Jen-Yu Han

A Noniterative Approach for the Quick Alignment of Multistation Unregistered LiDAR Point Clouds

A novel approach for aligning multistation unregistered Light Detection and Ranging (LiDAR) point clouds is presented in this letter. It is designed to find the rigid rotations and translations between two data sets using hybrid conjugate features, including points, lines, planes, and groups of points. In addition, the proposed solution is expressed in a closed form, meaning that neither an initial alignment nor an iterative computation is required. Based on the numerical results from a real case study, it has been demonstrated that the proposed approach is capable of giving an efficient and reliable alignment solution. With the aforementioned advantages, the proposed technique can not only be directly implemented in a general analysis of LiDAR surveying data but will also particularly benefit those applications where classical point-based iterative analysis approaches are not practically feasible (e.g., an application without a sufficient number of connecting points).

LiDAR Point Cloud Registration by Image Detection Technique

In this letter, a novel approach that utilizes the spectrum information (i.e., images) provided in a modern light detection and ranging (LiDAR) sensor is proposed for the registration of multistation LiDAR data sets. First, the conjugate points in the images collected at varied LiDAR stations are extracted through the speedup robust feature technique. Then, by applying the image-object space mapping technique, the 3-D coordinates of the conjugate image points can be obtained. Those identified 3-D conjugate points are then fed into a registration model so that the transformation parameters can be immediately solved using the efficient noniterative solution to linear transformations technique. Based on numerical results from a case study, it has been demonstrated that, by implementing the proposed approach, a fully automatic and reliable registration of multistation LiDAR point clouds can be achieved without the need for any human intervention.

A Direct Determination of the Orientation Parameters in the Collinearity Equations

Collinearity equations provide an essential basis for photogrammetry applications in which the observables in the image and object spaces are related within an imaging system. It has been routine practice to determine the exterior orientation parameters in these equations using observed control points. However, due to the nonlinearity of the collinearity equations, an appropriate set of approximate values for the orientation parameters must be previously given in order to initiate the parameter estimation procedure and result in a converged solution. In this letter, a quick algorithm for determining the orientation parameters is proposed based on the newly developed noniterative solutions to linear transformations technique. This algorithm does not require auxiliary attitude information (e.g., from inertial navigation system (INS) measurements or trajectory data), and a direct solution for the orientation parameters can be obtained using a closed-form expression. It is then demonstrated, in a real case study, that the proposed approach is capable of producing a set of orientation parameter estimates with a sufficient level of quality to support rigorous image analyses.

Rotation- and Translation-Free Estimations of Symmetric, Rank-Two Tensors with a Case Study in LIDAR Surveying

An eigenparameter analysis plays an important role in varied fields where a symmetric tensor is involved. This technique allows one to investigate the principal behaviors (i.e., magnitudes and orientations) of a physical phenomenon that can be represented as a rank-two symmetric tensor. In this study, an analytical approach that enables rotation- and translation-free estimations of the eigenparameters from a symmetric tensor is developed, with a goal to remove the errors associated with a neglect and/or miscalculation of reference frame variations during a dynamical process. Two numerical examples, one with simulated data and the other with real light detection and ranging (LIDAR) surveying data, have been carried out to demonstrate the capability of the proposed approach in estimating the principal strains from a symmetric strain tensor. The results reveal that the proposed approach is capable of giving a direct estimate for the strain tensor without being affected by the rotation and translation of the reference frame and thus produces a principal strain estimate of a higher quality.

Time-Variant Registration of Point Clouds Acquired by a Mobile Mapping System

A mobile mapping system (MMS) is a combination of several modern spatial techniques, including laser scanning, digital photogrammetry, global positioning system, and inertial navigation system. It is one of the most powerful systems capable of acquiring meticulous spatial information in a fast and automatic manner. However, the degradation of positional quality in areas with very limited satellite visibility is a constant issue disturbing the reliability of such a system. In this letter, a rigorous registration approach for MMS-collected point clouds is proposed. By making use of a time-variant reference transformation model and a few calibration points, most positioning errors due to the loss of satellite signals can be significantly eliminated. Consequently, the applicability of the MMS technique can be further extended to areas where current methods are limited (e.g., in a tunnel or urban area).

Determining the optimal site location of GNSS base stations

The relative positioning technique plays an essential role in Global Navigation Satellite System (GNSS) surveys. Simultaneous observation at base and rover stations eliminates the majority of error sources thus the quality of a positioning solution can be substantially improved. However, topographic obstruction is still a key issue affecting positioning quality. In this study, an integrated approach for analyzing the impact of topographic obstruction on GNSS relative positioning has been developed. By considering varied satellite geometry according to actual terrain variation, this approach can be used to realistically determine satellite visibility condition for a specific base station with respect to any rover station. Furthermore, a base station quality index (BSQI) is proposed as an explicit indication of the sufficiency in a relative positioning. By incorporating the proposed approach, one can immediately identify an optimal site location for a GNSS base station with subsequent GNSS field survey thus achieved in a more reliable and cost-efficient manner.

Feature Conjugation for Intensity-Coded LIDAR Point Clouds

AbstractFeature conjugation is a major task in modern-day spatial analysis and contributes to efficient integration across multiple data sets. In this study, an efficient approach that utilizes the intensity information provided in most light detection and ranging (LIDAR) data sets for feature conjugation is proposed. First, a two-dimensional (2D) intensity map is generated based on the original intensity-coded LIDAR observables in three-dimensional (3D) space. The 2D map is further transformed into a regularly sampled image, and an image feature detection technique is subsequently applied to identify point conjugations between a pair of intensity maps. Finally, the paired conjugations in the image space are mapped backward into the LIDAR space, and the object coordinates of the conjugate points can be verified and obtained. Based on the numerical results from a real world case study, it is illustrated that by fully exploring the existing spectral information, a reliable feature conjugation across multipl...

Alternative transformation from Cartesian to geodetic coordinates by least squares for GPS georeferencing applications

The inverse transformation of coordinates, from Cartesian to curvilinear geodetic, or symbolically (x,y,z)->(@l,@f,h) has been extensively researched in the geodetic literature. However, published formulations require that the application must be deterministically implemented point-by-point individually. Recently, and thanks to GPS technology, scientists have made available thousands of determinations of the coordinates (x,y,z) at a single point perhaps characterized by different observational circumstances such as date, length of occupation time, distance and geometric distribution of reference stations, etc. In this paper a least squares (LS) solution is introduced to determine a unique set of geodetic coordinates, with accompanying accuracy predictions all based on the given sets of individual (x,y,z) GPS-obtained values and their variance-covariance matrices. The (x,y,z) coordinates are used as pseudo-observations with their attached stochastic information in the LS process to simultaneously compute a unique set of (@l,@f,h) curvilinear geodetic coordinates from different observing scenarios.

On rotation of frames and physical vectors: an exercise based on plate tectonics theory

The mathematical interaction between the simultaneous rotation of both a coordinate frame and a set of physical vectors in that frame is covered and theoretically and empirically explained. A practical example related to the secular motion of the pole determined using recent GPS results is addressed. A least-squares adjustment is introduced to determine a possible displacement of the geodetic north pole of the frame caused by plausible changes in the coordinates of the observing stations defining the frame due to the rotation of the plates on which these stations are located. Two examples of GPS networks are investigated both referred to the latest definition of the IGS08 geodetic frame. The positioning and velocities of the points were exclusively obtained using GPS data as published by the International GNSS Service (IGS). The first case comprises the complete GPS/IGS network of global stations; the second one assumes the closest GPS/IGS stations to the now discontinued International Latitude Service network. The results of this exercise hints at the possibility that the secular global rotation of the frame caused by plate rotations should be accounted for in order to rigorously determine the true absolute velocities referred to the IGS frame before the actual velocities of the rotation of the plates using GPS observations are published.

Image-Based Approach for Road Profile Analyses

AbstractRoad profile extraction and analysis are essential tasks in transportation asset management. Current approaches use vehicle-borne laser sensors in order to precisely measure the variations in elevation along a specific route. However, a complicated sensor mechanism, such as in the mobile light detection and ranging (LiDAR) system, is involved and the resulting quality is compromised owing to multiple factors. In this study, an image-based approach for extracting road profiles is proposed. It requires only a single camera sensor and a low-cost laser module and is capable of collecting road profiles along both the longitudinal and transverse directions. A detailed methodology is first presented in this paper, followed by a simulation evaluation and a case study. The case study illustrates that the quality of the extracted profiles based on the proposed approach achieves millimeter accuracy. Consequently, an accurate and cost-efficient road profile analysis becomes possible when the proposed approach...