Welcome to the Fall 2023 issue of NAVIGATION. In this bumper issue, we feature 16 articles reporting on significant advances in PNT research covering topics such as improved modeling the ionosphere and further reducing its impact on positioning and navigation, the authentication of augmentation systems and GNSS navigation messages, improving and supplementing GNSS use in difficult reception environments, and the navigation of a spacecraft in the vicinity of the moon.
ION promotes the research of journal authors in a variety of ways including video abstracts hosted on the ION website. The latest video abstracts are documented below. You can find the video abstract for any recently published article under the article’s supplemental menu item on the journal’s website. ION also engages with the PNT community, through its webinar series, to highlight current topics of interest to the community. The most recent webinars are also documented below.
VIDEO ABSTRACTS
Video Abstracts allow authors to present their research in their own words. This multimedia format communicates the background and context of authors’ research in a quick and easy way, elevating research from simple print delivery.
Video for “Accurate Covariance Estimation for Pose Data from Iterative Closest Point Algorithm”
By Rick H. Yuan, Clark N. Taylor, and Scott L. Nykl
(https://navi.ion.org/content/70/2/navi.562/tab-supplemental)
Abstract: One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is introduced.
Article Citation: Yuan, H. R., Taylor, C. N., & Nykl, S. L. (2023). Accurate covariance estimation for pose data from iterative closest point algorithm. NAVIGATION, 70(2). https://doi.org/10.33012/navi.562
Video for “Resilient Smartphone Positioning Using Native Sensors and PPP Augmentation”
By Sihan Yang, Ding Yi, Sudha Vana, and Sunil Bisnath
(https://navi.ion.org/content/70/2/navi.567/tab-supplemental)
Abstract: With the ubiquitous use of global navigation satellite system (GNSS) receivers, navigation solutions from smartphones have become integrated in various applications throughout our lives. These ultra-low-cost GNSS receivers have the drawbacks of insufficient observations and poorer signal reception quality than higher-cost receivers. Since 2016, smartphones using the Android operating system have been able to output raw GNSS pseudorange and carrier-phase measurements, thereby enabling improved navigation capabilities. The realm of sensor fusion is also being explored by using smartphone sensors, including inertial measurement units (IMUs), cameras, and other fusion techniques. The research presented herein deployed only IMU and GNSS sensors native to existing smartphones and achieved a standalone solution using PPP/IMU integration that outperformed standard techniques. In open-sky vehicle experiments, the sensor integration algorithm achieved 1.6-m horizontal RMS, thus reducing 80% of horizontal errors in GNSS-challenging environments through a tightly coupled GNSS-PPP solution that is yet to appear in publications.
Article Citation: Yang, S., Yi, D., Vana, S., & Bisnath, S. (2023). Resilient smartphone positioning using native and PPP augmentation. NAVIGATION, 70(2). https://doi.org/10.33012/navi.567
Video for “Optimized Position Estimation in Mobile Multipath Environments Using Machine Learning”
By Nesreen I. Ziedan
(https://navi.ion.org/content/70/2/navi.569/tab-supplemental)
Abstract: The positioning accuracy of global navigation satellite system receivers is frequently degraded in urban areas due to reflected signals. A moving receiver faces additional challenges because it needs to adjust to changes in the statuses of the signals received, including line-of-sight (LOS), multipath, non-LOS, or invisible. This paper proposes two new algorithms that can be used to enhance the accuracy of a moving receiver. The first algorithm is called Optimized Position Estimation (OPE). The OPE algorithm estimates the most likely paths and identifies the one with the optimal weight. The second algorithm is called Intelligent Signal Status Estimation (ISE). The ISE algorithm utilizes a self-organizing map machine-learning algorithm to estimate the probability of a change in signal status. The algorithms are tested using global positioning system C/A signals, which have over 50 changes in their statuses. The results obtained using these algorithms reveal that the accuracy is enhanced by as much as 96.3% (i.e., a 27-fold improvement) when compared to results using a conventional navigation algorithm.
Article Citation: Ziedan, N. I. (2023). Optimized position estimation in mobile multipath environments using machine learning. NAVIGATION, 70(2). https://doi.org/10.33012/navi.569
Video for “Multi-Parameter Adaptive Notch Filter (MPANF) for Enhanced Interference Mitigation”
By Johannes Rossouw van der Merwe, Iñigo Cortés, Fabio Garzia, Alexander Rügamer, and Wolfgang Felber
(https://navi.ion.org/content/70/2/navi.570/tab-supplemental)
Abstract: Interference signals degrade global navigation satellite system (GNSS) performance and must be mitigated. Chirp signals can be mitigated with an adaptive notch filter (ANF), but the dynamic behavior limits performance. An ANF determines the instantaneous frequency and removes interference with a notch filter. However, there are several limitations. In this article, we propose a multi-parameter adaptive notch filter (MPANF) approach that significantly enhances conventional ANFs. First, it uses an loop-bandwidth control algorithm (LBCA) to alter the loop bandwidth of an frequency-locked loop (FLL)-based adaptation algorithm to facilitate superior tracking agility-to-precision trade-off. Second, it dynamically adjusts the notch depth to switch on interference mitigation or pass the signal through. Third, it modifies the notch width to accommodate tracking stability and optimize interference signal suppression to GNSS signal removal. The presented MPANF exhibits superior performance against chirp signals, including faster response to jump discontinuities.
Article Citation: van der Merwe, J. R., Cortés, I., Garzia, F., Rügamer, A., & Felber, W. (2023). Multi-Parameter adaptive notch filter (MPANF) for enhanced interference mitigation. NAVIGATION, 70(2). https://doi.org/10.33012/navi.570
Video for “Perspectives on the Systematic (Type B) Uncertainties of UTC-UTC(k)”
By Demetrios Matsakis
(https://navi.ion.org/content/70/2/navi.571/tab-supplemental)
Abstract: The systematic uncertainties in the difference between Coordinated Universal Time (UTC) and UTC realizations like UTC(k) are analyzed with a semi-historical algorithm using the uncertainties of the calibrations of only the extant time-transfer links and their covariance with clock predictions. It is important that the network has matured through recalibration, and that UTC was once generated with only GPS. This approach covers all types of links, including redundant links and cross links. The uncertainties of non-GPS links depend on the uncertainties of the pivot lab’s GPS system and the other system(s) used in the link. Clock predictions of labs not linked by GPS must be adjusted whenever the pivot lab’s GPS receiver is recalibrated. The resulting uncertainties differ by up to 45% from the results given in a recently published alternative proposal. Aging of the uncertainties leads to a blending of this approach with the current algorithm used by the International Bureau of Weights and Measures (BIPM).
Article Citation: Matsakis, D. (2023). Perspectives on the systematic (Type B) uncertainties of UTC-UTC(k). NAVIGATION, 70(2), https://doi.org/10.33012/navi.571
Video for “Low-Cost, Triple-Frequency, Multi-GNSS PPP and MEMS IMU Integration for Continuous Navigation in Simulated Urban Environments”
By Sudha Vana and Sunil Bisnath
(https://navi.ion.org/content/70/2/navi.578/tab-supplemental)
Abstract: In this research, a next-generation, low-cost triple-frequency GNSS, microelectromechanical (MEMS) based inertial measurement unit (IMU), and a patch antenna was used to obtain decimeter-level accuracy in a suburban and urban environment. A unique combination of the low-cost hardware and software constraining was used to bridge the GNSS gaps in an urban environment to provide a continuous, accurate, and reliable position solution that is novel and has not been previously published. The low-cost navigation system demonstrates less than a decimeter-level accuracy in the presence of a sufficient number of satellites. During half a minute of introduced GNSS signal loss, the overall rms of the algorithm is 10–40% better than dual-frequency PPP with IMU, as the satellite availability reduces. The results obtained during partial GNSS availability indicate a significant step forward in the low-cost navigation area for applications like low-cost autonomous vehicles, intelligent transportation systems, etc. that demand a decimeter level of accuracy.
Article Citation: Vana, S., & Bisnath, S. (2023). Low-cost, triple-frequency, multi-GNSS PPP and MEMS IMU integration for continuous navigation in simulated urban environments. NAVIGATION, 70(2). https://doi.org/10.33012/navi.578
Video for “Probabilistic Map Matching for Robust Inertial Navigation Aiding”
By Xuezhi Wang, Christopher Gilliam, Allison Kealy, John Close, and Bill Moran
(https://navi.ion.org/content/70/2/navi.583/tab-supplemental)
Abstract: Robust aiding of inertial navigation systems in GNSS-denied environments is critical for the removal of accumulated navigation error caused by the drift and bias inherent in inertial sensors. One way to perform such an aiding uses matching of geophysical measurements, such as gravimetry, gravity gradiometry or magnetometry, with a known geo-referenced map. Although simple in concept, this map-matching procedure is challenging: The measurements themselves are noisy, their associated spatial location is uncertain, and the measurements may match multiple points within the map (i.e., non-unique solution). In this paper, we propose a probabilistic multiple-hypotheses tracker to solve the map-matching problem and allow robust inertial navigation aiding. Our approach addresses the problem both locally, via probabilistic data association, and temporally by incorporating the underlying platform kinematic constraints into the tracker. The estimated platform position from the output of map matching is then integrated into the navigation state using an unscented Kalman filter. Additionally, we present a statistical measure of local map information density — the map feature variability — and use it to weight the output covariance of the proposed algorithm. The effectiveness and robustness of the proposed algorithm are demonstrated using a navigation scenario involving gravitational map matching.
Article Citation: Wang, X., Gilliam, C., Kealy, A., Close, J., & Moran, B. (2023). Probabilistic map matching for robust inertial navigation aiding. NAVIGATION, 70(2). https://doi.org/10.33012/navi.583
Video for “Performance of GNSS-SDR for IRNSS L5 Signals Using a Low-Cost RF Front-End”
By Chittimalla Srinu and Laxminarayana Parayitam
(https://navi.ion.org/content/70/2/navi.573/tab-supplemental)
Abstract: The GNSS software receiver has evolved as a promising tool for researchers and developers because of its flexibility and reconfigurability. As modernized GNSS signals have been emerging day by day, the need to adapt the software receiver to address the upcoming challenges of GNSS navigation has become inevitable. The main aim of this work is to assess the existing Global Navigation Satellite System Software Defined Receiver (GNSS-SDR) tool for Indian Regional Navigation Satellite System (IRNSS) signals using a low-cost RTL-SDR front-end. The IRNSS software receiver chain is developed using GNSS-SDR code and framework. GNSS-SDR is an open-source tool developed by the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) of Spain. This work is useful for carrying out various GNSS-related applications using IRNSS signals in the future and paves the way for further research and development of the IRNSS system by using it as a research/academic tool.
Article Citation: Srinu, C., & Parayitam, L. (2023). Performance of GNSS-SDR for IRNSS L5 signals using a low-cost RF front-end. NAVIGATION, 70(2). https://doi.org/10.33012/navi.573
Video for “PPP/PPP-RTK Message Authentication”
By Ignacio Fernandez-Hernandez, Rui Hirokawa, Vincent Rijmen, and Yusuke Aikawa
(https://navi.ion.org/content/70/2/navi.579/tab-supplemental)
Abstract: This paper analyzes candidate schemes for PPP/PPP-RTK (precise point positioning/real-time kinematic) data authentication. Asymmetric schemes are proposed based on existing standards and compatible with GNSS messages. Post-quantum cryptographic signatures are also reviewed and discussed. Two schemes are selected for analysis: digital signature (DS) based on ECDSA, and delayed disclosure (DD) based on a hybrid scheme using the TESLA protocol. Each of them is described in detail for both Galileo high-accuracy service and QZSS centimeter-level accuracy service. The performance of the schemes in terms of time to receive the corrections message and increase in the age of data (ΔAOD) is analyzed. The analysis is complemented by a review of the CPU consumption at receiver level.
Article Citation: Fernandez-Hernandez, I., Hirokawa, R., Rijmen, V., & Aikawa, Y. (2023). PPP/PPP-RTK message authentication. NAVIGATION, 70(2). https://doi.org/10.33012/navi.579
Video for “Ambiguity-Fixing in Frequency-Varying Carrier Phase Measurements: Global Navigation Satellite System and Terrestrial Examples”
By A. Khodabandeh and P.J.G. Teunissen
(https://navi.ion.org/content/70/2/navi.580/tab-supplemental)
Abstract: Carrier phase signals are considered among the key observations in global navigation satellite systems (GNSSs) and several other high-precision interferometric measurement systems. However, these ultra-precise measurements are not fully exploited when the integerness of their inherent ambiguities is discarded during the estimation process. Provided that the integer-estimable functions of their phase ambiguities are properly identified, integer ambiguity resolution (IAR) can be utilized to benefit their parameter solutions. For the GNSS code division multiple access systems with transmitters that broadcast carrier phase signals on identical frequencies, these integer-estimable functions have been characterized and are well-known as double differenced ambiguities. However, this is not the case with “frequency-varying” carrier phase signals that are broadcast by GLONASS satellites, Low-Earth-Orbiting communication satellites, or cellular long-term evolution (LTE) transmitters. This study aims to present full-rank models that can be used to identify integer-estimable ambiguity functions, thereby bringing the observation equations of frequency-varying carrier phase measurements into an IAR-applicable form. Our analytical results are supported by several numerical examples, including GNSS and terrestrial-based IAR as well as a new set of “inter-frequency” integer ambiguities that this study discovers in Galileo multi-frequency carrier phase signals.
Article Citation: Khodabandeh, A., & Teunissen, P. J. G. (2023). Ambiguity-fixing in frequency-varying carrier phase measurements: Global navigation satellite system and terrestrial examples. NAVIGATION, 70(2). https://doi.org/10.33012/navi.580
Video for “Real-Time Ionosphere Prediction Based on IGS Rapid Products Using Long Short-Term Memory Deep Learning”
By Jianping Chen and Yang Gao
(https://navi.ion.org/content/70/2/navi.581/tab-supplemental)
Abstract: High-precision ionospheric corrections are essential for precise positioning using low-cost single-frequency GNSS receivers. Although Real-Time Global Ionosphere Maps (RT-GIMs) are available from the International GNSS Service (IGS), their ionospheric predictions continue to rely on networks of globally-distributed GNSS stations and real-time data links. In this paper, we develop a regional real-time ionospheric prediction model based on a long short-term memory (LSTM) deep learning method. Because the GIMs from the IGS are used as prediction bases, the requirement for real-time GNSS data-links is eliminated. A comparison of the ionospheric predictions generated over 24 hours by the proposed method and the IGS GIM revealed a prediction accuracy root mean square error of 0.8 TECU. These results suggest that the proposed model may be suitable for use in real-time applications.
Article Citation: Chen, J., & Gao, Y. (2023). Real-time ionosphere prediction based on IGS rapid products using long short-term memory deep learning. NAVIGATION, 70(2). https://doi.org/10.33012/navi.581
Video for “Performance-Based GNSS Satellite Selection: A Linear Matrix Inequality (LMI) Approach”
By Jyh-Ching Juang
(https://navi.ion.org/content/70/2/navi.582/tab-supplemental)
Abstract: In the multi-GNSS era, the observable satellites are more than needed and the benefit of processing more than enough satellites is marginal. It is thus desired to select a subset of satellites so that the receiver operation complexity and navigation performance can be balanced. In the paper, performance requirements in navigation accuracy and integrity are represented in terms of a performance index and the performance-based satellite selection is to determine the satellite combination to minimize the performance index. A linear matrix inequality (LMI) relaxation approach is developed to solve the problem and render candidates of satellites. The proposed approach quantifies the significance of each satellite on the resulting performance metric and, more importantly, provides a lower bound in satellite selection for performance-based navigation. The generalizations of the proposed approach in multi-epoch satellite selection is also discussed. Examples are provided to illustrate the effectiveness of the proposed approach.
Article Citation: Juang, J-C. (2023). Performance-based GNSS satellite selection: A linear matrix inequality (LMI) approach. NAVIGATION, 70(2). https://doi.org/10.33012/navi.582
WEBINARS
ION Webinars highlight timely and engaging articles published in NAVIGATION and other topics of interest to the PNT community in an interactive virtual presentation.
July 11, 2023 Webinar: Resilient Smartphone Positioning Using Native Sensors and PPP Augmentation
By Sunil Bisnath, Sihan Yang, and Ding Yi
(https://www.ion.org/publications/webinar-bisnath.cfm)
Abstract: With the ubiquitous use of global navigation satellite system (GNSS) receivers, navigation solutions from smartphones have become integrated in various applications throughout our lives. These ultra-low-cost GNSS receivers have the drawbacks of insufficient observations and poorer signal reception quality than higher-cost receivers. Since 2016, smartphones using the Android operating system have been able to output raw GNSS pseudorange and carrier-phase measurements, thereby enabling improved navigation capabilities. The realm of sensor fusion is also being explored by using smartphone sensors, including inertial measurement units (IMUs), cameras, and other fusion techniques. The research presented herein deployed only IMU and GNSS sensors native to existing smartphones and achieved a standalone solution using PPP/IMU integration that outperformed standard techniques. In open-sky vehicle experiments, the sensor integration algorithm achieved 1.6-m horizontal RMS, thus reducing 80% of horizontal errors in GNSS-challenging environments through a tightly coupled GNSS-PPP solution that is yet to appear in publications.
Article Citation: Yang, S., Yi, D., Vana, S., & Bisnath, S. (2023). Resilient smartphone positioning using native and PPP augmentation. NAVIGATION, 70(2). https://doi.org/10.33012/navi.567
June 27, 2023 Webinar: The 2023 Autonomous Snowplow Competition First Place Team - Case Western Reserve University “OTTO”
By Shane Riddle and Ian Adams
(https://www.ion.org/publications/webinar-snowplow23.cfm)
Abstract: The 13th Annual Autonomous Snowplow Competition was held January 20-21, 2023 at Dunwoody College in Minneapolis, MN! The purpose of this competition is to challenge university and college students, as well as the general public, to design, build, and operate a fully autonomous snowplow to remove snow from a designated path. The objectives of this competition include encouraging students and individuals to utilize the state of the art in navigation and control technologies to rapidly, accurately, and safely clear a path of snow. Join us to learn how Case Western Reserve University team “OTTO” earned first place - from their innovative design and development strategies - to the specific navigation technology implemented in their vehicle.
May 24, 2023 Webinar: Improved GPS-Based Single-Frequency Orbit Determination for the CYGNSS Spacecraft Using GipsyX
By Penina Axelrad and Alex Conrad
https://www.ion.org/publications/webinar-conrad.cfm
Abstract: This webinar presents methods for the precise orbit determination (POD) of a satellite in the CYGNSS constellation based on available single-frequency GPS code and carrier measurements. The contributions include the development and evaluation of procedures for single-frequency POD with GipsyX, improvement of CYGNSS orbit knowledge, and an assessment of its final accuracy. Ionospheric effects are mitigated using the GRAPHIC processing method, and spacecraft multipath effects are calibrated with an azimuth/elevation-dependent antenna calibration map. The method is demonstrated using comparable data from the GRACE mission, from which we infer the expected accuracy of the CYGNSS results. Processing more than 170 days of data from each mission, a 1s CYGNSS orbit accuracy of 2.8 cm radial, 2.4 cm cross-track, and 6 cm in-track is demonstrated. We expect that achieving this level of performance will expand the set of future scientific investigations that can be undertaken using satellites equipped with single-frequency GNSS.
Article Citation: Conrad, A. V., Axelrad, P., Haines, B., Zuffada, C., & O’Brien, A. (2023). Improved GPS-based single-frequency orbit determination for the CYGNSS spacecraft using GipsyX. NAVIGATION, 70(1). https://doi.org/10.33012/navi.565
April 18, 2023 Webinar: Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS
By Todd E. Humphreys
(https://www.ion.org/publications/webinar-yoder.cfm)
Abstract: Signal quality monitoring (SQM) is a technique utilized by satellite- and ground-based augmentation systems (SBAS/GBAS) to detect potential hazardous deformations in signals and better protect integrity for safety-critical users. The next generation of SBASs will incorporate dual-frequency multi-constellation (DFMC) techniques, for which SQM is particularly important since signal deformations might be the largest source of uncertainty in ranging error after first-order ionospheric delays are eliminated. However, the performance bounds of the traditional multi-correlator-based SQM technique face some challenges because of the raised requirement on detection sensitivity by dual-frequency ionosphere-free measurements and multiple modulation modes of civilian signals from multi-constellation techniques. To mitigate the challenges and improve overall performance, SQM based on chip domain observables (CDOs) is emerging, but has not yet been systematically studied. We propose a design methodology for CDO-based SQM, consisting of derivations and corresponding massive simulations. Correctness and effectiveness are assessed to confirm the methodology, and a simplification process by checking the sensitivity of CDOs is demonstrated in terms of implementation.
Article Citation: Yoder, J. E., & Humphreys, T. E. (2023). Low-cost inertial aiding for deep-urban tightly coupled multi-antenna precise GNSS. NAVIGATION, 70(1). https://doi.org/10.33012/navi.561
HOW TO CITE THIS ARTICLE
Langley, R. B. (2023). Navigator notes: Editorial Highlights from the Editor-in-Chief. NAVIGATION, 70(3). https://doi.org/10.33012/navi.587
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.