in the dynamic updating process, centimeter-level positioning precision can be achieved in the field intensity environment of 30 dBm or above, and meanwhile real-time detection of dynamic obstacles is achieved through an optical flow acceleration constraint mechanism.

The invention belongs to the technical field of image processing, and discloses a three-dimensional radar sub-aperture imaging deformation monitoring device and method, and the device comprises a radar which is used for collecting echo signals passing through a preset position, processing the echo signals according to frequency mixing and analog-to-digital conversion, obtaining a three-dimensional echo matrix, and outputting the three-dimensional echo matrix; the three-dimensional echo matrix and a sampling ending signal are sent to a motion compensation module; the motion compensation module is used for resampling the azimuth direction of the three-dimensional echo matrix by adopting an interpolation algorithm; the distance matching filtering module is used for performing pulse compression on the distance direction of the three-dimensional echo matrix; the migration correction module is used for carrying out migration correction on the distance direction of the three-dimensional echo matrix after pulse compression; the sub-aperture imaging module is used for calculating a three-dimensional echo matrix after migration correction according to a sub-aperture imaging algorithm; and the deformation monitoring module is used for performing interference difference processing on the three-dimensional complex image to obtain deformation data. The imaging quality and the deformation monitoring precision can be improved.

The invention discloses a squint synthetic aperture sonar imaging method based on a dynamic slant-range space-variant model, and relates to the technical field of synthetic aperture sonar imaging, and the method comprises the steps: constructing a dynamic slant-range model; inputting the converted data into the dynamic oblique variation model to obtain a residual space-variant distance bending amount, and compensating the space-variant distance bending amount by using a first filter; according to the dynamic slope distance model, expanding the azimuth time offset into an azimuth frequency modulation factor; based on the azimuth frequency modulation factor and the azimuth time offset, designing a second filter by using an improved extended nonlinear frequency modulation scaling algorithm, and filtering the corrected data by using the second filter; and carrying out Fourier transform on the filtered data, compressing the transformed data by using a third filter, and then carrying out inverse Fourier transform to obtain a focused synthetic aperture sonar image. According to the invention, the imaging performance and stability of the imaging algorithm in a low signal-to-noise ratio and strong multipath interference environment can be improved.

The invention discloses a method and a device for analyzing and correcting influence of phase errors between sub-bands of step-frequency ultra-wideband SAR (Synthetic Aperture Radar) data, and belongs to the technical field of synthetic aperture radar signal processing. The method comprises the following steps: carrying out amplitude error estimation and compensation on each sub-band echo signal; preliminarily estimating a phase error by using the partial overlapping characteristic of the sub-band spectrum; performing distance compression on each sub-band signal; establishing an optimization model based on a maximum norm, and solving an accurate phase error by taking the preliminarily estimated phase error as an iteration initial value; carrying out sub-band splicing and distance resolution compression on the sub-band signals after phase error compensation; and finally, a corrected SAR image is obtained through a CS imaging algorithm. According to the method, extra calibration signals are not needed, high-precision phase error correction can be achieved only based on echo data, the calculation efficiency is high, and the method is suitable for a high-resolution SF-SAR system.

The invention discloses a self-adaptive phase gradient self-focusing imaging method suitable for a strip SAR (Synthetic Aperture Radar), and belongs to the technical field of synthetic aperture radar signal processing. In order to solve the problems that a traditional phase gradient self-focusing PGA algorithm is difficult to be directly applied to a strip SAR due to multi-point interference and phase error space-variant characteristics, and the processing flow of the traditional phase gradient self-focusing PGA algorithm is not matched with that of a conventional RD imaging algorithm and the like, the invention provides a novel imaging compensation method. The method comprises the following steps: firstly, sequentially carrying out range-direction and azimuth-direction dechirp processing on SAR echo data, and carrying out Fourier transform to obtain a preliminary complex image, thereby fundamentally solving the application premise problem of a PGA algorithm; then, detecting and positioning strong scattering points in the complex image, and carrying out self-adaptive partitioning on the image according to the spatial distribution characteristics of the strong scattering points so as to effectively isolate mutual interference among different targets; then, independently applying a PGA algorithm to each sub-block, and accurately estimating and compensating a phase error introduced by non-ideal motion of the platform through an iteration mode; and finally, synthesizing the compensated sub-blocks into an SAR image which is clearly focused. According to the method, the estimation precision of the phase error is remarkably improved, and high-quality self-focusing imaging of the strip SAR data can be realized.

The invention discloses a large-view-field camera light calibration method and system based on polynomial fitting, and the method comprises the steps: setting a measurement target on a camera and a calibration plate rigid tool, building a fixed connection coordinate system, directly measuring the pose between the coordinate systems through employing a laser tracker and other external high-precision equipment, and achieving the decoupling of a pose error and an image algorithm. The method comprises the following steps of: acquiring a plurality of calibration plate images, performing global polynomial curved surface fitting on sparse feature angular points of each image, and establishing continuous analytic mapping from pixels to a three-dimensional space; and carrying out spatial straight line fitting on a plurality of three-dimensional points corresponding to the same pixel to obtain an accurate light equation of the pixel. Calibration results are stored based on a camera target seat coordinate system, and direct migration and use can be achieved only by re-measuring the conversion relation between the coordinate system and a world coordinate system during actual measurement. The method is suitable for any complex imaging system, and has the advantages of high precision, strong universality, good robustness, outstanding engineering practicability and the like.

The invention relates to the field of camera calibration, in particular to a binocular camera positioning precision evaluation method and device, equipment and a medium. According to the method, the hardware dependence is extremely low, extra complex special equipment is not needed, only the binocular camera is used for collecting the calibration board image, the calibration board is a common tool for binocular system calibration, extra preparation is not needed, and the evaluation cost and the equipment threshold are reduced. And secondly, the operation process is simple, the process of constructing the X corner points through the image and screening the vertexes according to the number of the adjacent points can be automatically completed through a basic image algorithm, tedious manual intervention or complex modeling is not needed, and the steps are clear and efficient. And finally, precision quantification is direct and rapid, an evaluation result can be output based on comparison of geometric dimension parameters between vertexes and a true value, redundant data processing links are omitted, rapid quantification of positioning precision is realized, and the defects of complex equipment and tedious process of an existing method are thoroughly avoided.

The invention discloses a dam anti-seepage body integrity detection method based on an artificial power supply. Comprising the following steps: injecting a broadband excitation current signal into a dam anti-seepage body through a multi-frequency program control constant current source; a modular distributed electrode array is adopted to collect and obtain voltage data of the surface of the dam anti-seepage body in real time; high signal-to-noise ratio voltage data is obtained by adopting filtering processing and a digital phase-locked amplification technology; carrying out three-dimensional inversion calculation by adopting an improved electrical impedance tomography algorithm, and reconstructing an internal conductivity distribution image of the dam anti-seepage body; analyzing, identifying and positioning defects through a deep learning model; and constructing an electro-seepage coupling inversion model, converting the internal conductivity distribution image based on the dam anti-seepage body into permeability coefficient distribution, and generating an integrity evaluation report of the dam anti-seepage body. Compared with a traditional detection method, the method is high in detection precision, wide in application range and high in detection efficiency, and a brand new technical means is provided for evaluating the health state of the dam seepage-proofing body.

The invention provides a multi-modal sample data generation method and a related device, and in the method, a constructed first multi-modal sample data set comprises a collected first wireless local area network picture, a second wireless local area network picture generated based on a text, and a third wireless local area network picture generated based on the first wireless local area network picture. In order to make the sample data closer to reality, processing the first multi-modal sample data set to determine a second multi-modal sample data set, the second multi-modal sample data set comprising a first type of wireless local area network pictures and a second type of wireless local area network pictures, the second type of wireless local area network picture is a picture obtained by performing image algorithm processing on the first type of wireless local area network picture, and the second multi-modal sample data set is used for training a multi-modal large model. Through the method, the sample data is constructed from multiple dimensions, the richness and authenticity of the sample data are increased, and the generalization ability of the multi-modal model is improved.

The application provides a control method of a tracked photovoltaic cleaning robot based on fuzzy logic and proportional differential integral correctors, and relates to the field of robot control, which comprises the following steps: when the tracked photovoltaic cleaning robot is running on a photovoltaic panel, a current straight line is obtained through a camera system cooperating with an image algorithm to obtain a current yaw angle error and a lateral error, fuzzy reasoning is performed on the yaw angle error and the lateral error to obtain a coefficient, and a control signal is obtained by combining two proportional differential integral correctors, the control signal is subjected to hard constraint to obtain a correction amount, and a motor control signal is generated to control the motor of the tracked photovoltaic cleaning robot so that the tracked photovoltaic cleaning robot runs along the texture of the photovoltaic panel. The application can obtain motion information only by using the camera system, and the hardware structure is simple; the pose data obtained through the image algorithm has small fluctuation, so that the tracked photovoltaic cleaning robot can be better controlled, and the cleaning effect on the photovoltaic panel is improved.

The invention relates to a two-dimensional staggered array MIMO (Multiple Input Multiple Output) radar system for monitoring dynamic deformation of a bridge, which realizes decoupling of spatial resolution and time resolution by adopting a two-dimensional staggered array MIMO radar hardware architecture and replacing traditional mobile synthetic aperture with static virtual aperture synthesis through integrated design. According to the system, a continuous virtual area array is synthesized through transmitting and receiving arrays which are in non-uniform sparse arrangement, and high-resolution three-dimensional imaging of a bridge monitoring area is realized in combination with an FMCW signal processing and near-field three-dimensional imaging algorithm; and carrying out pixel-level processing on the serialized three-dimensional complex image by using a rapid time sequence interference and deformation extraction module to obtain a high-precision deformation sequence. The method does not need a mechanical scanning part, has the advantages of high environmental robustness, low hardware cost, flexible deployment and the like, and can provide panoramic and high-precision four-dimensional dynamic deformation field data for bridge structure state evaluation.

The present application relates to the technical field of radar signal processing, aiming at the target positioning and imaging ambiguity caused by the distance-angle coupling of the traditional frequency diversity array beam pattern, and the problem that more array elements are needed for random frequency offset to remove ambiguity, a FDA structure based on joint design of intra-array frequency offset and inter-array frequency offset is proposed, the transmission energy is focused on the expected distance-angle area to realize distance-angle decoupling, and by increasing the number of intra-array frequency increments, the number of array elements is increased to improve the target ambiguity-free limit, the number of frequency increments is increased from N of the traditional FDA to, the order of magnitude of the ambiguity-free limit can be greatly increased, and the tolerance of the target ambiguity-free limit is greater. By optimizing the parameters of the array element and inter-array frequency offset design, the de-ambiguous imaging can be realized without complex imaging algorithm.

The invention belongs to the field of earth exploration, and provides an urban underground collapse hidden danger area rapid detection system and method.The urban underground collapse hidden danger area rapid detection system comprises a miniature intelligent sensor array and a central processing unit, the miniature intelligent sensor array comprises a plurality of detection lines arranged side by side, and each detection line comprises a plurality of miniature intelligent sensors arranged at intervals; the adjacent micro intelligent sensors on the same detection line are connected through a towing cable; the distance between the adjacent micro intelligent sensors is adjustable; and the central processing unit is used for receiving the vibration data acquired by each miniature intelligent sensor, performing inversion on the vibration data by using a background noise surface wave imaging algorithm to obtain an underground transverse wave velocity structure model, and identifying a low-speed abnormal region as a collapse hidden danger region. According to the invention, efficient, accurate, wide-coverage and non-sensitive detection of urban underground collapse hidden dangers can be realized.

The application relates to an online monitoring device and method for microelectrodes, and belongs to the technical field of special machining.The online monitoring device is composed of a coaxial holographic imaging module, an LED backlight imaging module, a motion control module, an image acquisition card, a laser power controller and an LED brightness controller.The LED backlight imaging module is used for positioning the microelectrode image; the coaxial holographic imaging module is used for holographic interference imaging of the microelectrode; based on a holographic reconstruction algorithm, electrode profile information is obtained, and the electrode loss degree is judged.The coaxial holographic imaging module and the LED backlight imaging module switch the positions of the reflecting mirrors through the motion control module to realize control of different imaging modes; the collected images are input into a PC through the image acquisition card, image algorithm analysis is carried out, and the microelectrode loss degree is judged.The application realizes online monitoring of the microelectrode loss.

The invention provides gas phase pipeline leakage detection rapid positioning equipment and a rapid positioning method. The system comprises a sound source acquisition module, a visible light imaging module, a thermal infrared imaging module, an information processing module and a display module. The visible light imaging module is used for collecting visual image signals. The thermal infrared imaging module collects a temperature electric signal. The information processing module is used for processing the sound source electric signals, the visual image signals and the temperature electric signals and completing image algorithm superposition calculation of all the signals. Dual judgment of sound source positioning and temperature verification is adopted, rapid space positioning of a leakage sound source is achieved in combination with leakage sound source detection of the sound source collection module, and meanwhile misjudgment caused by interference factors such as environmental noise and equipment vibration is effectively eliminated through temperature anomaly verification of the thermal infrared imaging module. The positioning precision is high, and the position of a leakage point is quickly and accurately locked.

The invention discloses a three-dimensional imaging detection integrated device and method for a carbon deuterium pellet, and belongs to the technical field of optical precision measurement and nondestructive testing. The device comprises an illumination mechanism, a light source mechanism and a control mechanism, wherein the illumination mechanism adopts an addressable LED array to provide multi-angle illumination; the imaging mechanism is a 4f microscopic system and is used for collecting images; the sample control mechanism is used for realizing automatic posture adjustment and transmission of the pellets; and the control mechanism coordinates all the modules to complete automatic detection. The method comprises the steps that an image sequence is collected, complex amplitude projection is recovered through a Fourier lamination imaging algorithm, and based on a tomography inversion algorithm, the surface point cloud radius is calculated and compared with a standard value, and the defect is automatically identified and marked. According to the invention, automatic, quantitative and high-resolution three-dimensional imaging and evaluation of the morphology and internal defects of the pellet are realized, and a stable and efficient measurement platform is provided for scientific research and industrial application.

A large field of view camera light ray calibration method and system based on polynomial fitting, the method is that the camera and the calibration board rigid tooling are respectively provided with measurement targets, a fixed connection coordinate system is established, and an external high-precision device such as a laser tracker is used to directly measure the pose between the coordinate systems, and the decoupling of the pose error and the image algorithm is realized. A plurality of calibration board images are collected, a global polynomial curved surface fitting is respectively performed on the sparse feature corner points of each image, a continuous analytical mapping of pixels to three-dimensional space is established, and then a plurality of three-dimensional points corresponding to the same pixel are subjected to spatial straight line fitting, so that the accurate light ray equation of the pixel is obtained. The calibration result is stored based on the camera target seat coordinate system, and when actually measuring, only the conversion relationship between the coordinate system and the world coordinate system needs to be measured again, so that the calibration result can be directly migrated and used. The application is suitable for any complex imaging system, and has the advantages of high precision, strong universality, good robustness and outstanding engineering practicability.

The invention discloses a single pixel panoramic imaging (SPPI) method based on a Walsh-Hadamard (W-H) base. The SPPI technology is widely applied to the fields of automatic driving, pipeline detection, low-altitude economy and the like, and according to a traditional scheme, although efficient panoramic perception is achieved through combination of a convex mirror and an imaging algorithm, the algorithm efficiency and precision still need to be optimized. According to the invention, a W-H orthogonal basis optimization panoramic annular modulation mode is introduced, and the SPPI technology is improved on one-dimensional and two-dimensional imaging algorithms. The method mainly comprises the following steps: 1) constructing a two-dimensional orthogonal ring modulation framework by adopting a W-H orthogonal basis to replace a random mode; 2) building a panoramic imaging system based on a passive modulation single-pixel camera; and 3) improving a single-pixel panoramic imaging model based on two-dimensional W-H base orthogonality and a V2DALM algorithm, and optimizing the panoramic imaging adaptation capability of the algorithm. According to the method, the imaging speed and quality are considered, and the optimal SPPI scheme can be selected for different application scene requirements such as high fidelity, high speed and speed-fidelity balance.

The application relates to a method for detecting an obstacle in a parking space and a storage medium, the method comprising: collecting a parking space image; splitting the parking space image into a plurality of sub-images; determining texture features and color features of each of the plurality of sub-images; determining texture similarity of adjacent two of the plurality of sub-images with respect to the texture features and color similarity with respect to the color features; forming a difference coefficient of the parking space image according to statistical information of the texture similarity and the color similarity; and judging whether an obstacle exists in the parking space according to the difference coefficient. The method can determine whether an obstacle exists in the parking space according to an image algorithm, so as to guarantee parking safety.

The invention discloses a method for extracting a self-adaptive uniform region and reducing phase noise based on a GNSS-based InSAR (Global Navigation Satellite System-Based InSAR) system. The method mainly aims at the problem that a traditional noise reduction algorithm based on a uniform region under a GNSS-based InSAR system is not applicable, and firstly, an improved Canny edge detection algorithm is used for carrying out self-adaptive uniform region extraction on an SAR image according to a resolution unit center and a gradient size. Then, a coherence matrix is introduced, a main phase component is obtained through eigenvalue decomposition, and the phase change of a deformation area is obtained; the method overcomes the limitation of a traditional InSAR imaging algorithm, is suitable for a GNSS-based InSAR system, can reduce phase noise interference, and lays a foundation for deformation monitoring application.

The application discloses a kind of acoustic-electric tomography image imaging algorithm based on two-point gradient iterative method, and the innovation is to improve the calculation efficiency by two-point gradient iterative method, and the accuracy of image reconstruction is improved by the selection of regularization term.The core of the application is to use the characteristics of acoustic-electric hybrid imaging, that is, when the boundary detection current is applied, the power density data is obtained by using ultrasonic disturbance, so as to obtain the internal data of biological tissue.At the same time, according to the different characteristics of different biological tissue conductivity, different regularization terms are introduced, two-point gradient iterative method is established, and high-resolution reconstruction of biological tissue conductivity is realized.Compared with the traditional acoustic-electric imaging method, the application reduces the calculation and storage cost of multiple observation currents, improves the imaging efficiency.And the iteration process is modified by using a special regularization term, so that the boundaries or geometric characteristics of different tissues can be accurately determined, and the imaging accuracy is improved.

This application provides a method and system for target translational compensation and three-dimensional imaging using a near-range millimeter-wave MIMO radar, enabling real-time three-dimensional imaging. The method includes: receiving echo data and motion velocity of a person under test; performing phase calibration on the echo data; determining the movement distance of the person under test within the acquisition time based on the motion velocity and the acquisition time required to acquire one frame of echo data; dividing the phase-calibrated echo data into blocks based on the movement distance and azimuth resolution; performing a two-dimensional Fourier transform and motion compensation processing on each block of echo data based on the motion velocity; performing a two-dimensional inverse Fourier transform on each processed block of echo data, and then coherently superimposing each block of echo data to obtain motion-compensated echo data; then superimposing the motion-compensated echo data to obtain motion-compensated echo data, and finally processing it based on the principle of stationary target three-dimensional imaging algorithm to obtain a three-dimensional image of the person under test.