Xiangrui Tian

Bio: Xiangrui Tian is an academic researcher from Beihang University. The author has contributed to research in topics: Lidar & Combustion. The author has an hindex of 6, co-authored 22 publications receiving 101 citations.

Terrain slope estimation within footprint from ICESat/GLAS waveform: model and method

Abstract: Terrain slope of Greenland is usually calculated from surface elevation on a large scale. Novel physical models were established to estimate the terrain slope within laser footprints on a smaller scale. Based on the time-stamped waveforms of ice, clouds, and land elevation satellite/geoscience laser altimeter system (ICESat/GLAS), the physical models for calculating the slopes were established in two cases: zero attitude angles and non-zero attitude angles, respectively. The expressions of waveform slopes are related not only to the waveform width and the mean pulse delay of the time-stamped waveform, both in nanoseconds, but also to the attitude of the satellite and the laser divergence angle. In order to calculate the waveform width and the mean pulse delay, a non-Gaussian mathematical function was proposed to curve-fit the waveforms. The slopes estimated from the waveforms were compared with the slopes calculated from surface elevations. Results show that the two methods generate almost identical slope estimations for the same terrain. Calculation results also indicate that the method for slope estimation proposed in this paper performs better for extreme sloping terrain than for gentle sloping terrain.

Flame temperature field and combustion intermediate product concentration field monitoring system designed on basis of optical compensation

Abstract: The invention discloses a flame temperature field and combustion intermediate product concentration field monitoring system designed on the basis of optical compensation. Flame radiation light is collected by a flame speculum device and a detection wide-angle lens at the front end of the flame speculum device and transferred to a light split device, and narrow-band optical signals with different center wavelength are obtained by a wave filtering device; because all optical paths are different, optical path differences occur among different optical paths; because a lens is provided with different refraction rates in different wavelengths and generates the chromatic dispersion effect, all optical paths are provided with image planes in different distances; a light intensity distribution image in the same definition can be obtained on a CCD receiving device in such a way that the optical path differences and the chromatic dispersion effect are compensated by an optical compensating lens with different diopters; a concentration distribution figure of a combustion intermediate product is obtained by subtracting light intensity distribution images of two paths of signals; and the flame temperature field distribution is obtained by the light intensity comparison of other two paths of optical signals according to a colorimetric method. The invention can simultaneously obtain monitoring images of the two-dimensional distribution of the flame temperature and the concentration of the combustion intermediate product on line.

Geometric distortion correction for sinusoidally scanned images

Abstract: A method for correcting the geometric distortion of sinusoidally scanned images was proposed. The generation mechanism of the geometric distortion in sinusoidally scanned images was analyzed. Based on the relationship between the coordinates of uniformly scanned points and those of sinusoidally scanned points, a transformation formula was obtained for correcting the geometric distortion when the sampling rate was a constant. By comparing the forward method with the inverse method, a hybrid method for correcting the geometric distortion of sinusoidally scanned images was proposed. This method takes advantage of both the forward and inverse methods and was proven to be better than either of them in terms of peak signal-to-noise ratio (PSNR). The time consumed by the hybrid method was between the other two. When a higher PSNR is desired, the hybrid method is recommended if time permits. In addition, it is a universal approach to the correction of geometric distortion of the images scanned in the sinusoidal mode.

Method and device for real-time compensation of roll angle deviation of airborne laser radar

Abstract: The invention discloses a method and a device for the real-time compensation of the roll angle deviation of an airborne laser radar. A roll angle compensation control device and a roll angle driving device are designed mainly. The devices comprise a roll angle compensation controller, a laser Q switch control circuit, a pumping lamp high-frequency pulse power supply and an electro-optic Q switch.The roll angle compensation controller receives the roll angle deviation measured by a GPS/INS combined measuring system, combines a real-time angle measured by a rotary prism optical electric axial angle encoder for making a judgment and outputs a high-level conduction control signal; the signal and a high-frequency pulse signal of the pumping lamp power supply commonly act on the laser Q switchcontrol circuit so that the laser Q switch control circuit outputs the high-voltage pulse signal to the electro-optic Q switch in a control signal connection period so as to control a laser emitter to emit laser pulses in a proper scanning angle area to realize real-time high-precision compensation of the roll angle deviation.

Method for simultaneously monitoring two-dimensional distribution of combustion flame temperature field and concentration of combustion flame intermediate product

Abstract: The invention discloses a method for simultaneously monitoring the two-dimensional distribution of a combustion flame temperature field and the concentration of a combustion flame intermediate product. A flame detecting device, a light split device, a wave filtering device and a detection processing device are provided in the method, wherein the flame detecting device comprises a flame speculum device as well as a wide-angle lens and a cooling sleeve which are arranged at the front end of the flame speculum device; flame radiation light is transferred to the light split device by the speculumdevice; after the light is split, four paths of narrow-band optical signals with different center wavelengths are obtained by the wave filtering device; the detection processing device comprises a CCD receiving device and a software processing system; the receiving device obtains four paths of different light intensity distribution images, and the light intensity distribution images of two paths of signals are subtracted to obtain a concentration distribution image which corresponds to the combustion intermediate product according to an absolute black body radiation law; the light intensity of other two paths of narrow-band optical signals is compared, and the flame temperature field distribution can be obtained according to a colorimetric method. The invention can simultaneously monitor the two-dimensional distribution of the flame intermediate material and the flame temperature field in real time.

Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain.

Abstract: Two-photon calcium imaging provides an optical readout of neuronal activity in populations of neurons with subcellular resolution. However, conventional two-photon imaging systems are limited in their field of view to ∼1 mm(2), precluding the visualization of multiple cortical areas simultaneously. Here, we demonstrate a two-photon microscope with an expanded field of view (>9.5 mm(2)) for rapidly reconfigurable simultaneous scanning of widely separated populations of neurons. We custom designed and assembled an optimized scan engine, objective, and two independently positionable, temporally multiplexed excitation pathways. We used this new microscope to measure activity correlations between two cortical visual areas in mice during visual processing.

Non-Parametric Statistics

Abstract: Beginning statistics students are usually introduced to what are called “parametric” statistics methods. Those methods utilize “models” of score distributions such as the normal (Gaussian) distribution, Poisson distribution, binomial distribution, etc. The emphasis in parametric statistical methods is estimating population parameters from sample statistics when the distribution of the population scores can be assumed to be one of these theoretical models. The observations made are also assumed to be based on continous variables that utilize an interval or ratio scale of measurement. Frequently the measurement scales available yield only nominal or ordinal values and nothing can be assumed about the distribution of such values in the population sampled. If however, random sampling has been utilized in selecting subjects, one can still make inferences about relationships and differences similar to those made with parametric statistics. For example, if students enrolled in two courses are assigned a rank on their achievement in each of the two courses, it is reasonable to expect that students that rank high in one course would tend to rank high in the other course. Since a rank only indicates order however and not “how much” was achieved, we cannot use the usual product–moment correlation to indicate the relationship between the ranks. We can estimate, however, what the product of rank values in a group of n subjects where the ranks are randomly assigned would tend to be and estimate the variability of these sums or rank products for repeated samples. This would lead to a test of significance of the departure of our rank product sum (or average) from a value expected when there is no relationship.

K-Plane-Based Classification of Airborne LiDAR Data for Accurate Building Roof Measurement

Abstract: A new classification method based on the k-plane clustering algorithm is proposed to segment the point cloud of a building roof, which is obtained from an airborne light detection and ranging (LiDAR) instrument. In the operation of laser points clustering, 3-D coordinates of laser points in the point cloud are directly used as clustering objects. Fitting planes of laser points in the clusters are generated from the obtained clustering solution, and intersecting lines of the fitting planes are calculated. Using the intersecting lines, the point cloud of the building roof is then segmented. Since calculation for the clustering objects, i.e., the normal vectors of neighboring planes of the laser points, required in the classification methods based on the fuzzy k-means clustering algorithm is avoided in the proposed method, not only is the complexity of the classification procedure reduced, but also the accuracy of classification result is improved. In addition, in the proposed method, to guarantee the effectiveness of the k-plane algorithm, the initial cluster planes are estimated from the elevation image of building roof in advance before the process of clustering operation. The proposed k-plane-based classification method is validated by using a number of real airborne LiDAR point clouds.

Correction of image drift and distortion in a scanning electron microscopy

Abstract: Continuous research on small-scale mechanical structures and systems has attracted strong demand for ultrafine deformation and strain measurements. Conventional optical microscope cannot meet such requirements owing to its lower spatial resolution. Therefore, high-resolution scanning electron microscope has become the preferred system for high spatial resolution imaging and measurements. However, scanning electron microscope usually is contaminated by distortion and drift aberrations which cause serious errors to precise imaging and measurements of tiny structures. This paper develops a new method to correct drift and distortion aberrations of scanning electron microscope images, and evaluates the effect of correction by comparing corrected images with scanning electron microscope image of a standard sample. The drift correction is based on the interpolation scheme, where a series of images are captured at one location of the sample and perform image correlation between the first image and the consequent images to interpolate the drift-time relationship of scanning electron microscope images. The distortion correction employs the axial symmetry model of charged particle imaging theory to two images sharing with the same location of one object under different imaging fields of view. The difference apart from rigid displacement between the mentioned two images will give distortion parameters. Three-order precision is considered in the model and experiment shows that one pixel maximum correction is obtained for the employed high-resolution electron microscopic system.

Satellite Attitude Determination and Map Projection Based on Robust Image Matching

Abstract: Small satellites have limited payload and their attitudes are sometimes difficult to determine from the limited onboard sensors alone. Wrong attitudes lead to inaccurate map projections and measurements that require post-processing correction. In this study, we propose an automated and robust scheme that derives the satellite attitude from its observation images and known satellite position by matching land features from an observed image and from well-registered base-map images. The scheme combines computer vision algorithms (i.e., feature detection, and robust optimization) and geometrical constraints of the satellite observation. Applying the proposed method to UNIFORM-1 observations, which is a 50 kg class small satellite, satellite attitudes were determined with an accuracy of 0.02°, comparable to that of star trackers, if the satellite position is accurately determined. Map-projected images can be generated based on the accurate attitudes. Errors in the satellite position can add systematic errors to derived attitudes. The proposed scheme focuses on determining satellite attitude with feature detection algorithms applying to raw satellite images, unlike image registration studies which register already map-projected images. By delivering accurate attitude determination and map projection, the proposed method can improve the image geometries of small satellites, and thus reveal fine-scale information about the Earth.