148 results about "Colatitude" patented technology

A metrology target design may be optimized using inputs including metrology target design information, substrate information, process information, and metrology system information. Acquisition of a metrology signal with a metrology system may be modeled using the inputs to generate one or more optical characteristics of the metrology target. A metrology algorithm may be applied to the characteristics to determine a predicted accuracy and precision of measurements of the metrology target made by the metrology system. Part of the information relating to the metrology target design may be modified and the signal modeling and metrology algorithm may be repeated to optimize the accuracy and precision of the one or more measurements. The metrology target design may be displayed or stored after the accuracy and precision are optimized.

This invention belongs to measuring technique field and relates to improvement for space round geometry parameters non-contact measuring method. This invention can calculate eh real three dimensional coordinates of round fringe by use of polar line restriction and calculate space round geometry parameters based on space round optimal fit. This invention reduces the measuring error caused by shape distortion of space round perspective projecting and increases the measuring accuracy of round geometry parameters based on the optical method. When the surface of space round to be measured is angle more than fifty degrees, the repeatability accuracy 3sigma of space round geometry center is superior to minus or plus 0.01 mm.

A driving lane recognition system which can improve the lane recognition accuracy by stably detecting the various kinds of lane markers is disclosed. An image processing means 6 for image-processing a road image taken by a camera 5 has a plurality of different kinds of image processing algorithms 9 to 11. A driving lane is detected by selecting an image processing algorithm suitable for the driving lane out of the plurality of different kinds of image processing algorithms 9 to 11 corresponding to a road on which a vehicle is running.

A method and a measuring instrument for determining the position of an edge to be measured on a pattern on a substrate are described. A complete, nonlinear model intensity profile, which identifies the edge to be measured, of a model edge is ascertained and stored, and a desired edge position x_k is defined therein with subpixel accuracy. A camera image of the substrate having the edge to be measured is acquired, and a one-dimensional measured intensity profile of the edge to be measured is determined therefrom. The model intensity profile is identified in the measured intensity profile with an indication of its location x_m relative to a reference point. The desired position p of the edge to be measured is determined with subpixel accuracy as p=x_m+x_k.

The invention relates to a real-scene consulting system and a coordinate offset method based on GPS location and direction identification. The system comprises a real-scene consulting electronic device based on technology of GPS location and direction identification, a communication network and an interest point database. The real-scene consulting electronic device comprises a camera, a GPS location module, a horizontal and vertical direction identification module, a display module, a data storage module, a coordinate offset converting module and a treatment control module, wherein the treatment control module is connected with the other modules. The coordinate offset converting module can offset the accurate coordinate into the offset coordinate and correct the offset coordinate into the accurate coordinate. The coordinate offset method of the invention has the advantages of improving the searching and inquiring accuracy and precision of the surrounding interest points, improving the calculation accuracy and precision of the distance between the present position and the interest point, and improving the accuracy and the precision of the real-scene function. The invention can offset the coordinate and correct the coordinate to ensure that the present position and the position of the interest point are precisely marked in the real-scene observation and the map display.

The invention discloses an attitude standard deviation estimation and correction method of a star sensor and a payload. The attitude standard deviation estimation and correction method comprises the following steps of 1, according to payload characteristics, determining a location formula of an incident light vector of a payload and building a payload error model with payload standard deviation, 2, according to star sensor characteristics, building a star sensor error model with star sensor standard deviation, 3, through the payload, determining measured deviation by observation data of a known target and corresponding star sensor measured data, and building a payload and star sensor standard deviation measurement equation according to the measured deviation, the payload standard deviation and the star sensor standard deviation, 4, carrying out estimation of the star sensor or payload standard deviation according to the payload and star sensor standard deviation measurement equation, and 5, correcting the star sensor or payload measured data by the estimated standard deviation. The attitude standard deviation estimation and correction method can reduce star sensor and imaging payload attitude standard deviation and improve imaging quality and an image positioning precision.

The present invention is one kind of apex curvature radius measuring method and device for aspherics and relates to the technology of measuring aspherical optical elements. Based on ray tracing principle, laser beam is projected to the measured aspherics in the dot array structural light mode, the positions of one incident light spot and the reflected light spot on light receiving screen are measured with a CCD camera, and the images of the incident flare and the reflected flare are analyzed and processed in computer, so that the apex curvature radius of the aspherics is obtained. The method has relatively high measurement precision, especially to large apex curvature radius of aspherics, and the present invention may also realize the in-situ measurement of the aspherics in its production.

A method for identifying roadway curvature that includes determining a range of interest and collecting shape points from a map database from a current position of the vehicle to an end of the range of interest that define the location of the roadway. The method converts the shape points from World Geodetic System 84 (WGS84) coordinates to UTM coordinates, and then fits a single set of polynomial equations to define a curve using the converted shape points. The method determines whether the single set of polynomial equations exceeds a predetermined curvature accuracy threshold, and if so, fits multiple sets of polynomial equations to multiple roadway segments over the range of interest using the converted shape points. The method then determines the roadway curvature at any roadway location using solutions to the multiple sets of polynomial equations.

The invention discloses an estimation method of an atmosphere angle of attack and an angle of sideslip in a high-angle-of-attack flight status. Under the premise that the structure of an aircraft is not changed and additional measuring devices and hardware devices are not added, the parameters output by the existing onboard strapdown inertial navigation system, a GPS (Global Position System) system, a flight control system and a fuel measuring system are fully used for resolving the angular acceleration, the rotational inertia, the product of inertia, the coefficient of a moment equation set and the total mass of the aircraft; based on a flight dynamics model, by establishing an extended Kalman filter, and integrating the processes of resolving the flight dynamics model and the status estimation together, accurate estimation of the current angle of attack, the angle of sideslip and the true airspeed is realized, and then the current air speed and the change rate of the air speed are resolved and input into the extended Kalman filter as the feedback information so as to finish the real-time accurate estimation of the angle of attack and the angle of sideslip of next time; the real-time accurate estimation of the angle of attack and the angle of sideslip is realized by a recursive resolving mode, measurement range and measurement precision of an atmosphere data system are improved, and adaptability to complex flight environment is also improved.

The invention relates to a self-adaptive indoor vision positioning method based on global motion estimation. The self-adaptive indoor vision positioning method comprises the following steps of: firstly, extracting and matching feature points based on a modified MIC (Minimum Intensity Change) algorithm and a modified SURF (Speed Up Robust Features) algorithm, and estimating an overlapping region of matching images at each time by applying Kalman filtering; secondly, only detecting and matching the feature points on the overlapping region, figuring up offsets of two continuous images in a sequence image by utilizing a global motion estimation method; and lastly, estimating a displacement of a camera by utilizing a six-parameter affine model according to a matching result, drawing a real trace of the camera on an interface of an upper computer in a real-time manner, and correcting the drawn trace according to set wireless beacons. According to the self-adaptive indoor vision positioning method, angular points are detected, described and matched on the overlapping region other than the whole image, the modified MIC algorithm is utilized to detect, so that the effectiveness of extraction of the feature points, the estimated accuracy of the model and the execution speed are improved. The wireless beacons are adopted to correct position information of the camera, so that the positioning accuracy is improved.

A road recognition apparatus estimates road parameters of a road model equation by processing a forward road image of a vehicle. A processor sets a series of windows along a road white line (or lane marker) on the forward road image, and calculates a candidate straight line segment likely to be a white line in each window. The processor further checks an accuracy in position of a candidate white line in each window. The processor estimates the road parameters from the image coordinates of the candidate white line in each or the window higher in the accuracy, and estimates the road parameters exclusive of a vehicle lateral displacement from the gradient of candidate white line in each or the window lower in the accuracy.

The invention relates to a method for calculating for calculating the pose of a vehicle at a curve. The method is based on a combination of GPS positioning and vehicle visual pose calculation based onthe characteristics of a curved road, and comprises the steps of firstly, performing initial positioning using GPS position information of the current vehicle, then matching a test image of the curved road with a curve map database, and finally, performing visual pose calculation according to the matched local feature points to obtain high-precision pose information of the vehicle at the curve. The method overcomes the defects that the existing method using a single GPS is poor in positioning precision and the existing visual pose calculation method is improper in curve pose calculation, andcan solve the problems of large error and high cost in curve vehicle pose calculation, thereby improving the precision of vehicle curve pose calculation.

The present disclosure discloses an aircraft (e.g., unmanned aerial obstacle detection method and apparatus, to reduce aircraft obstacle detection errors, and improve aircraft obstacle detection precision. The apparatus performs image collection on a target obstacle by using a binocular camera, to obtain a first image and a second image. After determining a first pixel location obtained by projecting the target obstacle in the first image, and a second pixel location obtained by projecting the target obstacle in the second image, the apparatus calculates a disparity between the first pixel location and the second pixel location and a depth value between the binocular camera and the target obstacle according to the disparity and a preset disparity-to-depth mapping matrix, to detect whether a flight direction of the aircraft is blocked by an obstacle.

The invention discloses a lane judgment method based on latitude and longitude acquisition points. Multiple reference points are set on a target road, and a principal coordinate matrix of the target rod and a sub-coordinate matrix of each lane are acquired; the lane in which a target vehicle is positioned is determined, the coordinate values of all the reference vehicles in the adjacent lanes of the lane in which the target vehicle is positioned are collected, and actual distance between the target vehicle and the reference vehicles is acquired through matrix calculation; and whether the target vehicle can change lane is judged by comparing the actual distance and safe distance. Meanwhile, the invention also discloses a positioning device applied to the method. Advantages of the method are that the method has higher reliability in comparison with that of an independent GPS and has better road fault tolerance in comparison with that of radar so that degree of safety is higher, data feedback is more rapid, and whether the vehicle can change lane is prejudged through establishment of a vehicle latitude and longitude matrix coordinate system and differential correction of precision of submitted distance calculation.

The invention discloses a strapdown inertial navigation system coarse alignment method based on a recursive quaternion. According to the method, a constant value attitude matrix in solidification method coarse alignment is calculated by adopting a recursive quaternion algorithm, and then the strapdown inertial navigation coarse alignment process is completed on the basis of solidification method coarse alignment. Solving of an initial attitude matrix is converted into calculation of the constant value attitude matrix in solidification method coarse alignment, an optimal quaternion solution of the constant value attitude matrix in a solidification method can be solved by constructing observation vectors and a reference vector and adopting a recursive quaternion algorithm, and then the strapdown inertial navigation coarse alignment process is completed. By constructing different observation vectors, the method can be applied in initial alignment under a static base and a swinging base and also applied in initial alignment under a movable base. The recursive quaternion algorithm is applied in the solidification method coarse alignment process, the alignment precision and the convergence speed can be improved. Therefore, the method has a very good engineering reference and application value by serving as a coarse alignment method for the swinging base or the movable base.

A user gives, as input, two curves at a start time and at an end time and reference correspondence points with respect to the respective curves. Then, a pursuit operation of pursuing a reference correspondence point is carried out with respect to picture images successive in the time axis direction. As a result, positions of reference correspondence points at respective intermediate stages can be determined. Then, interpolation of the shape is carried out. Then, the determined interpolated shape is deformed in correspondence with the determined reference correspondence point. Accordingly, even in the case where a contour shape does not linearly move, it is possible to precisely pursue correspondence points on the contour. Thus, a contour shape with higher precision can be prepared.

The invention discloses a camera angle calibration method during a robot speech localization process. The method comprises a first step of speech coarse localization in which the camera is rotated to an approximate speech source direction according to the speech information, a second step of human face detection in which the camera is used for detecting whether a human face exists and a third step is carried out if the camera detects the human face, a third step of human face angle deviation calculation in which a rectangular coordinate axis is built with the camera center as the original point, the coordinates [X, Y] of the human face center are localized, and the coordinates [X, Y] are deviation between the human face center and the camera center, and a fourth step of angle adjustment in which the angle degreeX of the camera rotating along the X axis and the angle degreeY of the camera rotating along the Y axis are converted according to the deviation between the human face coordinates and the camera center and then, the camera is rotated to enable the human face center to be aligned with the camera center according to the degreeX and the degreeY. The camera alignement precision during the speech localization process is improved.

Scattered X-rays scattered by an object or a structure enter in a detector (a shift detector) for detecting the positional shift of an X-ray focal point and become a noise source, thereby deteriorating the positional shift detection precision. In particular, the estimation of the dose of scattered X-rays originating from the object is difficult prior to the measurement, and correction of the scattered X-rays is important in order to precisely calculate the positional shift of the X-ray focal point. In order to address this drawback, according to the present invention, a scattered X-ray detector 6 is provided which measures the dose of scattered rays entering in a shift detector 5 for detecting the positional shift of an X-ray focal point 9, and has a function that the output by the shift detector 5 is corrected using the scattered ray dose measured by the scattered X-ray detector.

The invention discloses a Bayesian iterative reweighted sparse autofocus array synthetic aperture radar (SAR) imaging method. The Bayesian iterative reweighted sparse autofocus array SAR imaging method aims at the influence of phase errors existing in array SAR echo signals on imaging results. Based on a traditional sparse autofocus Bayesian recovery via iterative minimum (SAFBRIM) algorithm, a linear measurement matrix of scattering coefficients in the array SAR original echo signals and an observation scene target space is established, norm items in a cost function in the algorithm are subjected to iterative adaptive reweighted processing, pulse compression and equidistant surface division are carried out on a distance direction, and then each equidistant two-dimensional surface is estimated. According to the Bayesian iterative reweighted sparse autofocus array synthetic aperture radar (SAR) imaging method, different weighting coefficients are given to each norm item, and then imagesare reconstructed, so that higher-quality array SAR imaging results can be obtained. The Bayesian iterative reweighted sparse autofocus array synthetic aperture radar (SAR) imaging method has the advantages of high reconstruction precision and effective reduction of phase errors, and can be applied to the fields such as array synthetic aperture radar imaging.

The invention discloses a spatial non-cooperative target pose measurement method based on stereoscopic vision. The method does not need any auxiliary measurement tool and a geometric size of a target, and directly recognizes the inherent characteristics of a non-cooperative target to realize the measurement of target position attitude parameters. The method utilizes an image pre-processing frame based on adaptive smoothing filtering and Wallis filtering to solve the problem of image degradation caused by a complex space environment so that the accuracy of non-cooperative target recognition and feature extraction is improved. A feature matching algorithm based on spatial geometric constraint is adopted so that the epipolar constraint in the plane is extended to the space, and the three-dimensional information is obtained directly when the feature matching is completed so that the complexity of the image processing algorithm is reduced.