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High Performance Positioning, Navigation and Timing for Mobile Platforms

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

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 19715

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Prof. Dr. Washington Yotto Ochieng

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Guest Editor

Department of Civil and Environmental Engineering, Imperial College London, London, UK
Interests: navigation; positioning; transport; aviation; geomatics
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Dr. Mireille Elhajj

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Astra-Terra Limited and Imperial College London, London, UK
Interests: Smart Cities, Intelligent Transport Systems, Interference, Integrity Monitoring

Dr. Rui Sun

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College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: seamless positioning and navigation in challenging environments
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Dear Colleagues,

I hope that you are well in this unprecedented period. It gives us great pleasure to invite you to contribute to this Special Issue on high performance Positioning, Navigation and Timing (PNT) for mission (e.g., safety and security) critical applications. The provision of very high accuracy PNT and location-based capabilities for mobile platforms such as driverless cars requires the use of GNSS carrier phase measurements together with measurements and/or observables from other sources both bespoke and opportunistic, and spatial data. We invite innovative papers with the potential for high impact on knowledge and practice. The topics should address any aspects of the processing chain including receiver/sensor/antenna design, measurements/observables processing models (including error mitigation), system/sensor/spatial data integration or data fusion, and applications, with a particular focus on very high performance as measured in terms of the required navigation performance parameters of accuracy, integrity, continuity and availability. Papers that tackle interference (jamming, meaconing and spoofing) and integrity monitoring are particularly encouraged.

Prof. Washington Yotto Ochieng
Dr. Mireille Elhajj
Dr. Rui Sun
Guest Editors

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Keywords

Mobile platforms
Very high accuracy, integrity, continuity and availability
Multi-sensor integration
Data fusion

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Published Papers (6 papers)

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22 pages, 6279 KiB

Open AccessArticle

A Novel GNSS Interference Detection Method Based on Smoothed Pseudo-Wigner–Hough Transform

by Kewen Sun, Baoguo Yu, Mireille Elhajj, Washington Yotto Ochieng, Tengteng Zhang and Jianlei Yang

Sensors 2021, 21(13), 4306; https://doi.org/10.3390/s21134306 - 24 Jun 2021

Cited by 7 | Viewed by 2500

Abstract

This paper develops novel Global Navigation Satellite System (GNSS) interference detection methods based on the Hough transform. These methods are realized by incorporating the Hough transform into three Time-Frequency distributions: Wigner–Ville distribution, pseudo -Wigner–Ville distribution and smoothed pseudo-Wigner–Ville distribution. This process results in the corresponding Wigner–Hough transform, pseudo-Wigner–Hough transform and smoothed pseudo-Wigner–Hough transform, which are used in GNSS interference detection to search for local Hough-transformed energy peak in a small limited area within the parameter space. The developed GNSS interference detection methods incorporate a novel concept of zero Hough-transformed energy distribution percentage to analyze the properties of energy concentration and cross-term suppression. The methods are tested with real GPS L1-C/A data collected in the presence of sweep interference. The test results show that the developed methods can deal with the cross-term problem with improved interference detection performance. In particular, the GNSS interference detection performance obtained with the smoothed pseudo-Wigner–Hough transform method is at least double that of the Wigner–Hough transform-based approach; the smoothed pseudo-Wigner–Hough transform-based GNSS interference detection method is improved at least 20% over the pseudo-Wigner–Hough transform-based technique in terms of the zero Hough-transformed energy percentage criteria. Therefore, the proposed smoothed pseudo-Wigner–Hough transform-based method is recommended in the interference detection for GNSS receivers, particularly in challenging electromagnetic environments. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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18 pages, 4307 KiB

Open AccessArticle

Intense L-Band Solar Radio Bursts Detection Based on GNSS Carrier-To-Noise Ratio Decrease over Multi-Satellite and Multi-Station

by Fan Yang, Xuefen Zhu, Xiyuan Chen and Mengying Lin

Sensors 2021, 21(4), 1405; https://doi.org/10.3390/s21041405 - 17 Feb 2021

Cited by 2 | Viewed by 2246

Abstract

Intense solar radio bursts (SRBs) can increase the energy noise and positioning error of the bandwidth of global navigation satellite system (GNSS). The study of the interference from intense L-band SRBs is of great importance to the steady operation of GNSS receivers. Based [...] Read more.

C / N_{0}

) of multiple GNSS satellites over a large area of the sunlit hemisphere, an intense L-band SRB detection method without the aid of a radio telescope is proposed. Firstly, the valley period of a single satellite at a single monitoring station is detected. Then, the detection of SRBs is achieved by calculating the intersection of multiple satellites and multiple stations. The experimental results indicate that the detection rates of GPS L2 and GLONASS G2 are better than those of GPS L1 L5, GLONASS G1, and Galileo E1 E5. The detection rate of SRBs can reach 80% with a flux density above 800 solar flux unit (SFU) at the L2 frequency of GPS. Overall, the detection rate is not affected by the satellite distribution relative to the Sun. The proposed detection method is low-cost and has a high detection rate and low false alarm rate. This method is a noteworthy reference for coping with interference in GNSS from intense L-band SRBs. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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19 pages, 5588 KiB

Open AccessArticle

Driving Behavior Analysis of City Buses Based on Real-Time GNSS Traces and Road Information

by Yuan Yang, Jingjie Yan, Jing Guo, Yujin Kuang, Mingyang Yin, Shiniu Wang and Caoyuan Ma

Sensors 2021, 21(3), 687; https://doi.org/10.3390/s21030687 - 20 Jan 2021

Cited by 22 | Viewed by 4510

Abstract

The driving behavior of bus drivers is related to the safety of all passengers and regulation of urban traffic. In order to analyze the relevant characteristics of speed and acceleration, accurate bus trajectories and patterns are essential for driver behavior analysis and development of effective intelligent public transportation. Exploiting real-time vehicle tracking, this paper develops a platform with vehicle-mounted terminals using differential global navigation satellite system (DGNSS) modules for driver behavior analysis. The DGNSS traces were used to derive the vehicle trajectories, which were then linked to road information to produce speed and acceleration matrices. Comprehensive field tests were undertaken on multiple bus routes in urban environments. The spatiotemporal results indicate that the platform can automatically and accurately extract the driving behavior characteristics. Furthermore, the platform’s visual function can be used to effectively monitor driving risks, such as speeding and fierce acceleration, in multiple bus routes. The details of the platform’s features are provided for intelligent transport system (ITS) design and applications. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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18 pages, 4887 KiB

Open AccessArticle

A Real-Time Trajectory Prediction Method of Small-Scale Quadrotors Based on GPS Data and Neural Network

by Zhao Yang, Rong Tang, Jie Bao, Jiahuan Lu and Zhijie Zhang

Sensors 2020, 20(24), 7061; https://doi.org/10.3390/s20247061 - 10 Dec 2020

Cited by 11 | Viewed by 3196

Abstract

This paper proposes a real-time trajectory prediction method for quadrotors based on a bidirectional gated recurrent unit model. Historical trajectory data of ten types of quadrotors were obtained. The bidirectional gated recurrent units were constructed and utilized to learn the historic data. The prediction results were compared with the traditional gated recurrent unit method to test its prediction performance. The efficiency of the proposed algorithm was investigated by comparing the training loss and training time. The results over the testing datasets showed that the proposed model produced better prediction results than the baseline models for all scenarios of the testing datasets. It was also found that the proposed model can converge to a stable state faster than the traditional gated recurrent unit model. Moreover, various types of training samples were applied and compared. With the same randomly selected test datasets, the performance of the prediction model can be improved by selecting the historical trajectory samples of the quadrotors close to the weight or volume of the target quadrotor for training. In addition, the performance of stable trajectory samples is significantly better than that with unstable trajectory segments with a frequent change of speed and direction with large angles. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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19 pages, 7296 KiB

Open AccessArticle

A Modified Residual-Based RAIM Algorithm for Multiple Outliers Based on a Robust MM Estimation

by Wenbo Wang and Ying Xu

Sensors 2020, 20(18), 5407; https://doi.org/10.3390/s20185407 - 21 Sep 2020

Cited by 9 | Viewed by 2479

Abstract

The residual-based (RB) receiver autonomous integrity monitoring (RAIM) detector is a widely used receiver integrity enhancement technology that has the ability to rapidly respond to outliers. However, the sensitivity and vulnerability of the residuals to the outliers are the weaknesses of the method especially in the case of multi-outlier modes. It is an effective method for enhancing the validity of residuals by robust estimation instead of least squares (LS) estimation. In this paper, a modified RB RAIM detector based on a robust MM estimation with a higher detection performance under multi-outlier modes is presented. A fast subset selection method based on the characteristic slope that could reduce the number of subsets to be calculated is also presented. The experimental results show that the proposed algorithm maintains a more robust performance than the RB RAIM detector based on the LS estimator and M estimator with an IGG III function especially with the increase in the number of outliers. The proposed fast subset selection method can reduce the calculation time by at least 80%, demonstrating the practical application value of the algorithm. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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17 pages, 3635 KiB

Open AccessLetter

A Modified Kalman Filter for Integrating the Different Rate Data of Gyros and Accelerometers Retrieved from Android Smartphones in the GNSS/IMU Coupled Navigation

by Wenlin Yan, Qiuzhao Zhang, Lijuan Wang, Ying Mao, Aisheng Wang and Changsheng Zhao

Sensors 2020, 20(18), 5208; https://doi.org/10.3390/s20185208 - 12 Sep 2020

Cited by 18 | Viewed by 4034

Abstract

Recent study indicates that by using the inertial measurement unit (IMU) sensors inside smartphones, we can obtain similar navigation solutions to the professional ones. However, the sampling rates of the gyros and accelerometers inside some types of smartphones are not set in the same frequencies, i.e., the gyros of “Huawei p40” are in 50 Hz while the accelerometer is 100 Hz. The conventional method is resampling the higher frequency to the lower frequency ones, which means the resampled accelerometer will lose half frequency observations. In this work, a modified Kalman filter was proposed to integrate all these different rate IMU data in the GNSS/IMU-smartphone coupled navigation. To validate the proposed method, a terrestrial test with two different types of android smartphones was done. With the proposed method, a slight improvement of the attitude solutions can be seen in the experiments under the GNSS open-sky condition, and the obvious improvement of the attitude solutions can be witnessed at the simulated GNSS denied situation. The improvements by 45% and 23% of the horizontal position accuracy can be obtained from the experiments under the GNSS outage of 50 s in a straight line and 30 s in a turning line, respectively. Full article

(This article belongs to the Special Issue High Performance Positioning, Navigation and Timing for Mobile Platforms)

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