GNSS Vulnerabilities and Existing Solutions:A Review of the Literature

This literature review paper focuses on existing vulnerabilities associated with global navigation satellite systems (GNSSs). With respect to the civilian/non encrypted GNSSs, they are employed for proving positioning, navigation and timing (PNT) solutions across a wide range of industries. Some of these include electric power grids, stock exchange systems, cellular communications, agriculture, unmanned aerial systems and intelligent transportation systems. In this survey paper, physical degradations, existing threats and solutions adopted in academia and industry are presented. In regards to GNSS threats, jamming and spoofing attacks as well as detection techniques adopted in the literature are surveyed and summarized. Also discussed are multipath propagation in GNSS and non line-of-sight (NLoS) detection techniques. The review also identifies and discusses open research areas and techniques which can be investigated for the purpose of enhancing the robustness of GNSS

Review on Sparse-Based Multipath Estimation and Mitigation: Intense Solution to Counteract the Effects in Software GPS Receivers

Multipath is the major concern in GPS receivers that fade the actual GPS signal causes positioning error up to 10 m so special care need to be taken to mitigate the multipath effects. Numerous methods like hardware based antenna arrays technique, receiver based narrow correlator receiver, double -delta discriminator, Adaptive Multipath Estimator, Wavelet Transformation and Particle filter, Kalman filter based post receiver methods etc. used to resolve the problem. But some of the methods can only reduce code multipath error but not effective in eliminating carrier multipath error. Most of these techniques are based on the assumption that the Line-of-Sight (LOS) signal is stronger than the Non-Line of-Sight (NLOS) signals. However, in the scenarios where the LOS signal is weaker than the composite multipath signal, this approach may result in a bias in code tracking. In this chapter, different types of multipath mitigation and its limitation are described. The recent development in sparse signal processing based blind channel estimation is investigated to compensate the multipath error. The Rayleigh and Rician fading model with different multipath parameters are simulated to test the urban scenario. The inverse problem of finding the GPS signal is addressed based on the deconvolution approach. To solve linear inverse problems, the suitable kind of appropriate objective function has been formulated to find the signal of interest. By exploiting this methods, the signal is observed and the carrier and code tracking loop parameters are computed with minimal error

3D LiDAR Aided GNSS NLOS Mitigation for Reliable GNSS-RTK Positioning in Urban Canyons

GNSS and LiDAR odometry are complementary as they provide absolute and relative positioning, respectively. Their integration in a loosely-coupled manner is straightforward but is challenged in urban canyons due to the GNSS signal reflections. Recent proposed 3D LiDAR-aided (3DLA) GNSS methods employ the point cloud map to identify the non-line-of-sight (NLOS) reception of GNSS signals. This facilitates the GNSS receiver to obtain improved urban positioning but not achieve a sub-meter level. GNSS real-time kinematics (RTK) uses carrier phase measurements to obtain decimeter-level positioning. In urban areas, the GNSS RTK is not only challenged by multipath and NLOS-affected measurement but also suffers from signal blockage by the building. The latter will impose a challenge in solving the ambiguity within the carrier phase measurements. In the other words, the model observability of the ambiguity resolution (AR) is greatly decreased. This paper proposes to generate virtual satellite (VS) measurements using the selected LiDAR landmarks from the accumulated 3D point cloud maps (PCM). These LiDAR-PCM-made VS measurements are tightly-coupled with GNSS pseudorange and carrier phase measurements. Thus, the VS measurements can provide complementary constraints, meaning providing low-elevation-angle measurements in the across-street directions. The implementation is done using factor graph optimization to solve an accurate float solution of the ambiguity before it is fed into LAMBDA. The effectiveness of the proposed method has been validated by the evaluation conducted on our recently open-sourced challenging dataset, UrbanNav. The result shows the fix rate of the proposed 3DLA GNSS RTK is about 30% while the conventional GNSS-RTK only achieves about 14%. In addition, the proposed method achieves sub-meter positioning accuracy in most of the data collected in challenging urban areas

Novel multipath mitigation methods using a dual-polarization antenna

There are many methods for mitigating GNSS multipath errors. However, none of them completely eliminate the effects of multipath or suit all GNSS applications. A new class of multipath mitigation methods exploit new dual-polarization antenna technology. GNSS signals received direct from the satellites have right-handed circular polarization (RHCP), whereas (singly) reflected signals have left-handed circular polarization (LHCP) or an elliptical polarization that may be expressed as the sum of RHCP and LHCP components. Conventional GNSS user antennas are more sensitive to signals with RHCP, attenuating LHCP signals and reducing, but not eliminating, the multipath errors in the receiver. An antenna with the opposite polarization sensitivity will attenuate the direct signals more than the reflected signals. This can be used to characterizing the reflected signals and thus mitigate the effects of multipath interference.Experimental work using an Antcom dual-polarization antenna and dual geodetic receivers is presented. This verifies that carrier power to noise density, C/N-0, measurements obtained by separately correlating the RHCP and LHCP antenna outputs can be used to distinguish between a low-multipath and moderate-multipath environment. This may be used as the basis of a multipath detection technique.Three different multipath mitigation techniques that use a dual-polarization antenna are proposed. Measurement weighting estimates the code and carrier multipath error standard deviation from the RHCP-LHCP C/N-0 difference and elevation angle. This is used by the navigation processor to discard and reweight measurements. Range-domain multipath correction, uses the pseudo-range, carrier-phase and C/N-0 differences between the outputs of RHCP and LHCP receiver tracking channels, together with antenna calibration data, to estimate corrections to the code and carrier measurements. In tracking-domain multipath mitigation, the RHCP and LHCP correlator outputs are input to common acquisition and tracking algorithms which attempt to separate the direct line of sight and reflected signalsThe design of a novel dual-input GNSS front end, based on direct RF sampling, is presented This will be used, in conjunction with a software GNSS receiver, for future development and testing of multipath mitigation using a dual-polarization antenna

A hybrid optical-wireless network for decimetre-level terrestrial positioning

Global navigation satellite systems (GNSS) are widely used for navigation and time distribution, features indispensable for critical infrastructure such as mobile communication networks, as well as emerging technologies like automated driving and sustainable energy grids. While GNSS can provide centimetre-level precision, GNSS receivers are prone to many-metre errors due to multipath propagation and obstructed view of the sky, which occur especially in urban areas where accurate positioning is needed most. Moreover, the vulnerabilities of GNSS, combined with the lack of a back-up system, pose a severe risk to GNSS-dependent technologies. Here, we demonstrate a terrestrial positioning system which is independent of GNSS and offers superior performance through a constellation of radio transmitters, connected and time-synchronised at the sub-nanosecond level through a fibre-optic Ethernet network. Employing optical and wireless transmission schemes similar to those encountered in mobile communication networks, and exploiting spectrally efficient virtual wideband signals, the detrimental effects of multipath propagation are mitigated, thus enabling robust decimetre-level positioning and sub-nanosecond timing in a multipath-prone outdoor environment. This work provides a glimpse of a future in which telecommunication networks provide not only connectivity, but also GNSS-independent timing and positioning services with unprecedented accuracy and reliability.Comment: 38 pages, 9 figures, 3 table

Effects of Site-Dependent Errors on the Accuracy of C/A Code DGPS Positioning

Several differential GPS processing techniques can be used; for instance, single differencing and double differencing, which are popular in practice. Irrespective of the DGPS processing technique used, the ultimate accuracy of the user-location depends on the existence of non-common or site-dependent errors, which occur at the points of observation and the reference. Of these, the most common and dominant site-dependent error is the multipath. Therefore, this research evaluates the effects of site-dependent errors on C/A code differential GPS correction accuracies by providing special emphasis on the multipath error. For the analyses, four segments of about 24-hour continuous static C/A code based DGPS observations were conducted at three precisely known ground stations and four different multipath environments were introduced by placing three different types of artificial signal reflectors at one of the observation stations. By using the known GPS receiver-reflector configuration, pseudo-range multipath was precisely calculated for each observation segment. C/A code DGPS positioning accuracies before and after multipath mitigation were presented by evaluating the effect of the most dominant site-dependent error, i.e., multipath, on C/A code DGPS correction accuracies

Integrity Monitoring Using ARAIM Algorithm in Urban Environment

Aviation is one of the earliest application of the Global Navigation Satellite System (GNSS). Since the early days of the Global Positioning System (GPS), satellite navigation has been an essential part of the aviation industry. Being a particular mean of transport, which usually involves a large number of human lives, civil aviation always requires a high level of reliability from the navigation system. Such requirement brings about the concept of integrity, which concerns about the consistency and reliability of a navigation system, is defined as the capability of the system to provide timely warning when it should not be used for navigation. The concept of integrity allows the standardization of guidance systems' performance, with the utmost purpose of keeping safety for every flight. The concept of integrity has gained interests in other GNSS applications as well, especially in those that also require high reliability from the navigation solution, such as Intelligent Transport System (ITS), railways. This leads to the necessity to adapt the integrity monitoring techniques, in particular the Receiver Autonomous Integrity Monitoring (RAIM) algorithms, to use in working conditions other than the typical airport areas, such as urban environment. As a matter of fact, adaptation of RAIM algorithms to urban environment requires a throughout analysis of the environmental difference of the working condition as well as the requirement of the intended applications. This thesis focuses on developing a Kalman filter-based Advanced RAIM (ARAIM) algorithm for urban environment, which is an adaptation of the conventional ARAIM algorithm for civil aviation. ARAIM algorithm is considered the next generation of RAIM, aiming at providing higher integrity performance for more stringent phase of flight. The first step is to survey the necessary changes to adapt ARAIM algorithm to urban scenario. Experimental study highlights the prerequisite of finding a noise model to represents the signal noise level in urban area. After a suitable noise model was found after a comparative study, the KF-based ARAIM algorithm was developed. This method evaluates the separation of state correction using different subsets of measurement to detect abnormalities as well as potential faulty satellites for exclusion. The proposed method was also validated using simulation and real data. Performance analysis results show that the proposed algorithm can effectively follows the changes of signal quality which is expected to occur frequently when moving in urban environment, confirming its suitability for integrity monitoring in urban environment