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Robust Processing for GNSS
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Robust Processing for GNSS

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

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 8904

Special Issue Editors

Dr. Daniele Borio

E-Mail Website
Guest Editor
European Commission, Joint Research Centre (JRC), Varese, Italy
Interests: digital and wireless communications; location; navigation
Special Issues, Collections and Topics in MDPI journals
Dr. Ciro Gioia

E-Mail Website
Guest Editor
European Commission Joint Research Centre (JRC) Directorate for Space Security and Migration
Interests: location and navigation; geomatics
Dr. Andriy Konovaltsev

E-Mail
Guest Editor
Research Associate, Institute of Communications and Navigation, German Aerospace Center (DLR)
Interests: satellite navigation; radio frequency interference;; jamming, spoofing; resilient receiver; adaptive antenna arrays

Special Issue Information

Dear Colleagues,

Global navigation satellite system (GNSS) technology is experiencing rapid and sometimes unexpected developments, with the completion and modernization of the different satellite constellations, with new opportunities on the user side, such as the availability of raw measurements in smartphones, and with the development of new techniques and algorithms that can respond to different user needs. In addition to this, the wide availability of inertial sensor measurements, received signal strength indicator (RSSI) readings from Bluetooth and WiFi beacons, round trip time (RTT) observations specified by the WiFi IEEE 802.11-2016 standard, and several types of signals of opportunity (SoP) are promoting the development of robust sensor fusion algorithms that can improve GNSS performance, provide a seamless navigation experience, and cope with impairments such as radio frequency (RF) interference, weak GNSS signal conditions, and difficult reception environments. Moreover, authentication services, such as the Galileo Open Service Navigation Message Authentication (OS-NMA) and the Commercial Service Authentication (CAS) will provide robust verification methods to mitigate threats such as GNSS spoofing

This Special Issue will investigate different approaches that can improve GNSS performance through advanced algorithms for signal processing and navigation, and through hybridization with measurements from other sensors. There will be a specific focus on robustness, intended as the ability of a system to operate under non-nominal conditions such as jamming and RF interference.

The main themes to guide potential authors are as follows:

  • Robust signal processing on all receiver stages: signal reception and conditioning, including the use of multiple antennas and antenna arrays, acquisition, tracking, data demodulation, and navigation solution
  • Sensor fusion and GNSS hybridization including algorithms for smartphone raw measurements
  • Cooperative positioning and robust navigation in a multi-agent collaborative context

Dr. Daniele Borio
Dr. Ciro Gioia
Dr. Andriy Konovaltsev
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Robustness
  • resilience
  • signal combining
  • meta-signals
  • smartphones
  • raw measurements
  • inertial sensors
  • WiFi RSSI
  • WiFi RTT
  • Bluetooth beacons
  • cooperative positioning
  • sensor fusion
  • interference
  • jamming
  • spoofing

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Published Papers (3 papers)

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Research

20 pages, 18744 KiB  
Article
Robustness against Chirp Signal Interference of On-Board Vehicle Geodetic and Low-Cost GNSS Receivers
by Franc Dimc, Polona Pavlovčič-Prešeren and Matej Bažec
Sensors 2021, 21(16), 5257; https://doi.org/10.3390/s21165257 - 4 Aug 2021
Cited by 6 | Viewed by 2609
Abstract
Robust autonomous driving, as long as it relies on satellite-based positioning, requires carrier-phase-based algorithms, among other types of data sources, to obtain precise and true positions, which is also primarily true for the use of GNSS geodetic receivers, but also increasingly true for [...] Read more.
Robust autonomous driving, as long as it relies on satellite-based positioning, requires carrier-phase-based algorithms, among other types of data sources, to obtain precise and true positions, which is also primarily true for the use of GNSS geodetic receivers, but also increasingly true for mass-market devices. The experiment was conducted under line-of-sight conditions on a straight road during a period of no traffic. The receivers were positioned on the roof of a car travelling at low speed in the presence of a static jammer, while kinematic relative positioning was performed with the static reference base receiver. Interference mitigation techniques in the GNSS receivers used, which were unknown to the authors, were compared using (a) the observed carrier-to-noise power spectral density ratio as an indication of the receivers’ ability to improve signal quality, and (b) the post-processed position solutions based on RINEX-formatted data. The observed carrier-to-noise density generally exerts the expected dependencies and leaves space for comparisons of applied processing abilities in the receivers, while conclusions on the output data results comparison are limited due to the non-synchronized clocks of the receivers. According to our current and previous results, none of the GNSS receivers used in the experiments employs an effective type of complete mitigation technique adapted to the chirp jammer. Full article
(This article belongs to the Special Issue Robust Processing for GNSS)
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21 pages, 426 KiB  
Article
Low Complexity Robust Data Demodulation for GNSS
by Lorenzo Ortega, Charly Poulliat, Marie Laure Boucheret, Marion Aubault Roudier, Hanaa Al-Bitar and Pau Closas
Sensors 2021, 21(4), 1341; https://doi.org/10.3390/s21041341 - 13 Feb 2021
Viewed by 2732
Abstract
In this article, we provide closed-form approximations of log-likelihood ratio (LLR) values for direct sequence spread spectrum (DS-SS) systems over three particular scenarios, which are commonly found in the Global Navigation Satellite System (GNSS) environment. Those scenarios are the open sky with smooth [...] Read more.
In this article, we provide closed-form approximations of log-likelihood ratio (LLR) values for direct sequence spread spectrum (DS-SS) systems over three particular scenarios, which are commonly found in the Global Navigation Satellite System (GNSS) environment. Those scenarios are the open sky with smooth variation of the signal-to-noise ratio (SNR), the additive Gaussian interference, and pulsed jamming. In most of the current communications systems, block-wise estimators are considered. However, for some applications such as GNSSs, symbol-wise estimators are available due to the low data rate. Usually, the noise variance is considered either perfectly known or available through symbol-wise estimators, leading to possible mismatched demodulation, which could induce errors in the decoding process. In this contribution, we first derive two closed-form expressions for LLRs in additive white Gaussian and Laplacian noise channels, under noise uncertainty, based on conjugate priors. Then, assuming those cases where the statistical knowledge about the estimation error is characterized by a noise variance following an inverse log-normal distribution, we derive the corresponding closed-form LLR approximations. The relevance of the proposed expressions is investigated in the context of the GPS L1C signal where the clock and ephemeris data (CED) are encoded with low-density parity-check (LDPC) codes. Then, the CED is iteratively decoded based on the belief propagation (BP) algorithm. Simulation results show significant frame error rate (FER) improvement compared to classical approaches not accounting for such uncertainty. Full article
(This article belongs to the Special Issue Robust Processing for GNSS)
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20 pages, 1048 KiB  
Article
NeQuick-G and Android Devices: A Compromise between Computational Burden and Accuracy
by Ciro Gioia and Daniele Borio
Sensors 2020, 20(20), 5908; https://doi.org/10.3390/s20205908 - 19 Oct 2020
Cited by 5 | Viewed by 2463
Abstract
Ionospheric delay is one of the largest errors affecting Global Navigation Satellite System (GNSS) positioning in open-sky conditions, and different methods are currently available for mitigating ionospheric effects including dual-frequency measurements and corrections from augmentation systems. For single-frequency standalone receivers, the most widely [...] Read more.
Ionospheric delay is one of the largest errors affecting Global Navigation Satellite System (GNSS) positioning in open-sky conditions, and different methods are currently available for mitigating ionospheric effects including dual-frequency measurements and corrections from augmentation systems. For single-frequency standalone receivers, the most widely used approach to correct ionospheric delays is to rely on a model. In this respect, Klobuchar and NeQuick-G Ionospheric Correction Algorithms (ICAs) are the approaches adopted by GPS and Galileo, respectively. While the latter outperforms the Klobuchar model, it requires a significantly higher computational load, which can limit its exploitation in some market segments such as smartphones. In order to foster adoption of the NeQuick-G model in this type of device, a smart application of NeQuick-G is proposed. The solution relies on the assumption that ionospheric delays are practically constant over short time intervals. Thus, the update rate of the ionospheric correction computation can be significantly reduced. This solution was implemented, tested, and evaluated using real data collected with a static smartphone in an ad hoc set-up. The impact of reducing the ionospheric correction update rate has been evaluated in terms of processing time, of ionospheric correction deviations and in the Ranging Error (RE) and position domains. The analysis shows that a significant reduction of the processing time can be obtained with negligible degradation of the navigation solution. Full article
(This article belongs to the Special Issue Robust Processing for GNSS)
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