Journal of Surveying Engineering

Global navigation satellite system (GNSS) observations have been shown to be physically correlated. Disregarding the physical correlations in a variance-covariance matrix (VCM) will lead to adverse impacts on GNSS applications. Typically, physical correlations have three types in a fully populated VCM: spatial, cross, and temporal correlations. However, such a fully populated VCM cannot be easily estimated and inverted, especially in real-time kinematic (RTK) positioning. The authors propose an efficient approximation approach for processing these physical correlations. This method appropriately considers the significant covariance elements and efficiently transforms the time-dependent VCM to a time-independent block diagonal matrix. As an example, 10 data sets of BeiDou code and phase observations with different baseline lengths and receivers were collected. The results showed that this proposed method had fewer covariance elements to be estimated, thus decreasing the number of unknowns when using (co)variance component estimation (VCE). In addition, the proposed method had lower computation burden than the multiple-epoch method. For instance, the computation efficiency was increased by more than 50% in the case of the 60-epoch data window. It can also provide more realistic baseline solutions and precisions compared with the traditional single-epoch method.

There are two different but equivalent forms to solve a least squares (LS) adjustment problem, namely batch LS (BLS) and recursive LS (RLS). The batch form is usually not an appropriate approach when measurements are sequentially received over time. When the unknown parameters are constant and hence converge slowly over time to their final estimates, the RLS algorithm can be used. For time-varying parameters, the Kalman filter (KF) algorithm can be used. To properly reflect the time variations of the parameters, this method requires the appropriate choice of filter parameters, and hence tuning is an important stage. In some geodetic applications, as time progresses, new observations and parameters are added to the system of equations. For such applications, an RLS algorithm with additive parameters can be developed. The method differs from the KF in the sense that there is no need to define and manipulate the dynamic model and the noise structure of the parameters involved. The implementation of the method in both linear and nonlinear models is explained. As an application of the proposed method, the algorithm is implemented in the global positioning system (GPS) precise point positioning (PPP), either in static or kinematic mode. Generally, the PPP adjustment is performed via a sequential filter: either the LS sequential filter, or the discrete KF. We propose an efficient alternative based on the RLS with additive parameters, which is applicable to PPP. The performance of the method is investigated with regard to the repeatability and accuracy using a few 24-h data sets of four International GNSS Service (IGS) stations. Finally, the efficacy of the proposed method is investigated in the kinematic mode using two experiments: a stationary experiment and a real kinematic test. The results indicate that the proposed method can be employed as an appropriate alternative to the KF algorithm.

This study presents an automatic method for horizontal curve identification and measurement using a mobile mapping system (MMS) with consideration of the impacts of vehicle wandering on the measurement. The hierarchical cluster model combined with the linear fit analysis achieved the automatic point of curvature (PC) and point of tangent (PT) station detection. The arc length method and chord offset method combined with the vehicle trajectory data were utilized for curve radius calculation. Finally, according to the adjacency patterns of the single curves, the types of curve were detected. A case study on a 9.756-km road section is provided, and on the test section, 21 single curves were detected and measured. Among them, 12 single curved segments were the simple curves, and nine single curved segments formed four reverse curves. A validation test based on the field measurement was conducted. The test results showed that the average errors for automatic PC/PT station detection, curve length measurement, and curve radius measurement were 2.15, 3.07, and 4.93%, respectively, which demonstrated that the presented method had a high accuracy for horizontal curve measurement. The significance of the proposed method was threefold. First, it solved the common problems of vehicle wandering on mobile survey. Second, it detected the curve types and the PC station of two adjacent single curves. Third, it had high accuracy, effectiveness, and automaticity, and can be used for roadway survey at network level.

In recent years, global positioning system (GPS) has been widely used for the measurement of deflections of bridges. However, due to multipath and satellite signal obstructions caused by towers, cables, and passing vehicles, the reliability of deformation monitoring with GPS is still a problem. Recent research with respect to multi–global navigation satellite system (multi-GNSS) technology, though, has enhanced satellite visibility and availability for positioning, navigation, and timing (PNT) for users. Its benefits involving application in bridge monitoring are still rarely studied. In this paper, we propose a composite strategy where integrated GPS and BeiDou navigation satellite system (BDS) dual-frequency, carrier-phase data processing is carried out to improve the reliability of bridge monitoring with GNSS measurements. In addition, signal-to-noise ratio (SNR)–based stochastic model and postfit residual editing strategies are utilized to enhance the reliability further. In a group of fixed-point experiments, improvements of 20–30% in precision were achieved with the integrated GPS and BDS compared to GPS-only results. Based on the real GPS and BDS measurements collected on the Baishazhou Yangtze River Bridge in China, we assessed the performance of the proposed method. In the vibration experiment, no apparent effects on natural frequency identification were found by introducing BDS into the solution in an ideal observation environment. However, the combined GPS and BDS results seemed to be much more promising, with lower background noise. Meanwhile, the integrated GPS and BDS data processing with postfit residual editing and SNR-based stochastic model strategies effectively managed satellite signal obstruction and the influence of multipath effect to attain reliable dynamic deformation-monitoring information for bridges.

The method of least squares is widely used to fit data to a mathematical model, and the model is generally formulated as a Gauss-Markov model. Constraints on the parameters lead to a constrained adjustment of the observations. The validity of such a model can be tested. However, testing a model uniformly and if necessary, simultaneously, for both biased observations and invalid constraints has not yet been described; nor has a quality description of such tests yet been described. Here a simple, general procedure to resolve this is developed. It includes the computation of minimal detectable biases for both observations and constraints. Methods to compute the test statistic in the presence of singular covariance matrices (inevitable in the proposed procedure) and rank deficient coefficient matrices have not been published before. In this paper, an overview is given of six such methods. Constraints can describe deterministic, unmeasured model elements. In geodetic deformation analysis, for example, the stability of points can be formulated as constraints, tested, and provided with a quantification of the minimal detectable deformation. The analysis does not require the points that constitute the geodetic datum to be stable. Two comprehensive examples illustrate the use in geodetic deformation analysis.

The horizontal alignment geometric parameter is an important basis for road management, safety analysis, and railway maintenance. Therefore, the identification of horizontal curve features is of great importance. Least squares is most common method currently used to estimate the parameter. By comparing different approaches of least squares, this paper outlines the drawbacks of algebraic fitting and presents an analysis of the connection and limitation of other forms of least squares. After showing the presence of correlated noise in sampled data points and based on the maximum likelihood estimation theory, the paper shows the derivation of a generic curve-fitting method, which was also applied to circular curve fitting. Experimental results showed that the proposed fitting method was capable of estimating circular curve parameters and the precision of them in all circumstances by specifying stochastic models. The geometric meaning of the fitting results was connected with the corresponding stochastic models. The estimated parameters varied by stochastic models, leading to different alignment identifications. An in-depth understanding of curve fitting was provided that explains that only the proper stochastic model could meet the maximum likelihood principle, and thus, achieved the best fit.

Several precise point positioning or relative positioning services are available online for postprocessing static global navigation satellite system (GNSS) data collected on a single mark. The accuracy of five services (OPUS-S, AUSPOS, CSRS-PPP, GAPS, TrimbleRTX) were compared by processing the same 490 static GNSS files of varying session duration (from 2 to 10 h) on six passive marks in minimal or moderate multipathing environments. First, only Global Positioning System (GPS) observables at a 30-s logging rate were tested using each service. Then, the effects of including observables from Russia’s GNSS (i.e., GLONASS) were investigated using TrimbleRTX and CSRS-PPP, and the accuracy of processing data at faster logging rates were evaluated using TrimbleRTX. The results from each service were differenced with coordinates derived from a high-accuracy campaign-style static GNSS survey. Increasing the logging rate from 30 to 10 s did not significantly reduce the root-mean-square error (RMS) of the differences. However, adding GLONASS observables significantly reduced the horizontal RMS by an average of 17.1% and 36.7% at sites in minimal and moderate multipathing environments, respectively.

When it comes to the safe design and operation of highways, sight distance is of utmost importance. The estimation of sight distance must be performed taking the three-dimensional (3D) nature of roadways and related features into account. Horizontal curves and crest vertical curves were the common sight restrictions considered in highway design. However, overhanging features may also affect sight distance. This paper presents a 3D virtual model for evaluating sight distance on sites where overpass structures restrict sight distance and for detecting sight-distance-related issues. The procedure and inputs for the computation of sight distance are described as are the results, which were validated and applied to a case study of an in-service highway underpass. Stopping sight distance and passing sight distance were evaluated for a section of highway with specific sight-distance characteristics of overpasses. The effect of the observer and target heights on sight distance for underpasses proved the opposite of those on horizontal curves and crests. Near an overpass, the heights should be switched from those used on curves and crests to evaluate stopping and passing sight distance according to operational and safety criteria. Finally, the currently existing passing zones were evaluated by means of the results obtained, revealing possible deficiencies in the establishment of passing zones.

An improved leveling method based on an updated definition of leveling is proposed for application in civil engineering projects. The approach is defined as the measurement of the elevation difference between the elevation of the sight line at level station Z_L and the benchmark height Z_B, where the leveling staff is placed. Under the updated leveling definition, sight line length needs to be measured (modern instruments have this function), but the line lengths between the level station and leveling benchmarks do not have to be the same. The improved approach exhibits four advantages: It eliminates the impact of a possible sight line inclination caused by inaccurate instrument adjustment and additional systematic factors that affect the sight line inclination; it reduces the required number of level stations needed for a job, thereby reducing the time required to conduct measurements; it eliminates the need to find locations for the instrument station that have equal sight line lengths, that is, the instrument can be set up in a location where many leveling benchmarks can be seen; and by eliminating the frequent changes in the position of the level instrument, the total measurement cost is reduced.