Jacek Rapinski

M-Split Estimation in Laser Scanning Data Modeling

This paper proposes a new approach to 3D modeling on the basis of laser scanner data. It presents the attempt to automatically detect two planes and an edge in one processing algorithm. The algorithm is based on the Msplit estimation, which is a recently developed regression method of multi functional models. Plane equations in three dimensional space are derived on the basis of the presented method. Msplit estimation divides the functional model of least squares adjustment in particular into two groups. Both simulated and real data from airborne laser scanning is tested to present the results. In each case the mehod gave good results which encourages for further work on the application of this method for 3D modeling.

Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud

Airborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration), and the main processing (including DTM generation). Problems primarily concerning the time span necessary for processing a very high number of observations occur at each of the stages mentioned above. In previous studies the authors proposed modification of the ALS point cloud methodology. The modification introduced an optimization algorithm to reduce the size of the survey dataset at the stage of initial processing. Those studies analyzed the “optimization–filtration” and “filtration–optimization” variants, applying methods based on the multi (M) estimation principle at the filtration stage. This study presents a modified process of the initial data processing stage with the application of filtration using the adaptive triangulated irregular network (TIN) model and an optimization algorithm. The algorithm used the Visvalingam–Whyatt generalization method.

ZigBee Ranging using Phase Shift Measurements

This paper presents the results of distance measurements performed with an AT86RF233 chip. It uses a combination of time of flight and phase shift measurements to perform ranging. The statistical parameters describing the ranging results are presented and an algorithm to process raw measurement data is proposed. The results show significant improvement in ranging accuracy.

Application of the Msplit method for filtering airborne laser scanning data-sets to estimate digital terrain models

ALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey conditions. This article proposes the use of a new estimation method in the filtering of point clouds obtained from airborne laser scanning (ALS), provisionally called Msplit-estimation. The application of Msplit-estimation in ALS data filtering requires the determination of the appropriate functional model for the surface, which will be used in the filtering of the set of points. A polynomial terrain surface model was selected for this purpose. Two methods of filtering using the Msplit method are presented. The first is based on the estimated parameters of the polynomial describing the surface (called the ‘quality’ approach in the article). The second method (provisionally called the ‘quantity’ method) is carried out in two stages. The first stage is point cloud filtering, which results in two subsets being created. One of these is the subset of points intended for DTM creation, while the other contains the remaining points. The second stage of the approach is the creation of a DTM from the first subset. Since the Msplit method has an analytical character, the ATIN method was selected to verify the correct operation of the method. The ATIN method is based on computational geometry and uses repeated Delaunay triangulation and statistical evaluation of the geometric parameters. Comparison of Msplit with a method based on different principles mitigates errors arising from similarly functioning methods belonging to the same group of filters. The choice of the ATIN method was also dictated by its established position among filtering algorithms. The method is well-known, documented, and verified and this ensures that filtering by this method provides a reliable result that can serve as a reference for comparison with the proposed new filtering method. The theoretical discussion presented in this article was verified with two practical examples. The results obtained from computation by the Msplit method with appropriate terrain models encourage more detailed theoretical and empirical tests of this method for the filtering and segmentation of ALS data-sets.

Modified GPS/Pseudolite Navigation Message

One of the issues regarding integrated GPS/pseudolite measurements is how to deliver a pseudolites position to a receiver or to post-processing software and how to manage it. This paper presents a proposed solution to this problem. The standard navigation message is modified in such way that without changing receivers (or post-processing software), the calculated position of a transmitter is fixed at a pseudolites known position. The formulae for modification of standard Ephemeris Data are also derived. This algorithm can be implemented in a transmitters firmware or a navigation data file can be modified for post-processing.

Linearization problem in pseudolite surveys

Abstract GPS augmented with pseudolites (PL), can be used in various engineering surveys. Also pseudolite—only navigation system can be designed and used in any place, even if GPS signal is not available (Kee et al. Development of indoor navigation system using asynchronous pseudolites, 1038–1045, 2000). Especially in engineering surveys, where harsh survey environment is common, pseudolites have a lot of applications. Pseudolites may be used in construction sites, open pit mines, city canyons, GPS and PL baseline processing is similar, although there are few differences that must be taken into account. One of the major issues is linearization problem. The source of the problem is neglecting second terms of Taylor series expansion in GPS baseline processing software. This problem occurs when the pseudolite is relatively close to the receiver, which is the case in PL surveys. In this paper authors presents the algorithm for GPS + PL data processing including, neglected in classical GPS only approach, second terms of Taylor series expansion. The mathematical model of adjustment problem, detailed proposal of application in baseline processing algorithms, and numerical tests are presented.

Some considerations in designing a GPS pseudolite

Some Considerations in Designing a GPS Pseudolite Pseudolites are transmitters of GPS-like signals placed on the ground. Though pseudolites are well known devices and have already been used in the project where visibility to the GNSS satellites is limited, there are still many issues that need enhancement. A prototype of a low-cost pseudolite is being designed and assembled at the University of Warmia and Mazury. This will allow for conducting tests with various codes, signals and software. The goal of the project is to apply the pseudolite as an augmentation to GNSS positioning tasks in geodetic engineering projects. Some practical considerations crucial for the design are discussed in this paper.

OUTLIERS DETECTION BY RANSAC ALGORITHM IN THE TRANSFORMATION OF 2D COORDINATE FRAMES

Over the years there have been a number of different computational methods that allow for the identification of outliers. Methods for robust estimation are known in the set of M-estimates methods (derived from the method of Maximum Likelihood Estimation) or in the set of R-estimation methods (robust estimation based on the application of some rank test). There are also algorithms that are not classified in any of these groups but these methods are also resistant to gross errors, for example, in M-split estimation. Another proposal, which can be used to detect outliers in the process of transformation of coordinates, where the coordinates of some points may be affected by gross errors, can be a method called RANSAC algorithm (Random Sample and Consensus). The authors present a study that was performed in the process of 2D transformation parameter estimation using RANSAC algorithm to detect points that have coordinates with outliers. The calculations were performed in three scenarios on the real geodetic network. Selected coordinates were burdened with simulated values of errors to confirm the efficiency of the proposed method.

Pseudolite signal tests

ABSTRACT Pseudolites are ground based GNSS signal transmitters that have already been used in the project where visibility to the GNSS satellites is limited, however there are still many issues that need enhancement. A prototype of a low-cost pseudolite is being designed and assembled at the University of Warmia and Mazury. The goal of the project is to apply the pseudolite as an augmentation to GNSS positioning tasks in geodetic engineering projects. This paper presents the results of first prototype testing in the area of code generation, carrier frequency and signal power.

The Analyzes of PDOP Factors for a Zigbee Ground – Based Augmentation Systems

Abstract This paper presents the analysis of PDOP factors for a ZigBee ground - based augmentation systems. It presents the idea of such a system followed by the results of assessment of application in Gdansk Marina. The results of the experiment show that the application of ZigBee can significantly improve PDOP value in harsh measurement environment. The analysis shows that it is possible to select an optimal location of ground-based transceiver on the basis of predicted trajectory and obstructions measured with laser scanning.