Research

20 pages, 2425 KiB

Open AccessArticle

Galileo L10 Satellites: Orbit, Clock and Signal-in-Space Performance Analysis

by Constantin-Octavian Andrei, Sonja Lahtinen, Markku Poutanen, Hannu Koivula and Jan Johansson

Sensors 2021, 21(5), 1695; https://doi.org/10.3390/s21051695 - 01 Mar 2021

Cited by 2 | Viewed by 5518

The tenth launch (L10) of the European Global Navigation Satellite System Galileo filled in all orbital slots in the constellation. The launch carried four Galileo satellites and took place in July 2018. The satellites were declared operational in February 2019. In this study, [...] Read more.

The tenth launch (L10) of the European Global Navigation Satellite System Galileo filled in all orbital slots in the constellation. The launch carried four Galileo satellites and took place in July 2018. The satellites were declared operational in February 2019. In this study, we report on the performance of the Galileo L10 satellites in terms of orbital inclination and repeat period parameters, broadcast satellite clocks and signal in space (SiS) performance indicators. We used all available broadcast navigation data from the IGS consolidated navigation files. These satellites have not been reported in the previous studies. First, the orbital inclination (

56.7 \pm 0.15

°) and repeat period (

50680.7 \pm 0.22

s) for all four satellites are within the nominal values. The data analysis reveals also 13.5-, 27-, 177- and 354-days periodic signals. Second, the broadcast satellite clocks show different correction magnitude due to different trends in the bias component. One clock switch and several other minor correction jumps have occurred since the satellites were declared operational. Short-term discontinuities are within ±1 ps/s, whereas clock accuracy values are constantly below 0.20 m (root-mean-square—rms). Finally, the SiS performance has been very high in terms of availability and accuracy. Monthly SiS availability has been constantly above the target value of 87% and much higher in 2020 as compared to 2019. Monthly SiS accuracy has been below 0.20 m (95th percentile) and below 0.40 m (99th percentile). The performance figures depend on the content and quality of the consolidated navigation files as well as the precise reference products. Nevertheless, these levels of accuracy are well below the 7 m threshold (95th percentile) specified in the Galileo service definition document. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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22 pages, 1978 KiB

Open AccessArticle

Influence of Noise-Limited Censored Path Loss on Model Fitting and Path Loss-Based Positioning

by Aki Karttunen, Mikko Valkama and Jukka Talvitie

Sensors 2021, 21(3), 987; https://doi.org/10.3390/s21030987 - 02 Feb 2021

Viewed by 1900

Abstract

Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning [...] Read more.

Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning technologies. Conventionally, PL-based positioning has two phases—fitting a PL model to training data and positioning based on the link distance estimates. However, in both phases, the maximum measurable PL is limited by measurement noise. Such immeasurable samples are called censored PL data and such noisy data are commonly neglected in both the model fitting and in the positioning phase. In the case of censored PL, the loss is known to be above a known threshold level and that information can be used in model fitting and in the positioning phase. In this paper, we examine and propose how to use censored PL data in PL model-based positioning. Additionally, we demonstrate with several simulations the potential of the proposed approach for considerable improvements in positioning accuracy (23–57%) and improved robustness against PL model fitting errors. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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39 pages, 3401 KiB

Open AccessArticle

Evaluation of Adaptive Loop-Bandwidth Tracking Techniques in GNSS Receivers

by Iñigo Cortés, Johannes Rossouw van der Merwe, Jari Nurmi, Alexander Rügamer and Wolfgang Felber

Sensors 2021, 21(2), 502; https://doi.org/10.3390/s21020502 - 12 Jan 2021

Cited by 17 | Viewed by 3084

Abstract

Global navigation satellite system (GNSS) receivers use tracking loops to lock onto GNSS signals. Fixed loop settings limit the tracking performance against noise, receiver dynamics, and the current scenario. Adaptive tracking loops adjust these settings to achieve optimal performance for a given scenario. [...] Read more.

Global navigation satellite system (GNSS) receivers use tracking loops to lock onto GNSS signals. Fixed loop settings limit the tracking performance against noise, receiver dynamics, and the current scenario. Adaptive tracking loops adjust these settings to achieve optimal performance for a given scenario. This paper evaluates the performance and complexity of state-of-the-art adaptive scalar tracking techniques used in modern digital GNSS receivers. Ideally, a tracking channel should be adjusted to both noisy and dynamic environments for optimal performance, defined by tracking precision and loop robustness. The difference between the average tracking jitter of the discriminator’s output and the square-root Cramér-Rao bound (CRB) indicates the loops’ tracking capability. The ability to maintain lock characterizes the robustness in highly dynamic scenarios. From a system perspective, the average lock indicator is chosen as a metric to measure the performance in terms of precision, whereas the average number of visible satellites being tracked indicates the system’s robustness against dynamics. The average of these metrics’ product at different noise levels leads to a reliable system performance metric. Adaptive tracking techniques, such as the fast adaptive bandwidth (FAB), the fuzzy logic (FL), and the loop-bandwidth control algorithm (LBCA), facilitate a trade-off for optimal performance. These adaptive tracking techniques are implemented in an open software interface GNSS hardware receiver. All three methods steer a third-order adaptive phase locked loop (PLL) and are tested in simulated scenarios emulating static and high-dynamic vehicular conditions. The measured tracking performance, system performance, and time complexity of each algorithm present a detailed analysis of the adaptive techniques. The results show that the LBCA with a piece-wise linear approximation is above the other adaptive loop-bandwidth tracking techniques while preserving the best performance and lowest time complexity. This technique achieves superior static and dynamic system performance being 1.5 times more complex than the traditional tracking loop. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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21 pages, 2758 KiB

Open AccessArticle

Computational Load Analysis of a Galileo OSNMA-Ready Receiver for ARM-Based Embedded Platforms

by Micaela Troglia Gamba, Mario Nicola and Beatrice Motella

Sensors 2021, 21(2), 467; https://doi.org/10.3390/s21020467 - 11 Jan 2021

Cited by 15 | Viewed by 2196

Abstract

Many GNSS applications have been experiencing some constantly growing needs in terms of security and reliability. To address some of them, both GPS and Galileo are proposing evolutions of their legacy civil signals, embedding features of authentication. This paper focuses on the Galileo [...] Read more.

Many GNSS applications have been experiencing some constantly growing needs in terms of security and reliability. To address some of them, both GPS and Galileo are proposing evolutions of their legacy civil signals, embedding features of authentication. This paper focuses on the Galileo Open Signal Navigation Message Authentication (OSNMA) and describes its implementation within a real-time software receiver for ARM-based embedded platforms. The innovative contributions of the paper include the software profiling analysis for the OSNMA add on, along with the comparison among performances obtained with different platforms. In addition, specific evaluations on the computational load of the whole receiver complete the analysis. The receiver used for the implementation belongs to the NGene receivers family—real-time fully-software GPS and Galileo receivers, tailored for different platforms and sharing the same core processing. In detail, the paper deals with the introduction of the OSNMA support inside the eNGene, the version of the receiver executable by ARM-based embedded platforms. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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17 pages, 12825 KiB

Open AccessArticle

Deep Learning-Based Cell-Level and Beam-Level Mobility Management System

by Roman Klus, Lucie Klus, Dmitrii Solomitckii, Jukka Talvitie and Mikko Valkama

Sensors 2020, 20(24), 7124; https://doi.org/10.3390/s20247124 - 11 Dec 2020

Cited by 5 | Viewed by 2384

Abstract

The deployment with beamforming-capable base stations in 5G New Radio (NR) requires an efficient mobility management system to reliably operate with minimum effort and interruption. In this work, we propose two artificial neural network models to optimize the cell-level and beam-level mobility management. [...] Read more.

The deployment with beamforming-capable base stations in 5G New Radio (NR) requires an efficient mobility management system to reliably operate with minimum effort and interruption. In this work, we propose two artificial neural network models to optimize the cell-level and beam-level mobility management. Both models consist of convolutional, as well as dense, layer blocks. Based on current and past received power measurements, as well as positioning information, they choose the optimum serving cell and serving beam, respectively. The obtained results show that the proposed cell-level mobility model is able to sustain a strong serving cell and reduce the number of handovers by up to

94.4 %

compared to the benchmark solution when the uncertainty (representing shadowing, interference, etc.) is introduced to the received signal strength measurements. The proposed beam-level mobility management model is able to proactively choose and sustain the strongest serving beam, even when high uncertainty is introduced to the measurements. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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23 pages, 2180 KiB

Open AccessArticle

MAMPI-UWB—Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers

by Marco Cimdins, Sven Ole Schmidt and Horst Hellbrück

Sensors 2020, 20(24), 7090; https://doi.org/10.3390/s20247090 - 10 Dec 2020

Cited by 20 | Viewed by 2699

Abstract

In this paper, we propose a multipath-assisted device-free localization (DFL) system that includes magnitude and phase information (MAMPI). The DFL system employs ultra-wideband (UWB) channel impulse response (CIR) measurements, enabling the extraction of several multipath components (MPCs) and thereby benefits from multipath propagation. [...] Read more.

In this paper, we propose a multipath-assisted device-free localization (DFL) system that includes magnitude and phase information (MAMPI). The DFL system employs ultra-wideband (UWB) channel impulse response (CIR) measurements, enabling the extraction of several multipath components (MPCs) and thereby benefits from multipath propagation. We propose a radio propagation model that calculates the effect on the received signal based on the position of a person within a target area. Additionally, we propose a validated error model for the measurements and explain the creation of different feature vectors and extraction of the MPCs from Decawave DW1000 CIR measurements. We evaluate the system via simulations of the position error probability and a measurement setup in an indoor scenario. We compare the performance of MAMPI to a conventional DFL system based on four sensor nodes that measures radio signal strength values. The combination of the magnitude and phase differences for the feature vectors results in a position error probability that is comparable to a conventional system but requires only two sensor nodes. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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24 pages, 2064 KiB

Open AccessArticle

HDDM Hardware Evaluation for Robust Interference Mitigation

by Fabio Garzia, Johannes Rossouw van der Merwe, Alexander Rügamer, Santiago Urquijo and Wolfgang Felber

Sensors 2020, 20(22), 6492; https://doi.org/10.3390/s20226492 - 13 Nov 2020

Cited by 10 | Viewed by 2010

Abstract

Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art [...] Read more.

Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art interference mitigation techniques. The high-rate DFT-based data manipulator (HDDM) is proposed as a possible solution to overcome their limitations. This paper presents a hardware implementation of the HDDM algorithm. The hardware HDDM module is integrated in three different receivers equipped with analog radio-frequency (RF) front-ends supporting signals with different dynamic range. The resource utilization and power consumption is evaluated for the three cases. The algorithm is compared to a low-end mass-market receiver and a high-end professional receiver with basic and sophisticated interference mitigation capabilities, respectively. Different type of interference are used to compare the mitigation capabilities of the receivers under test. Results of the HDDM hardware implementation achieve the similar or improved performance to the state of the art. With more complex interferences, like frequency hopping or pulsed, the HDDM shows even better performance. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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14 pages, 2546 KiB

Open AccessArticle

RSS-Based Localization and Mobility Evaluation Using a Single NB-IoT Cell

by Thomas Janssen, Rafael Berkvens and Maarten Weyn

Sensors 2020, 20(21), 6172; https://doi.org/10.3390/s20216172 - 29 Oct 2020

Cited by 10 | Viewed by 2689

Abstract

Low Power Wide Area Networks (LPWAN) have the ability to localize a mobile transmitter using signals of opportunity, as a low power and low cost alternative to satellite-based solutions. In this paper, we evaluate the accuracy of three localization approaches based on the [...] Read more.

Low Power Wide Area Networks (LPWAN) have the ability to localize a mobile transmitter using signals of opportunity, as a low power and low cost alternative to satellite-based solutions. In this paper, we evaluate the accuracy of three localization approaches based on the Received Signal Strength (RSS). More specifically, the performance of a proximity, range-based and optimized fingerprint-based algorithm is evaluated in a large-scale urban environment using a public Narrowband Internet of Things (NB-IoT) network. The results show a mean location estimation error of 340, 320 and 204 m, respectively. During the measurement campaign, we discovered a mobility issue in NB-IoT. In contrast to other LPWAN and cellular technologies which use multiple gateways or cells to locate a device, only a single cell antenna can be used for RSS-based localization in NB-IoT. Therefore, we address this limitation in the current NB-IoT hardware and software by studying the mobility of the cellular-based 3GPP standard in a localization context. Experimental results show that the lack of handover support leads to increased cell reselection time and poor cell sector reliability, which in turn results in reduced localization performance. Full article

(This article belongs to the Special Issue Selected Papers from 10th International Conference on Localization and GNSS 2020 (ICL-GNSS 2020))

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