Xiangrui Tian

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

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.

Geometric distortion correction for sinusoidally scanned images

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.

Simulation on impact of random attitude measurement errors on point cloud and 3D image of ALS

The influence of random attitude measurement errors of the GPS/INS integrated system on the laser point cloud and the three-dimensional (3D) surface image reconstructed by the airborne laser scanner was studied. The mapping relationship between the attitude measurement errors and the positioning errors of the laser footprints was derived. By numerical simulation, three common terrains, i.e. a planar, a rectangular, and a hemisphere terrain, were simulated, and the impacts of the random attitude measurement errors on the laser point clouds and the reconstructed 3D surface images of the three terrains were analyzed, respectively. Simulation results show that the random attitude measurement errors decrease the positioning accuracy of the laser point clouds, further directly deteriorating the 3D surface image. The greater the random attitude measurement errors are, the greater the caused 3D imaging distortion.

Impact analysis of random measurement errors on airborne laser scanning accuracy

In this paper, the impacts of the random measurement errors on airborne laser scanning (ALS) accuracy were studied. Firstly, the transformation formulas from measurement parameters to the coordinates of laser footprints were derived and the factors affecting ALS accuracy were analyzed. According to the actual characteristics of these factors, 2000 sets of experimental data of the random measurement errors were simulated and the errors of three-dimensional (3D) coordinates of the laser footprints were calculated. Then, the simulated experimental error data were processed by using the linear least squares regression method to get the standardized regression coefficients. According to the obtained standardized regression coefficients, the impacts of various random measurement errors on the 3D coordinate errors were evaluated quantitatively, and the variation of the impacts with increasing flight height was studied. Analysis results provide an important basis for error budget of ALS system and improvement of ALS accuracy.

Determination of platform attitude through SURF based aerial image matching

In this paper, an improved image matching methods based on Speeded Up Robust Features (SURF) algorithm was proposed to calculate the attitudes of the aircraft platform. Firstly, SURF algorithm was used to extract series of the interest points of two selected images. Then the improved nearest neighbor matching method based on KD-tree was used to get the pairs of the matching interest points. And the RANdom SAmple Consensus (RANSAC) algorithm was used to remove the error pairs of matching interest points. Finally, the transformation matrix between the two selected images was established to obtain the attitude angles. In order to validate the effectiveness, two images were utilized to implement the proposed methods. The experimental results show that the algorithm has the advantage in both accuracy and time-consuming, which is helpful to improve the performance of image navigation.

Impact of attitude measurement errors on laser footprints positioning accuracy

In order to analyze the impact of attitude measurement errors (roll, pitch and yaw errors) on the positioning accuracy of laser footprints, the positioning principle of airborne Light Detection And Ranging (LiDAR) was analyzed and the transformation relationship between the attitude measurement errors and the positioning errors of laser footprints was deduced. Considering the actual complex terrain, three different terrains were simulated to analyze the influence of attitude measurement errors on the positioning accuracy of laser footprints. After simulating calculations, some conclusions can be obtained, such as the impact of the roll angle error on the positioning accuracy of laser footprints is the most significant, the impact of the yaw angle error is minimal. And the results of the study will offer a theory foundation for the study of the positioning accuracy of laser footprints and practical application.

A federal UKF algorithm in INS/GPS/aerial image integrated attitude determination system

According to the attitude determination method based on aerial images, an INS/GPS/aerial-image integrated attitude determination system solutions was proposed to improve the airborne platform attitude determination accuracy and reliability. A federal Unscented Kalman Filter (UKF) algorithm based on optimization information distribution factor was used in the INS/GPS/aerial-image integrated system. The integrated system included INS/GPS and INS/aerial-image two subsystems, the outputs from two subsystems were fused in the main filter. Finally, optimal parameters of the system state estimation were obtained. Experimental results show that the proposed method well solves the error divergence problem over time with INS, and prevents the truncation error generated by EKF algorithm. The integrated attitude determination system can get higher precision and reliability.

Impacts of control errors and measurement errors in airborne LiDAR on laser point cloud

The impacts of various control errors and measurement errors of airborne LiDAR on laser point cloud were studied. Firstly, the principle of the Palmer-scan airborne LiDAR was analyzed. Then the transformation formulas, from the control errors and measurement errors of various parameters, such as attitude angles, flight trajectory and scan angle in airborne LiDAR system, to the three-dimensional (3D) coordinate errors of the point cloud, were derived. Finally, by numerical simulation, two terrain models (planar and hemisphere terrains) were established, and the impacts of the control errors and measurement errors of flight trajectory and attitude angles on the laser point cloud were analyzed. Results show that the control errors mainly cause the distribution region shifting and the point density decreasing of the laser point cloud, while the measurement errors mainly result in the 3D coordinate accuracy decreasing of the laser point cloud. The combining impact of the control errors and measurement errors results in the distortion increasing of the reconstructed 3D surface models relative to the surveyed terrain.

Design on the aerial survey parameters of the airborne LiDAR

A new method of parameters design for aerial survey based on the laser footprint distribution of airborne LiDAR was proposed. In order to implement the method of parameters design, the relationship maps between the distribution of laser footprints and different parameters, respective the parameters of laser beam, flight and laser scanning system were created. Using the actual parameters and the independent variable of the number of scanning strips, the best aerial survey parameters and flight routes were designed. It is an important method to achieve the least scanning time cost as a dependent variable.

A kernel-density-estimation-based outlier detection for airborne LiDAR point clouds

An outlier detection method is proposed based on the kernel density estimation for removing the outliers in airborne LiDAR point clouds. The point cloud is divided into many blocks. Then, in each block, the kernel probability density of the height values of all points is estimated. Two elevation thresholds, one for low outliers and one for high outliers, are selected based on the values of the probability density and the values of elevation. The computation is simplified in complexity for the method doses not focus on the calculation of individual points. Two datasets were utilized to test our method. This method combines distance-based method with density-based method. Experiments showed that our proposed method had good performance.