Assessment of Noise of MEMS IMU Sensors of Different Grades for GNSS/IMU Navigation.

Inertial measurement units (IMUs) are key components of various applications including navigation, robotics, aerospace, and automotive systems. IMU sensor characteristics have a significant impact on the accuracy and reliability of these applications. In particular, noise characteristics and bias stability are critical for proper filter settings to perform a combined GNSS/IMU solution. This paper presents an analysis based on the Allan deviation of different IMU sensors that correspond to different grades of micro-electromechanical systems (MEMS)-type IMUs in order to evaluate their accuracy and stability over time. The study covers three IMU sensors of different grades (ascending order): Rokubun Argonaut navigator sensor (InvenSense TDK MPU9250), Samsung Galaxy Note10 phone sensor (STMicroelectronics LSM6DSR), and NovAtel PwrPak7 sensor (Epson EG320N). The noise components of the sensors are computed using overlapped Allan deviation analysis on data collected over the course of a week in a static position. The focus of the analysis is to characterize the random walk noise and bias stability, which are the most critical for combined GNSS/IMU navigation and may differ or may not be listed in manufacturers' specifications. Noise characteristics are calculated for the studied sensors and examples of their use in loosely coupled GNSS/IMU processing are assessed. This work proposes a structured and reproducible approach for working with sensors for their use in navigation tasks in combination with GNSS, and can be used for sensors of different levels to supplement missing or incorrect sensor manufacturers' data.

Cloud-Based Single-Frequency Snapshot RTK Positioning.

With great potential for being applied to Internet of Things (IoT) applications, the concept of cloud-based Snapshot Real Time Kinematics (SRTK) was proposed and its feasibility under zero-baseline configuration was confirmed recently by the authors. This article first introduces the general workflow of the SRTK engine, as well as a discussion on the challenges of achieving an SRTK fix using actual snapshot data. This work also describes a novel solution to ensure a nanosecond level absolute timing accuracy in order to compute highly precise satellite coordinates, which is required for SRTK. Parameters such as signal bandwidth, integration time and baseline distances have an impact on the SRTK performance. To characterize this impact, different combinations of these settings are analyzed through experimental tests. The results show that the use of higher signal bandwidths and longer integration times result in higher SRTK fix rates, while the more significant impact on the performance comes from the baseline distance. The results also show that the SRTK fix rate can reach more than 93% by using snapshots with a data size as small as 255 kB. The positioning accuracy is at centimeter level when phase ambiguities are resolved at a baseline distance less or equal to 15 km.

Galileo Broadcast Ephemeris and Clock Errors Analysis: 1 January 2017 to 31 July 2020.

A preliminary analysis of Galileo F/NAV broadcast Clock and Ephemeris is performed in this paper with 43 months of data. Using consolidated Galileo Receiver Independent Exchange (RINEX) navigation files, automated navigation data monitoring is applied from 1 January 2017 to 31 July 2020 to detect and verify potential faults in the satellite broadcast navigation data. Based on these observation results, the Galileo Signal-in-Space is assessed, and the probability of satellite failure is estimated. The Galileo nominal ranging accuracy is also characterized. Results for GPS satellites are included in the paper to compare Galileo performances with a consolidated constellation. Although this study is limited by the short observation period available, the analysis over the last three-year window shows promising results with Psat = 3.2 × 10-6/sat, which is below the value of 1 × 10-5 stated by the Galileo commitments.

Special Issue on GNSS Data Processing and Navigation.

Global Navigation Satellite System (GNSS) data can be used in a myriad of ways. The current number of applications exceed by far those originally GNSS was designed for. As an example, the present Special Issue on GNSS Data Processing and Navigation compiles 14 international contributions covering several aspects of GNSS research. This Editorial summarizes the whole special issue grouping the contributions under four different, but related topics.

EGNOS 1046 Maritime Service Assessment.

The present contribution evaluates how the European Geostationary Navigation Overlay System (EGNOS) meets the International Maritime Organization (IMO) requirements established in its Resolution A.1046 for navigation in harbor entrances, harbor approaches, and coastal waters: 99.8% of signal availability, 99.8% of service availability, 99.97% of service continuity and 10 m of horizontal accuracy. The data campaign comprises two years of data, from 1 May 2016 to 30 April 2018 (i.e., 730 days), involving 108 permanent stations located within 20 km of the coast or in islands across the EGNOS coverage area, EGNOS corrections, and cleansed GPS broadcast navigation data files. We used the GNSS Laboratory Tool Suite (gLAB) to compute the reference coordinates of the stations, the EGNOS solution, as well as the EGNOS service maps. Our results show a signal availability of 99.999%, a horizontal accuracy of 0.91 m at the 95th percentile, and the regions where the IMO requirements on service availability and service continuity are met. In light of the results presented in the paper, the authors suggest the revision of the assumptions made in the EGNOS Maritime Service against those made in EGNOS for civil aviation; in particular, the use of the EGNOS Message Type 10.

Helmert Variance Component Estimation for Multi-GNSS Relative Positioning.

The Multi-constellation Global Navigation Satellite System (Multi-GNSS) has become the standard implementation of high accuracy positioning and navigation applications. It is well known that the noise of code and phase measurements depend on GNSS constellation. Then, Helmert variance component estimation (HVCE) is usually used to adjust the contributions of different GNSS constellations by determining their individual variances of unit weight. However, HVCE requires a heavy computation load. In this study, the HVCE posterior weighting was employed to carry out a kinematic relative Multi-GNSS positioning experiment with six short-baselines from day of year (DoY) 171 to 200 in 2019. As a result, the HVCE posterior weighting strategy improved Multi-GNSS positioning accuracy by 20.5%, 15.7% and 13.2% in east-north-up (ENU) components, compared to an elevation-dependent (ED) priori weighting strategy. We observed that the weight proportion of both code and phase observations for each GNSS constellation were consistent during the entire 30 days, which indicates that the weight proportions of both code and phase observations are stable over a long period of time. It was also found that the quality of a phase observation is almost equivalent in each baseline and GNSS constellation, whereas that of a code observation is different. In order to reduce the time consumption of the HVCE method without sacrificing positioning accuracy, the stable variances of unit weights of both phase and code observations obtained over 30 days were averaged and then frozen as a priori information in the positioning experiment. The result demonstrated similar ENU improvements of 20.0%, 14.1% and 11.1% with respect to the ED method but saving 88% of the computation time of the HCVE strategy. Our study concludes with the observations that the frozen variances of unit weight (FVUW) could be applied to the positioning experiment for the next 30 days, that is, from DoY 201 to 230 in 2019, improving the positioning ENU accuracy of the ED method by 18.1%, 13.2% and 10.6%, indicating the effectiveness of the FVUW.