Daniel Egea-Roca

On the use of quickest detection theory for signal integrity monitoring in single-antenna GNSS receivers

Local threats such as radio frequency interference, multi-path and spoofing have attracted the attention of many researchers in the past years thus leading to a myriad of contributions in the field of threat detection. As a matter of fact, the current state of the art relies on classical detection techniques, which are not well suited for threat detection. In this paper, we take a leap forward in local threat detection, presenting a quickest detection framework for threat detection. The aim is to detect the presence of local threats as soon as possible in order to improve the integrity of GNSS receivers.

A finite moving average test for transient change detection in GNSS signal strength monitoring

Due to the increasing interest in Global Navigation Satellite Systems (GNSSs) for safety-critical applications, one of the major challenges to be solved is the provision of integrity to urban environments. In the past years, it has been noted that to do so, the integrity of the received signal must be analyzed with the aim of detecting any local effect disturbing the GNSS signal. Moreover, the detection of such disturbing effects must be done with a bounded delay. This is desirable because the presence of any local effect may cause large position errors. This work addresses the signal integrity problem as a transient change detection problem by proposing a stopping time based on a finite moving average. The statistical performance of this stopping time is investigated and compared, in the context of multipath detection relying on C/N0 monitoring, to different methods available in the literature. Numerical results are presented in order to assess their performance.

Inhomogeneous quadratic tests in transient signal detection: Closed-form upper bounds and application in GNSS

This paper focuses on inhomogeneous quadratic tests, which involve the sum of a dependent non-central chisquare with a Gaussian random variable. Unfortunately, no closed-form expression is available for the statistical di stribution of the resulting random variable, thus hindering the analytical characterization of these tests in terms of probability of detection and probability of false alarm. In order to circumvent this limitation, two closed-form approximations are proposed i n this work based on results from Edgeworth series expansions and Extreme Value Theory (EVT). The use of these approximations is shown through a specific case of study in the context of integrity transient detection for Global Navigation Satellite Systems (GNSS). Numerical results are provided to assess the goodne ss of the proposed approximations, and to highlight their interest in real life applications.Abstract This paper focuses on transient signal detection based on inhomogeneous quadratic tests, which involve the sum of a dependent non-central chi-square with a Gaussian random variable. These tests arise in many signal processing-related problems in biomedicine, finance or engineering, where sudden changes in the magnitude under analysis need to be promptly detected. Unfortunately, no closed-form expression is available for the density of inhomogeneous quadratic tests, which poses some concerns and limitations in their practical implementation. In particular, when trying to assess their detection performance in terms of probability of detection and probability of false alarm. In order to circumvent this limitation, two closed-form approximations based on results from Edgeworth series expansions and Extreme Value Theory (EVT) are proposed in this work. The use of these approximations is shown through a specific case of study in the context of transient detection for signal quality monitoring in Global Navigation Satellite Systems (GNSS). Numerical results are provided to assess the goodness of the proposed approximations, and to highlight their interest in real life applications.

Transient change detection for LOS and NLOS discrimination at GNSS signal processing level

Multipath is one of the major impairments threatening the integrity of terrestrial Global Navigation Satellite Systems (GNSS). For this reason, multipath mitigation has attracted the attention of many researchers, thus leading to outstanding contributions in the past years. These techniques are useful when the Line of Sight (LOS) is not obstructed. Otherwise, they are not applicable, and thus we should use alternatives exploiting Non-Line of Sight (NLOS) conditions. It is for this reason that the discrimination between LOS and NLOS situations may be beneficial for integrity in terrestrial GNSS applications. Several contributions for doing so have been proposed, but relying on external aid that is not often available in mass-market receivers. In this paper, we take a leap forward by adopting a transient change detection framework for discriminating between LOS and NLOS conditions. This is done by using the Slope Asymmetry Metric (SAM), which can be calculated within the GNSS receiver at the signal processing level, without using external aid, thus adequate for mass-market receivers. Numerical results will be used to validate the proposed solution, contributing to improve the GNSS integrity in terrestrial environments.

Quickest Detection Framework for Signal Integrity Monitoring in Low-Cost GNSS Receivers

Recently, there has been an increasing interest in GNSS-based safety and liability applications. These applications, which are often associated to urban environments or in general to vehicular applications, have very stringent requirements in terms of accuracy, continuity and integrity of the provided position solution. In this paper, we present simple quickest threat detectors for being used in low-cost GNSS receivers. The aim is to detect the presence of interference and multipath as soon as posible in order to improve GNSS integrity.