Measurements consistency based Receiver Autonomous Integrity Monitoring (RAIM) is the main technique for monitoring the integrity of Global Satellite Navigation Systems (GNSS) at the user level. Existing RAIM algorithms utilize two tests, in the position domain a test for RAIM availability and in the measurement domain a test for failure detection. These tests involve the computation of three parameters: test statistic, decision threshold and protection level. The test statistic is based on the actual measurements in the form of the Sum of the Squared Errors (SSE). The decision threshold is chosen on the basis of the statistical characteristics of the SSE including the assumption that the errors are normally distributed. However, in practice residual error distributions exhibit heavier tails than predicted by the Gaussian model. Therefore, this paper challenges the normality assumption of the residual navigation errors in three ways. First, real data are used to assess its impact on the traditional RAIM algorithm. Second, Extreme Value Theory (EVT) is applied to the tails and the Generalized Extreme Value (GEV) distribution is derived to capture residual navigation errors. Third, the performance of the traditional RAIM approach is compared with that employing the GEV distribution. The results demonstrate that the GEV model is a more accurate representation of the distribution of residual navigation errors than the conventional Gaussian model and should be used in the development of integrity monitoring algorithms.
The demand for air travel continues to grow rapidly, and by 2010, air traffic in Europe is expected to be twice the 1990 level. This increase in air traffic may adversely affect safety if appropriate measures are not taken. Regulators and Air Navigation Service Providers (ANSPs) analyze incidents to identify ways to prevent them from happening again. Incidents are rare events in airspace, and this poses problems with robust statistical testing and trend analysis. Aviation safety analysis uses the Poisson distribution where possible, but doubts remain as to its appropriateness. Incident data from ANSP were analyzed over 17 years in a logical quantitative manner using extreme value theory (EVT), a method that uses the limited amount of information available on incidents and defines a distribution that can be used to make statistical inferences. EVT has had considerable use in other fields but little in aviation. A statistical analysis and validation framework is outlined and used to test the data using Poisson, negative binomial, and EVT. The goodness-of-fit tests, as well as other statistical tests, indicate that by far the best fit of the data is achieved using EVT. Further analysis using EVT shows its efficacy as a tool for monitoring and predicting incidents, based on statistical hypothesis and the use of quantile information.
The operation of Unmanned Aerial Systems (UAS) is widely recognised to be limited globally by challenges associated with gaining regulatory approval for flight Beyond Visual Line of Sight (BVLOS) from the UAS Remote Pilot. This challenge extends from unmanned aircraft flights having to follow the same 'see and avoid' regulatory principles with respect to collision avoidance as for manned aircraft. Due to the technical challenges of UAS and Remote Pilots being adequately informed of potential traffic threats, this requirement effectively prohibits BVLOS UAS flight in uncontrolled airspace, unless a specific UAS operational airspace is segregated from manned aviation traffic, often achieved by use of a Temporary Danger Area (TDA) or other spatial arrangements.The UK Civilian Aviation Authority (CAA) has defined a Detect and Avoid (DAA) framework for operators of UAS to follow in order to demonstrate effective collision avoidance capability, and hence the ability to satisfy the 'see and avoid' requirement. The National BVLOS Experimentation Corridor (NBEC) is an initiative to create a drone experimentation facility that incorporates a range of surveillance and navigation information sources, including radars, data fusion, and operational procedures in order to demonstrate a capable DAA System. The NBEC is part located within an active Airodrome Traffic Zone (ATZ) at Cranfield Airport, which further creates the opportunity to develop and test systems and procedures together with an operational Air Traffic Control (ATC) unit. This allows for manned and unmanned traffic to be integrated from both systems and procedural perspectives inside segregated airspace in a first stage, and then subsequently transiting to/from non-segregated airspace. The NBEC provides the environment in which a number of challenges can be addressed.
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