With more satellite systems becoming available there is currently a need for Receiver Autonomous Integrity Monitoring (RAIM) to exclude multiple outliers. While the single outlier test can be applied iteratively, in the field of statistics robust methods are preferred when multiple outliers exist. This study compares the outlier test and numerous robust methods with simulated GPS measurements to identify which methods have the greatest ability to correctly exclude outliers. It was found that no method could correctly exclude outliers 100% of the time. However, for a single outlier the outlier test achieved the highest rates of correct exclusion followed by the MM-estimator and the L 1 -norm. As the number of outliers increased MM-estimators and the L 1 -norm obtained the highest rates of normal exclusion, which were up to ten percent higher than the outlier test. K E Y W O R D S 1. RAIM. 2. Outliers. 3. Robust. 4. Integrity.
With the development of GPS, GLONASS, Galileo, Compass, QZSS and the IRNSS, there has been growing interest in the development of system independent receivers. However, one of the problems encountered in system independent receivers is in the different time systems employed by each of the satellite navigation systems. To overcome this problem it has become a standard practice to solve for the time differences within the receiver's navigation solution via a combination of receiver clock corrections and/or time offsets. While this technique overcomes the problem of the different time systems, it is at the cost of a satellite from each additional time system. Despite this, the numerous studies that combine multiple satellite navigation systems this way have still found that there are significant benefits in improved accuracy, integrity, continuity and availability. To enhance interoperability though satellite navigation system providers are intending to measure and transmit the time offsets to other time systems. The subsequent use of these time offsets will provide a more accurate navigation solution than without them. However, the problem with using the time offsets is that they pose an additional integrity risk because they are also potential sources of faults. However, with the use of the time offsets for multiple constellation solution, a proper Receiver Autonomous Integrity Monitoring method has not been developed. Thus, mathematical models to account for the time differences with and without the time offsets are presented in this paper. Furthermore, the model that incorporates the time offset allows the application of Receiver Autonomous Integrity Monitoring to detect the presence of any faults within the time offsets. The reliability of the linear models is then compared using GPS and GLONASS geometry in terms of the Minimal Detectable Biases, Protection Levels and the correlation coefficients. The results of this analysis indicate that a more reliable solution can be obtained with the time offsets because they are additional measurements.
In Global Navigation Satellite System (GNSS) positioning, it is standard practice to apply the Fault Detection and Exclusion (FDE) procedure iteratively, in order to exclude all faulty measurements and then ensure reliable positioning results. Since it is often only necessary to consider a single fault in a Receiver Autonomous Integrity Monitoring (RAIM) procedure, it would be ideal if a fault could be correctly identified. Thus, fault detection does not need to be applied in an iterative sense. One way of evaluating whether fault detection needs to be reapplied is to determine the probability of a wrong exclusion. To date, however, limited progress has been made in evaluating such probabilities. In this paper the relationships between different parameters are analysed in terms of the probability of correct and incorrect identification. Using this knowledge, a practical strategy for incorporating the probability of a wrong exclusion into the FDE procedure is developed. The theoretical findings are then demonstrated using a GPS single point positioning example.
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In an effort to supplement the available satelite-based positioning technology and extend such high level positioning capability to GPS-denied environments, a method of vision-based positioning with the use of single camera and newly defined 3D maps is proposed. Besides, only natural landmarks are required in the proposed method. Absolute position and orientation information can be provided in six degree of freedom. Our work here is to address the accuracy and reliability concerns of such a vision-based navigation system. The main contribution will be the newly defined 3D map and the adoption of photogrammetric 6DOF pose estimation method to improve positioning accuracy. Dilution of Precisions (DOPs) are introduced to evaluate positioning precision within the vision-based positioning domain. Quality control strategies are also applied to detect outliers in the observation and strengthen system reliability
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