Signal Processing for Satellite Positioning Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 25776

Special Issue Editors

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
Finnish Geospatial Research Institute (FGI-NLS), Helsinki, Finland
Interests: GNSS-based atmospheric monitoring; scintilaltion detection and mitigation; GNSS software receivers

Special Issue Information

Dear Colleagues,

The recent development of new Global Navigation Satellite Navigation Systems, such as the European Galileo and the modernization of Global positioning system, GLONASS, is boosting new applications that range from classical navigation services, to a plethora of new fields that are using GNSS signals for purposes other than positioning. New applications to timing services, as well as the use of GNSS signals for scientific applications, such as ionospheric tomography, are becoming popular and new services are being deployed in these new application fields.

Nevertheless, all these new applications share classical positioning techniques and advanced signal processing algorithms, starting from weak received signals, through tailored receivers and processors, that are able to denoise, extract features, mitigate disturbances and interference, and retrieve timing information.

This Special Issue aims at collecting relevant papers describing advanced signal processing algorithms that are being developed to process the GNSS signals, not only for the classical positioning applications, but also for other fields such as timing and remote sensing.

Original processing architecture, low complexity implementation strategies, feature extraction algorithms, and machine learning approaches fall within the field of interest of this Special Issue. Digital signal processing algorithms acting along the processing chain will be considered, as they can address raw signal samples, processed signals, post-correlation values, raw and corrected pseudoranges, and positioning solutions.

Prof. Fabio Dovis
Dr. Nicola Linty
Guest Editors

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Keywords

  • Global Navigation Satellite Systems
  • Positioning
  • Interference Detection
  • Interference Mitigation
  • Remote Sensing
  • Ionosphere

Published Papers (8 papers)

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15 pages, 299 KiB  
Article
Semi-Supervised GNSS Scintillations Detection Based on DeepInfomax
by Giulio Franzese, Nicola Linty and Fabio Dovis
Appl. Sci. 2020, 10(1), 381; https://0-doi-org.brum.beds.ac.uk/10.3390/app10010381 - 04 Jan 2020
Cited by 7 | Viewed by 2787
Abstract
This work focuses on a machine learning based detection of ionospheric scintillation events affecting Global Navigation Satellite System (GNSS) signals. We here extend the recent detection results based on Decision Trees, designing a semi-supervised detection system based on the DeepInfomax approach recently proposed. [...] Read more.
This work focuses on a machine learning based detection of ionospheric scintillation events affecting Global Navigation Satellite System (GNSS) signals. We here extend the recent detection results based on Decision Trees, designing a semi-supervised detection system based on the DeepInfomax approach recently proposed. The paper shows that it is possible to achieve good classification accuracy while reducing the amount of time that human experts must spend manually labelling the datasets for the training of supervised algorithms. The proposed method is scalable and reduces the required percentage of annotated samples to achieve a given performance, making it a viable candidate for a realistic deployment of scintillation detection in software defined GNSS receivers. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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19 pages, 14415 KiB  
Article
UAV-Based GNSS-R for Water Detection as a Support to Flood Monitoring Operations: A Feasibility Study
by Rayan Imam, Marco Pini, Gianluca Marucco, Fabrizio Dominici and Fabio Dovis
Appl. Sci. 2020, 10(1), 210; https://0-doi-org.brum.beds.ac.uk/10.3390/app10010210 - 26 Dec 2019
Cited by 17 | Viewed by 3530
Abstract
Signals from global navigation satellite systems (GNSS) can be utilized as signals of opportunity in remote sensing applications. Geophysical properties of the earth surface can be detected and monitored by processing the back-scattered GNSS signals from the ground. In the literature, several airborne [...] Read more.
Signals from global navigation satellite systems (GNSS) can be utilized as signals of opportunity in remote sensing applications. Geophysical properties of the earth surface can be detected and monitored by processing the back-scattered GNSS signals from the ground. In the literature, several airborne GNSS-based passive radar experiments have been successfully demonstrated. With the advancements in small unmanned aerial vehicles (UAVs) and their applications for environmental monitoring, we want to investigate whether GNSS-based passive radar can provide valuable geospatial information from such platforms. Low-cost GNSS reflectometry sensors, developed using commercial of the shelf components, can be mounted onboard UAVs and flown to sense environmental parameters. This paper presents the results of a preliminary study to investigate the feasibility of utilizing data collected by UAV-based GNSS-R sensors to detect surface water for a potential application in supporting flood monitoring operations. The study was conducted in the area surrounding the Avigliana lakes in Northern Italy. The results show the possibility of detecting small water surfaces with few tens of meters resolution, and estimating the area of the lake surface with 92% accuracy. Furthermore, it is proved through simulations that the use of multi-GNSS increases this accuracy to about 99%. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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18 pages, 3543 KiB  
Article
High-Precision Pseudo-Noise Ranging Based on BOC Signal: Zero-Bias Mitigation Methods
by Chunjiang Ma, Xiaomei Tang, Zhicheng Lv, Zhibin Xiao and Guangfu Sun
Appl. Sci. 2019, 9(15), 3162; https://0-doi-org.brum.beds.ac.uk/10.3390/app9153162 - 03 Aug 2019
Cited by 1 | Viewed by 2256
Abstract
In high precision applications based on binary subcarrier offset (BOC) signals, zero-bias of the digital discriminator is an error of importance. Unlike the thermal noise error, zero-bias is a fixed deviation that is challenging to eliminate by filtering in the time domain. In [...] Read more.
In high precision applications based on binary subcarrier offset (BOC) signals, zero-bias of the digital discriminator is an error of importance. Unlike the thermal noise error, zero-bias is a fixed deviation that is challenging to eliminate by filtering in the time domain. In this paper, a statistical error analysis model for the zero-bias of BOC signal’s digital phase discriminator is established. The evaluation of the zero-bias is inseparable from the spreading code sequence and the initial phase of the signal through defining the concept of statistics maximum and statistics standard deviation. Based on the zero-bias statistical error analysis model, two receiver parameter design methods, namely, the baseband signal sampling frequency and the early-late correlation interval, are proposed. The performance of the algorithm is simulated on account of the limited bandwidth, Doppler frequency offset and thermal noise. The simulation results prove that the proposed algorithm can suppress the standard deviation of zero-bias within one phase resolution, which contributes substantially to the improvement of the measurement accuracy of pseudo-noise ranging. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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14 pages, 1895 KiB  
Article
An Open-Loop Receiver Architecture for Monitoring of Ionospheric Scintillations by Means of GNSS Signals
by Nicola Linty and Fabio Dovis
Appl. Sci. 2019, 9(12), 2482; https://0-doi-org.brum.beds.ac.uk/10.3390/app9122482 - 18 Jun 2019
Cited by 14 | Viewed by 3778
Abstract
The quality of positioning services based on Global Navigation Satellite Systems (GNSS) is improving at a fast pace, driven by the strict requirements of a plethora of new applications on accuracy, precision and reliability of the services. Nevertheless, ionospheric errors still bound the [...] Read more.
The quality of positioning services based on Global Navigation Satellite Systems (GNSS) is improving at a fast pace, driven by the strict requirements of a plethora of new applications on accuracy, precision and reliability of the services. Nevertheless, ionospheric errors still bound the achievable performance and better mitigation techniques must be devised. In particular, the harmful effect due to non-uniform distribution of the electron density that causes amplitude and phase variation of the GNSS signal, usually named as scintillation effects. For many high-accuracy applications, this is a threat to accuracy and reliability, and the presence of scintillation effect needs to be constantly monitored. To this purpose, traditional receivers employ closed-loop tracking architectures. In this paper, we investigate an alternative architecture and a related metric based on the statistical processing of the received signal, after a code-wipe off and a noise reduction phase. The new metric is based on the analysis of the statistical features of the conditioned signal, and it brings the same information of the S 4 index, normally estimated by means of closed-loop receivers. This new metric can be obtained at a higher rate as well as in the case of strong scintillations when a closed-loop receiver would fail the tracking of the GNSS signals. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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20 pages, 7468 KiB  
Article
A Joint Dual-Frequency GNSS/SINS Deep-Coupled Navigation System for Polar Navigation
by Lin Zhao, Mouyan Wu, Jicheng Ding and Yingyao Kang
Appl. Sci. 2018, 8(11), 2322; https://0-doi-org.brum.beds.ac.uk/10.3390/app8112322 - 21 Nov 2018
Cited by 8 | Viewed by 3078
Abstract
The strategic position of the polar area and its rich natural resources are becoming increasingly important, while the northeast and northwest passages through the Arctic are receiving much attention as glaciers continue to melt. The global navigation satellite system (GNSS) can provide real-time [...] Read more.
The strategic position of the polar area and its rich natural resources are becoming increasingly important, while the northeast and northwest passages through the Arctic are receiving much attention as glaciers continue to melt. The global navigation satellite system (GNSS) can provide real-time observation data for the polar areas, but may suffer low elevation problems of satellites, signals with poor carrier-power-to-noise-density ratio (C/N0), ionospheric scintillations, and dynamic requirements. In order to improve the navigation performance in polar areas, a deep-coupled navigation system with dual-frequency GNSS and a grid strapdown inertial navigation system (SINS) is proposed in the paper. The coverage and visibility of the GNSS constellation in polar areas are briefly reviewed firstly. Then, the joint dual-frequency vector tracking architecture of GNSS is designed with the aid of grid SINS information, which can optimize the tracking band, sharing tracking information to aid weak signal channels with strong signal channels and meet the dynamic requirement to improve the accuracy and robustness of the system. Besides this, the ionosphere-free combination of global positioning system (GPS) L1 C/A and L2 signals is used in the proposed system to further reduce ionospheric influence. Finally, the performance of the system is tested using a hardware simulator and semiphysical experiments. Experimental results indicate that the proposed system can obtain a better navigation accuracy and robust performance in polar areas. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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10 pages, 2555 KiB  
Article
Effect of Surface Mass Loading on Geodetic GPS Observations
by Zhen Li, Jianping Yue, Jiyuan Hu, Yunfei Xiang, Jian Chen and Yankai Bian
Appl. Sci. 2018, 8(10), 1851; https://0-doi-org.brum.beds.ac.uk/10.3390/app8101851 - 09 Oct 2018
Cited by 4 | Viewed by 2397
Abstract
We investigated the effect of mass loading (atmospheric, oceanic and hydrological loading (AOH)) on Global Positioning System (GPS) height time series from 30 GPS stations in the Eurasian plate. Wavelet coherence (WTC) was employed to inspect the correlation and the time-variable relative phase [...] Read more.
We investigated the effect of mass loading (atmospheric, oceanic and hydrological loading (AOH)) on Global Positioning System (GPS) height time series from 30 GPS stations in the Eurasian plate. Wavelet coherence (WTC) was employed to inspect the correlation and the time-variable relative phase between the two signals in the time–frequency domain. The results of the WTC-based semblance analysis indicated that the annual fluctuations in the two signals for most sites are physically related. The phase asynchrony at the annual time scale between GPS heights and AOH displacements indicated that the annual oscillation in GPS heights is due to a combination of mass loading signals and systematic errors (AOH modelling errors, geophysical effects and/or GPS system errors). Moreover, we discuss the impacts of AOH corrections on GPS noise estimation. The results showed that not all sites have an improved velocity uncertainty due to the increased amplitude of noise and/or the decreased spectral index after AOH corrections. Therefore, the posterior mass loading model correction is potentially feasible but not sufficient. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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14 pages, 4024 KiB  
Article
Data Fusion Based on Adaptive Interacting Multiple Model for GPS/INS Integrated Navigation System
by Chuang Zhang, Chen Guo and Daheng Zhang
Appl. Sci. 2018, 8(9), 1682; https://0-doi-org.brum.beds.ac.uk/10.3390/app8091682 - 17 Sep 2018
Cited by 19 | Viewed by 4375
Abstract
The extended Kalman filter (EKF) as a primary integration scheme has been applied in the Global Positioning System (GPS) and inertial navigation system (INS) integrated system. Nevertheless, the inherent drawbacks of EKF contain not only instability caused by linearization, but also massive calculation [...] Read more.
The extended Kalman filter (EKF) as a primary integration scheme has been applied in the Global Positioning System (GPS) and inertial navigation system (INS) integrated system. Nevertheless, the inherent drawbacks of EKF contain not only instability caused by linearization, but also massive calculation of Jacobian matrix. To cope with this problem, the adaptive interacting multiple model (AIMM) filter method is proposed to enhance navigation performance. The soft-switching characteristic, which is provided by interacting multiple model algorithm, permits process noise to be converted between upper and lower limits, and the measurement covariance is regulated by Sage adaptive filtering on-line Moreover, since the pseudo-range and Doppler observations need to be updated, an updating policy for classified measurement is considered. Finally, the performance of the GPS/INS integration method on the basis of AIMM is evaluated by a real ship, and comparison results demonstrate that AIMM could achieve a more position accuracy. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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11 pages, 2966 KiB  
Letter
Band-Pass Sampling in High-Order BOC Signal Acquisition
by Zhijun Liu, Baiyu Li, Xiangwei Zhu, Lixun Li and Guangfu Sun
Appl. Sci. 2018, 8(11), 2226; https://0-doi-org.brum.beds.ac.uk/10.3390/app8112226 - 12 Nov 2018
Cited by 5 | Viewed by 2690
Abstract
The binary offset carrier (BOC) modulation, which has been adopted in modern global navigation satellite systems (GNSS), provides a higher spectral compatibility with BPSK signals, and better tracking performance. However, the autocorrelation function (ACF) of BOC signals has multiple peaks. This feature complicates [...] Read more.
The binary offset carrier (BOC) modulation, which has been adopted in modern global navigation satellite systems (GNSS), provides a higher spectral compatibility with BPSK signals, and better tracking performance. However, the autocorrelation function (ACF) of BOC signals has multiple peaks. This feature complicates the acquisition process, since a smaller time searching step is required, which results in longer searching time or greater amounts of hardware resources. Another problem is the high Nyquist frequency, which leads to high computational complexity and power consumption. In this paper, to overcome these drawbacks, the band-pass sampling technique for multiple signals is introduced to BOC signals. The sampling frequency can be reduced significantly. Furthermore, the ACF of the sampled signal has only two secondary peaks, so that the code phase can be searched with a larger searching step. An acquisition structure base on dual-loop is proposed, to completely eliminate the ambiguity and compensate the subcarrier Doppler. The acquisition performance and the computational complexity are also analysed. Full article
(This article belongs to the Special Issue Signal Processing for Satellite Positioning Systems)
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