ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Statistical Change Detection: Application to Global Navigation Satellite Systems

4 September 2018, 10:30 – 10:50

Abstract

Submitted by
Daniel Egea-Roca
Authors
Daniel Egea-Roca (Universitat Autònoma de Barcelona (UAB)), Gonzalo Seco-Granados (Universitat Autònoma de Barcelona (UAB)), José A. López-Salcedo (Universitat Autònoma de Barcelona (UAB))
Abstract
The problem of detecting sudden statistical changes has many important applications such as quality control, signal segmentation, on-line monitoring of safety-critical infrastructures or detection of signals in radar and sonar. This kind of detection lies in the field of the so-called statistical change detection (SCD), including both quickest change detection (QCD) and transient change detection (TCD).

QCD is particularly of interest for applications in which the statistical change will remain forever once it appears. This is the case for instance when analysing the quality of the product of an industrial process. In this case, when the process is miss-behaving, the quality of the product will be degraded as long as the problem is not solved. QCD has been extensively studied and applied into a wide range of applications since the 1950s. The goal of QCD is to detect the statistical change as soon as possible. The optimality criterion is to minimize the detection delay.

In contrast, TCD deals with the detection of changes with a finite duration. So, the goal in this case is to minimize the probability of detecting the change within a given period of time. For instance, in safety-critical applications we would like to detect any issue of the system before the end-user gets hurt. This may be the case of autonomous navigation when the navigation system fails. If we do not detect the failure within a short period of time the safety of the end-user might be in danger. Unfortunately, the related literature for the fundamentals of TCD is scarce because it is a field still under development. Nevertheless, in the last years some contributions have appeared shedding some light on the optimal solution for the TCD problem. This has raised interest of many fields to consider the framework of TCD. This is the case for instance of navigation, drinking water quality or cyber attacks monitoring.

Another sector that can benefit from the advances on SCD is the global navigation satellite systems (GNSSs). GNSSs are becoming an essential tool for many critical sectors in our modern society like transportation, communications or timing for power grid control or bank transactions. Indeed, as reported by the 2015 GSA market report, by 2020 GNSS will provide revenues of nearly 50 billions of Euro worldwide. As a matter of fact, the disruption or miss-behaviour of GNSS services can have a high economic impact and cause a major setback worldwide. For this reason, it is of paramount importance to promptly detect any possible anomaly or misleading behaviour that could be endangering the received GNSS signal.

Based on the above considerations, the goal of our presentation is to show the audience an overview of the detection theory with special emphasis on SCD. To see the practical application of the theoretical concepts of SCD we show its application to the GNSS field. The idea is to show the audience how to apply SCD to a particular detection problem so that they can get an idea of how to apply SCD to other problems.
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