Andreas Wieser

User-level reliability monitoring in urban personal satellite-navigation

Monitoring the reliability of the obtained user position is of great importance, especially when using the global positioning system (GPS) as a standalone system. In the work presented here, we discuss reliability testing, reliability enhancement, and quality control for global navigation satellite system (GNSS) positioning. Reliability testing usually relies on statistical tests for receiver autonomous integrity monitoring (RAIM) and fault detection and exclusion (FDE). It is here extended by including an assessment of the redundancy and the geometry of the obtained user position solution. The reliability enhancement discussed here includes rejection of possible outliers, and the use of a robust estimator, namely a modified Danish method. We draw special attention to navigation applications in degraded signal-environments such as indoors where typically multiple errors occur simultaneously. The results of applying the discussed methods to high-sensitivity GPS data from an indoor experiment demonstrate that weighted estimation, FDE, and quality control yield a significant improvement in reliability and accuracy. The accuracy actually obtained was by 40% better than with equal weights and no FDE; the rms value of horizontal errors was reduced from 15 m to 9 m, and the maximum horizontal errors were largely reduced.

Short static GPS sessions: robust estimation results

Least-squares estimation (LS) yields results of low accuracy in the presentce of GPS phase-corrupting environmental conditions. We present a robust estimator that clearly identifies outlying observations caused by obstacles like diagonal cables, branches, or leaves. It performs significantly better than standard LS and signal-to-noise ratio dependent weighting if unfavorable signal distortion occurs, and is equal to LS otherwise. The estimator is realized by an iterated LS algorithm using an equivalent weight matrix. It is a generalization of the Danish Method to heterogeneous and correlated observations. The excellent peformance of the estimator for processing short static sessions is demonstrated using data obtained from an investigation of GPS signal obstruction.

Empirical Affine Reference Frame Transformations by Weighted Multivariate TLS Adjustment

In order to determine the transformation parameters between two reference frames empirically, a sufficient number of point coordinates (or possibly higher dimensional features such as, e.g., straight lines or conics) need to be observed in both systems. A proper adjustment of the observed data must take the different variances and covariances into account.

Sensor placement determination for range-difference positioning using evolutionary multi-objective optimization

Sensor placement according to different performance measures obtained from the CRLB.The proposed approach is valid for different positioning technologies.Simulations are performed for an infrared positioning system used as example.The examples obtain sensor placements using two and three objectives.We show the relevance of the multiobjective optimization analyzing the Pareto fronts. This paper focuses on the application of a decision support system based on evolutionary multi-objective optimization for deploying sensors in an indoor localization system. Our methods aim to provide the human expert who works as the sensor resource manager with a full set of Pareto efficient solutions of the sensor placement problem. In our analysis, we use five scalar performance measures as objective functions derived from the covariance matrix of the estimation, namely the trace, determinant, maximum eigenvalue, ratio of maximum and minimum eigenvalues, and the uncertainty in a given direction. We run the multi-objective genetic algorithm to optimize these objectives and obtain the Pareto fronts. The paper includes a detailed explanation of every aspect of the system and an application of the proposed decision support system to an indoor infrared positioning system. Final results show the different placement alternatives according to the objectives and the trade-off between different accuracy performance measures can be clearly seen. This approach contributes to the current state-of-the art in the fact that we point out the problems of optimizing a single accuracy measure and propose using a decision support system that provides the resource manager with a full overview of the set of Pareto efficient solutions considering several accuracy metrics. Since the manager will know all the Pareto optimal solutions before deciding the final sensor placement scheme, this method provides more information than dealing with a single function of the weighted objectives. Additionally, we are able to use this system to optimize objectives obtained from fairly complex functions. On the contrary, recent works that are referenced in this paper need to simplify the localization process to obtain tractable problem formulations.

Influence of surface reflectivity on reflectorless electronic distance measurement and terrestrial laser scanning

Abstract The uncertainty of electronic distance measurement to surfaces rather than to dedicated precisionre flectors (reflectorless EDM) is afected by the entire system comprising instrument, atmosphere and surface. The impact of the latter is significant for applications like geodetic monitoring, high-precision surface modelling or laser scanner self-calibration. Nevertheless, it has not yet received sufficient attention and is not well understood. We have carried out an experimental investigation of the impact of surface reflectivity on the distance measurements of a terrestrial laser scanner. The investigation helps to clarify (i)whether variations of reflectivity cause systematic deviations of reflectorless EDM, and (ii) if so, whether it is possible and worth modelling these deviations. The results show that differences in reflectivity may actually cause systematic deviations of a few mm with diffusely re- flecting surfaces and even more with directionally reflecting ones. Using abivariate quadratic polynomial we were able to approximate these deviations as a function of measured distance and measured signal strength alone. Using this approximation to predict corrections, the deviations of the measurements could be reduced by about 70% in our experiment.We conclude that there is a systematic effect of surface reflectivity (or equivalently received signal strength) on the distance measurement and that it is possible to model and predict this effect. Integration into laser scanner calibration models may be beneficial for high precision applications. The results may apply to a broad range of instruments, not only to the specific laser scanner used herein.

SIGMA-F: Variances of GPS Observations Determined by a Fuzzy System

The determination of a realistic variance model is still an important issue in GPS data processing. An a-priori model of the variances of the double differenced phase observations is set up using their measured signal-to-noise ratios (C/N0). We present an adaptive variance model for GPS carrier phase observations (SIGMA-F) to be used with least squares estimation (LS). It is based on a fuzzy system which combines robust estimation and data quality assessment.

Infrared local positioning system using phase differences

In this paper an infrared (IR) indoor local positioning system (LPS) is presented. The most relevant low level design aspects are addressed. Using sinusoidal amplitude-modulation (AM) of an infrared carrier, differential distances between a mobile emitter, the position of which is to be obtained, and fixed receivers are measured. The system may yield accuracies at the level of a few cm and addresses applications for which the increasingly available wireless technologies and smart phone sensors are not sufficient. Such applications comprise e.g., positioning mobile-robots in a manufacturing plant or positioning tools on a construction site. The proposed system works with an IR LED emitter, with a wide emitting angle, resulting in a less complex system than a laser-based one, but requiring an elaborate sensor design in order to have a sufficiently high signal-to-noise ratio (SNR) for successful demodulation. A detailed description of the basic locating cells (BLC), composed of five receivers is given as well as a study including all the blocks that comprise the system: emitter and detector devices, sensor electronics, phase measuring electronic system and hyperbolic trilateration module. All these blocks are modelled numerically and their relevant parameters are discussed with respect to their effect on the position error. The numerical analysis provides a method to evaluate the system as a whole. The choice of parameter values is a trade-off between accuracy, coverage and admissible dynamics of the mobile robot, or - equivalently - between SNR, field of view and real time response. Multipath is one of the biggest challenges for current indoor positioning systems requiring line-of-sight observations. The proposed system achieves multipath mitigation through an additional spread spectrum modulation of the sinusoidal AM signal, in analogy to the modulation of the microwave carrier with GNSS. Finally, a numerical analysis and an experiment using a prototypical BLC are summarized. They indicate that the system achieves a precision of 5 cm (2σ) for the coordinates in a fixed local coordinate frame.

Multipath mitigation for a phase-based infrared ranging system applied to indoor positioning

A new measuring architecture for phase-based infrared ranging applied to indoor positioning is presented. The motivation to develop this proposal was to reduce the critical effect of multipath interferences on the differential distances estimated by the ranging system. The multipath mitigation feature of the proposed system is based on applying a spread spectrum modulation on the emitted signal so that the line-of-sight component reaching the receivers can be discriminated from the non-line-of-sight components by applying a selective coherent demodulation. An overview of the system architecture is provided, together with the first approach to the model of the demodulation process and its validation. The conclusions obtained from the study of the proposal are used to provide preliminary results of the mitigation capabilities of the system, and to analyze the key issues involved in its implementation. The results show that the effectiveness of the proposal is strongly related with the infrared link bandwidth. Mitigation levels above 50% for multipath 4.5 meters longer than the direct path are reached if the infrared link bandwidth is higher than 200 MHz.

Fusion of wireless and non-contact technologies for the dynamic testing of a historic RC bridge

In this paper, a dynamic testing and corresponding signal processing methodology is presented for condition assessment of bridge structures, via use of a diverse and potentially dense grid of low-cost and easily deployable monitoring technologies. In particular, wireless and non-contact sensors are simultaneously deployed on a historic reinforced concrete bridge in order to record acceleration and dynamic displacement response, under operational loading conditions. An innovative monitoring approach is proposed on both the hardware (sensors) and software (algorithmic) front, in which an effective data fusion procedure is adopted for fusing these alternative technologies for vibration-based monitoring in terms of both acceleration and displacement information. The demonstrated efficacy of the fusion procedure on the case-study of an actual operating system, the historic Brivio bridge, reveals the potential of this approach within the context of structural monitoring, where acquisition of heterogeneous information certainly proves advantageous.

Evolutionary optimization of sensor deployment for an indoor positioning system with unknown number of anchors

We present an evolutionary multi-objective optimization method for sensor deployment applied to an indoor positioning system with range-difference measurements. Stationary sensors at known locations are used to obtain the position of a moving emitter. Coverage and accuracy of the positioning system depend on the number and location of the sensors for a given indoor space (floor plan) and on the properties of the system. The proposed method allows finding an optimum number and spatial distribution of the sensors automatically using constraints and different optimization criteria. We use the usual genetic operators for crossover and mutation and we have also introduced the possibility of deleting or adding a sensor in the sensor distribution corresponding to the offspring population. The method is applied to an infrared indoor positioning system showing two examples of sensor deployment with three and four objectives, respectively.