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Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (20 August 2019) | Viewed by 53463

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Special Issue Editors

Dr. Elena Simona Lohan

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Guest Editor

Electrical Engineering unit, Tampere University, Korkeakoulunkatu 1, 33720 Tampere, Finland
Interests: wireless positioning and navigation; 5G; wearable computing; statistical signal processing; IoT
Special Issues, Collections and Topics in MDPI journals

Dr. Alberto De la Fuente

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Guest Editor

Product Manager at GMV, Madrid, Spain
Interests: GNSS; aviation; localization of GNSS interferences

Prof. Dr. Fabio Dovis

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Guest Editor

Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
Interests: satellite navigation and positioning; high altitude platforms for telecommunications; multichannel modulation schemes; wavelet modulations; adaptive array signal
Special Issues, Collections and Topics in MDPI journals

Dr. Pau Closas

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Guest Editor

Department of Electrical & Computing Engineering, Northeastern University, Boston, MA, USA
Interests: statistical and array signal processing; Bayesian inference; GNSS and indoor technologies

Special Issue Information

Dear Colleagues,

Sensors welcomes submissions to this Special Issue on “Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles”.

Commercial and non-commercial aircrafts, and emerging Unmanned Aerial Vehicles (UAVs) of the future, highly rely on GNSS for positioning, navigation and tracking. However, GNSS is more and more affected by various sources of radiofrequency interference, as pointed out annually by the Eurocontrol voluntary ATM incident report and in the International Air Transport Association (IATA) safety reports. Jamming, spoofing, meaconing, and harmonics from other wireless systems using frequency bands close to GNSS bands, and other types of in-band and adjacent band emissions, are a few examples of possible interferences in GNSS-based localization, navigation, and tracking of aircrafts. Such interferences might threaten drone functionality, with severe concerns for navigation systems, and, as a consequence, in some cases for the safety of users, as well as for the reliability of applications. This call invites original contributions and comprehensive survey papers in research areas related to how to detect, localize, classify and mitigate interference in GNSS signals used in aviation, as well as proposals of alternative or complementary solutions to deal with GNSS interference.

The main themes and keywords to guide potential authors are as follows:

Interference detection, classification, mitigation, and localization in GNSS
Authentication mechanisms in GNSS
Novel navigation solutions for aerial vehicles

Dr. Elena Simona Lohan
Dr. Fabio Dovis
Dr. Alberto de la Fuente
Dr. Pau Closas
Guest Editors

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Keywords

GNSS interferences
Spoofing
Meaconing
Interference detection
Interference mitigation
Interference localization
Interference classification
Authentication mechanisms in GNSS
Alternative/complementary tracking and navigation methods for aviation
Drones
Aviation
UAV

Published Papers (12 papers)

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Research

18 pages, 4691 KiB

Open AccessArticle

Robust Statistics for GNSS Positioning under Harsh Conditions: A Useful Tool?

by Daniel Medina, Haoqing Li, Jordi Vilà-Valls and Pau Closas

Sensors 2019, 19(24), 5402; https://doi.org/10.3390/s19245402 - 07 Dec 2019

Cited by 21 | Viewed by 3999

Abstract

Navigation problems are generally solved applying least-squares (LS) adjustments. Techniques based on LS can be shown to perform optimally when the system noise is Gaussian distributed and the parametric model is accurately known. Unfortunately, real world problems usually contain unexpectedly large errors, so-called outliers, that violate the noise model assumption, leading to a spoiled solution estimation. In this work, the framework of robust statistics is explored to provide robust solutions to the global navigation satellite systems (GNSS) single point positioning (SPP) problem. Considering that GNSS observables may be contaminated by erroneous measurements, we survey the most popular approaches for robust regression (M-, S-, and MM-estimators) and how they can be adapted into a general methodology for robust GNSS positioning. We provide both theoretical insights and validation over experimental datasets, which serves in discussing the robust methods in detail. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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15 pages, 3452 KiB

Open AccessArticle

Jammer Classification in GNSS Bands Via Machine Learning Algorithms

by Ruben Morales Ferre, Alberto de la Fuente and Elena Simona Lohan

Sensors 2019, 19(22), 4841; https://doi.org/10.3390/s19224841 - 06 Nov 2019

Cited by 40 | Viewed by 8177

Abstract

This paper proposes to treat the jammer classification problem in the Global Navigation Satellite System bands as a black-and-white image classification problem, based on a time-frequency analysis and image mapping of a jammed signal. The paper also proposes to apply machine learning approaches in order to sort the received signal into six classes, namely five classes when the jammer is present with different jammer types and one class where the jammer is absent. The algorithms based on support vector machines show up to

94.90 %

accuracy in classification, and the algorithms based on convolutional neural networks show up to

91.36 %

accuracy in classification. The training and test databases generated for these tests are also provided in open access. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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14 pages, 943 KiB

Open AccessArticle

Inertial-Navigation-Aided Single-Satellite Highly Dynamic Positioning Algorithm

by Lingling Zhang, Chengkai Tang, Yi Zhang and Houbing Song

Sensors 2019, 19(19), 4196; https://doi.org/10.3390/s19194196 - 27 Sep 2019

Cited by 7 | Viewed by 2298

Abstract

Nowadays, research on global navigation satellite systems (GNSS) has reached a certain level of maturity to provide high-precision positioning services in many applications. Nonetheless, there are challenging GNSS-denial environments where a temporarily deployed single-satellite positioning system is a promising choice. To further meet the emergency call of highly dynamic targets in such situations, an augmented single-satellite positioning algorithm is proposed in this paper. First, the initial location of the highly dynamic target is found by real-time displacement feedback from the inertial navigation system (INS). Then, considering the continuity of position change, and taking advantage of the high accuracy and robustness of the unscented Kalman filter (UKF), target location is through iteration and fusion. Comparing this proposed method with the least-squares Newton-iterative Doppler single-satellite positioning system and the pseudorange rate-assisted method under synthetic error conditions, the positioning error of our algorithm was

10 %

less than the other two algorithms. This verified the validation of our algorithm in the single-satellite system with highly dynamic targets. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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18 pages, 11374 KiB

Open AccessArticle

A GPS Spoofing Generator Using an Open Sourced Vector Tracking-Based Receiver

by Qian Meng, Li-Ta Hsu, Bing Xu, Xiapu Luo and Ahmed El-Mowafy

Sensors 2019, 19(18), 3993; https://doi.org/10.3390/s19183993 - 16 Sep 2019

Cited by 25 | Viewed by 4773

Abstract

Spoofing can seriously threaten the use of the Global Positioning System (GPS) in critical applications such as positioning and navigation of autonomous vehicles. Research into spoofing generation will contribute to assessment of the threat of possible spoofing attacks and help in the development of anti-spoofing methods. However, the recent commercial off-the-shelf (COTS) spoofing generators are expensive and the technology implementation is complicated. To address the above problem and promote the GPS safety-critical applications, a spoofing generator using a vector tracking-based software-defined receiver is proposed in this contribution. The spoofing generator aims to modify the raw signals by cancelling the actual signal component and adding the spoofing signal component. The connections between the spreading code and carrier, and the states of the victim receiver are established through vector tracking. The actual signal can be predicted effectively, and the spoofing signal will be generated with the spoofing trajectory at the same time. The experimental test results show that the spoofing attack signal can effectively mislead the victim receiver to the designed trajectory. Neither the tracking channels nor the positioning observations have abnormal changes during this processing period. The recent anti-spoofing methods cannot detect this internal spoofing easily. The proposed spoofing generator can cover all open-sky satellites with a high quality of concealment. With the superiority of programmability and diversity, it is believed that the proposed method based on an open source software-defined receiver has a great value for anti-spoofing research of different GNSS signals. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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21 pages, 660 KiB

Open AccessArticle

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

by Ngoc Mai Nguyen, Le Chung Tran, Farzad Safaei, Son Lam Phung, Peter Vial, Nam Huynh, Anne Cox, Theresa Harada and Johan Barthelemy

Sensors 2019, 19(11), 2633; https://doi.org/10.3390/s19112633 - 10 Jun 2019

Cited by 9 | Viewed by 4149

Abstract

Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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22 pages, 9251 KiB

Open AccessArticle

Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles

by Hery Mwenegoha, Terry Moore, James Pinchin and Mark Jabbal

Sensors 2019, 19(11), 2467; https://doi.org/10.3390/s19112467 - 29 May 2019

Cited by 7 | Viewed by 4411

Abstract

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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17 pages, 2693 KiB

Open AccessArticle

A Multi-Antenna Scheme for Early Detection and Mitigation of Intermediate GNSS Spoofing

by Jaroslaw Magiera

Sensors 2019, 19(10), 2411; https://doi.org/10.3390/s19102411 - 27 May 2019

Cited by 20 | Viewed by 3762

Abstract

This article presents a method for detecting and mitigating intermediate GNSS spoofing. In this type of attack, at its early stage, a spoofer transmits counterfeit signals which have slight time offsets compared to true signals arriving from satellites. The anti-spoofing method proposed in this article fuses antenna array processing techniques with a multipath detection algorithm. The latter is necessary to separate highly correlated true and counterfeit GNSS signals. Spoofing detection is based on comparison of steering vectors related to received spatial components. Whereas mitigation is achieved by means of adaptive beamforming which excises interferences arriving from common direction and preserves undistorted signals from GNSS satellites. Performance of proposed method is evaluated through simulations, results of which prove the usefulness of this method for protecting GNSS receivers from intermediate spoofing interference. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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12 pages, 7418 KiB

Open AccessArticle

A Miniaturized Multiband Antenna Array for Robust Navigation in Aerial Applications

by Stefano Caizzone, Georg Buchner, Mihaela-Simona Circiu, Manuel Cuntz, Wahid Elmarissi and Emilio Pérez Marcos

Sensors 2019, 19(10), 2258; https://doi.org/10.3390/s19102258 - 16 May 2019

Cited by 13 | Viewed by 3055

Abstract

Satellite navigation is more and more important in a plethora of very different application fields, ranging from bank transactions to shipping, from autonomous driving to aerial applications, such as avionics as well as unmanned aerial vehicles (UAVs). Due to the increasing dependency on satellite navigation, the need for robust systems able to counteract unintentional or intentional interferences is growing. When considering interference-robust designs; however, the complexity increases. Top performance is obtained through the use of multi-antenna receivers capable of performing spatial nulling in the direction of the interference signals. In particular, mobile applications (aeronautics, UAVs, automotive) have a substantial interest in robust navigation, but they also have the strongest constraints on the weight and available places for installation, with the use of bigger and heavier systems posing a substantial problem. In order to overcome this limitation, the present work shows a miniaturized five element (4+1) antenna array, which operates at the L1/E1 band (with array capability), as well as at the L5/E5 band (as a single antenna). The proposed antenna array is able to fit into a 3.5-inch footprint, i.e., is compliant with the most widespread footprints for single antennas. Moreover, it is capable of multiband operation and meets the requirements of dual-frequency multi-constellation (DFMC) systems. Thanks to its extreme miniaturization and its compliance with current airborne single antenna footprints, the presented antenna array is suitable for easy integration in future aerial platforms, while enabling robustness and enhancing interference mitigation techniques using multi-antenna processing. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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19 pages, 5265 KiB

Open AccessArticle

Impact Analysis of Standardized GNSS Receiver Testing against Real-World Interferences Detected at Live Monitoring Sites

by Mohammad Zahidul H. Bhuiyan, Nunzia Giorgia Ferrara, Amin Hashemi, Sarang Thombre, Michael Pattinson and Mark Dumville

Sensors 2019, 19(6), 1276; https://doi.org/10.3390/s19061276 - 13 Mar 2019

Cited by 6 | Viewed by 3661

Abstract

GNSS-based applications are susceptible to different threats, including radio frequency interference. Ensuring that the new applications can be validated against the latest threats supports the wider adoption and success of GNSS in higher value markets. Therefore, the availability of standardized GNSS receiver testing procedures is central to developing the next generation of receiver technologies. The EU Horizon2020 research project STRIKE3 (Standardization of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation) proposed standardized test procedures to validate different categories of receivers against real-world interferences, detected at different monitoring sites. This paper describes the recorded interference signatures, their use in standardized test procedures, and analyzes the result for two categories of receivers, namely mass-market and professional grade. The result analysis in terms of well-defined receiver key performance indicators showed that performance of both receiver categories was degraded by the selected interference threats, although there was considerable difference in degree and nature of their impact. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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17 pages, 794 KiB

Open AccessArticle

Detection of Induced GNSS Spoofing Using S-Curve-Bias

by Wenyi Wang, Na Li, Renbiao Wu and Pau Closas

Sensors 2019, 19(4), 922; https://doi.org/10.3390/s19040922 - 22 Feb 2019

Cited by 19 | Viewed by 4066

Abstract

In Global Navigation Satellite System (GNSS), a spoofing attack consists of forged signals which possibly cause the attacked receivers to deduce a false position, a false clock, or both. In contrast to simplistic spoofing, the induced spoofing captures the victim tracking loops by gradually adjusting it’s parameters, e.g., code phase and power. Then the victims smoothly deviates from the correct position or timing. Therefore, it is more difficult to detect the induced spoofing than the simplistic one. In this paper, by utilizing the dynamic nature of such gradual adjustment process, an induced spoofing detection method is proposed based on the S-curve-bias (SCB). Firstly, SCB in the inducing process is theoretically derived. Then, in order to detect the induced spoofing, a detection metric is defined. After that, a series of experiments using the Texas spoofing test battery (TEXBAT) are performed to demonstrate the effectiveness of the proposed algorithm. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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17 pages, 5002 KiB

Open AccessArticle

Spoofing Detection and Mitigation in a Multi-correlator GPS Receiver Based on the Maximum Likelihood Principle

by Yanbing Guo, Lingjuan Miao and Xi Zhang

Sensors 2019, 19(1), 37; https://doi.org/10.3390/s19010037 - 22 Dec 2018

Cited by 17 | Viewed by 3655

Abstract

As a structural interference, spoofing is difficult to detect by the target receiver while the advent of a repeater makes the implementation of spoofing much easier. Most existing anti-spoofing methods are merely capable of detecting the spoofing, i.e., they cannot effectively remove counterfeit signals. Therefore, based on the similarities between multipath and spoofing, the feasibility of applying multipath mitigation methods to anti-spoofing is first analyzed in this paper. We then propose a novel algorithm based on maximum likelihood (ML) estimation to resolve this problem. The tracking channels with multi-correlators are constructed and a set of corresponding steps of detecting and removing the counterfeit signals is designed to ensure that the receiver locks the authentic signals in the presence of spoofing. Finally, the spoofing is successfully executed with a software receiver and the saved intermediate frequency (IF) signals, on this basis, the effectiveness of the proposed algorithm is verified by experiments. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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22 pages, 12496 KiB

Open AccessArticle

A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System

by Yushi Hao, Aigong Xu, Xin Sui and Yulei Wang

Sensors 2018, 18(11), 3809; https://doi.org/10.3390/s18113809 - 06 Nov 2018

Cited by 32 | Viewed by 5869

Abstract

Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method. The impact of innovation perturbation produced by measurement outliers is found to account for positive feedback and numerical issues. Measurement noise covariance is updated based on a remodification algorithm according to measurement reliability specifications. An experimental field test was performed to demonstrate the robustness of the proposed state estimation method against dynamic model errors and measurement outliers. Full article

(This article belongs to the Special Issue Interference, Robustness and Complementary Solutions for GNSS-Based Navigation for Aerial Vehicles)

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