S2

There are three ‘pillars’ that define the performance or usefulness of a navigation technologies – cost, accuracy, and continuity. Navigation is a field that has been fascinating humankind for thousands of years and these pillars have been evolving with new technological advancements.  The current market in positioning and navigation is clearly dominated by GNSS. Besides being globally available, it meets two important pillars: accuracy and cost by providing the whole range of navigation accuracies at very low cost. It is also highly portable, has low power consumption, and is well suited for integration with other sensors, communication links, and databases.

At this point in the development of navigation technology, the need for alternative positioning systems only arises because GNSS does meet the continuity pillar as it does not work in all environments. Furthermore, there has been a constant market push to develop navigation systems that are accurate, continuous and easy to afford. Needless to say, that cost, and space constraints are currently driving manufacturers of cars, portable devices (e.g. smartphones), and autonomous systems (e.g. self-driving, drones and agriculture machine systems) systems to investigate and develop next generation of low cost and small size navigation systems to meet the fast-growing autonomous vehicles and location services market demands. This presentation will provide a state of the art and future trends of sensors used for navigation of autonomous vehicles: possibilities, limitations and various design approaches.  Emphasis will be on sensors and technologies that can navigate autonomous vehicles everywhere and at any time independent of weather and light conditions. Some of the current developed and possible future system’s accuracy performance will be demonstrated through different implementations/applications using Propound Positioning Inc technologies.

How to cite: El-Sheimy, N.: Navigation Technologies for Future Autonomous Vehicles, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-55, https://doi.org/10.5194/iag-comm4-2022-55, 2022.

How to cite: Kumar, G., Shah, S., Qian, Y., Pervez, N., and Reid, T.: Computing the GPS Sky-View Factor in Urban Landscapes for Autonomous Driving Simulation, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-4, https://doi.org/10.5194/iag-comm4-2022-4, 2022.

The interest in indoor positioning systems has been rising in the last couple of decades. This interest was further accelerated by the availability of signals of opportunity. The introduction of signals of opportunity into the indoor environments has meant that these widely available technologies can be utilised to achieve higher levels of accuracy and precision for positioning in parking garages, airports, underground locations, large office buildings, and shopping centres. Indoor positioning can also be utilised for emergency services or for Building Information Models (BIM) for purposes such as construction sites or hospital building management. In addition to the need for indoor and outdoor positioning, there is a need to ensure seamless transitions in and out of these different environments. For example, building information from BIM could be utilised for navigation of BIM users that considers the architectural barriers (e.g., for wheelchairs, baby strollers, and transport of large equipment within the facility). For this, a positioning system capable of seamlessly transitioning in and out of buildings is needed. This paper proposes a multi-sensor and cooperative positioning method of seamless environment transition and presents the first architecture concept. For this purpose, Global Navigation Satellite System (GNSS) data are planned to be fused with Ultra Wide-Band (UWB), Inertial Measurement Unit (IMU), Wireless-Fidelity (Wi-Fi), visual camera and LiDAR (Light Detection and Ranging) data. All sensors required for such a positioning system, are already available on modern smartphones commonly used as low-cost platforms for pedestrian navigation and localisation. Newer smartphones are also equipped with LiDAR and UWB chips, which are a future signal of opportunity, just like Wi-Fi currently is. The transition to different environments will be determined based on the UWB anchors called identical anchors that will be used to transition from the global coordinate system for the outdoor environment to the local building environment for positioning in indoor environments. The proposed multi-sensor and cooperative positioning system is expected to be able to achieve decimetre-level accuracy.

How to cite: Gabela, J., Retscher, G., Masiero, A., and Toth, C.: Seamless Indoor-Outdoor Transitioning of Pedestrian Platforms, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-5, https://doi.org/10.5194/iag-comm4-2022-5, 2022.

Satellite-based navigation has been a transformational technology that underpins almost all aspects of modern life. However, there are environments where global navigation satellite systems (GNSS) are not available, for example undersea or underground, and navigation that is robust to GNSS outages are also required for resilient systems.  In this context, we are exploring the potential for quantum diamond magnetometers to be used as aids for inertial measurement units for navigation in GNSS-denied environments.  We perform simulations of the magnetic field measurements combined with probabilistic data association for data mapping; and probabilistic multiple hypotheses (or Viterbi) map matching filters.  These methods are used to explore the expected navigation errors available to scalar and vector magnetometry with diamond at the sensitivities available using current and expected near-term devices.  Here we show some of our preliminary results as well as providing a broader overview of diamond as a quantum magnetometery.

How to cite: Greentree, A., Wang, X., Li, W., gibson, B., Moran, W., Hall, L., Simpson, D., and Kealy, A.: Quantum diamond magnetometry for navigation in GNSS denied environments, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-32, https://doi.org/10.5194/iag-comm4-2022-32, 2022.

Nowadays, in engineering geodesy, Multi-Sensor-Systems (MSSs) have gained a significant amount of interest in data acquisition.  To make sense of the derived data and use it for multiple purposes, such systems need to be localized with respect to a global coordinate system. To do so, the most straightforward way is to use the Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) data. However, such data are usually prone to errors, which should be overcome in the best way possible. One way to do so is to use beneficial information of the surrounding environment, which could be derived by other sensor types rather than the GNSS and IMU. An example of such sensors is a 3D scanner that could be used to capture the static information of a scene such as infrastructures. Moreover, the Ultra-Wide-Band (UWB) units could be used to establish a connection with the other nodes in the same environment and thus help to use potential dynamic information. Fusing various data derived from multiple sensors in a suitable filtering framework is another key to reach a reliable positioning solution. In this work, on the one hand we have explained our recent measurement campaign that was designed to cover the aforementioned aspects for capturing static and dynamic information. On the other hand, we have shown our proposed particle filtering methodology that could lead to reliable positioning solutions for MSSs that move in an inner-city area.

How to cite: Moftizadeh, R., Li, W., Alkhatib, H., and Kealy, A.: Information-Based and Cooperative Positioning of Multi-Sensor-Systems by Extended Kalman Particle Filter, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-56, https://doi.org/10.5194/iag-comm4-2022-56, 2022.

The release of Android Raw GNSS Measurements API in mid-2016 has enabled the reconstruction of pseudorange, carrier-phase, Doppler and carrier-to-noise density (CN0) observables in low-cost, smart devices.  This technical development has opened the door to numerous applications that necessitate increased Position-Velocity-Time (PVT) quality metrics.  However, despite the recent advances in the field, deficiencies inherent to smartphones GNSS antenna and chipset, still account for excessive biases in the raw GNSS observables and for severe multipath effects in the satellite signal.  RAIM (Receiver Autonomous Integrity Monitoring) techniques is one way to monitor and increase the performance of the PVT solution of a GNSS receiver.  It is an augmentation method to detect and eventually reject anomalous (blunders or outliers) measurements and compute protection levels that bound position errors to preset limits.

The implementation of RAIM technique to smartphone GNSS data is very limited and confined only to static positioning scenarios.  This study presents the results obtained from the testing of the classic RAIM technique in a series of kinematic positioning trials in urban environment using two cotemporary smartphone devices (i.e., Xiaomi Mi 8 and One Plus Nord2 5G).  In order to reconstruct a real use case, the smartphones were mounted on the vehicle dashboard.  The reference trajectory was obtained using a tactical grade GNSS/IMU system (NovAtel® PwrPak7, iMAR IMU-FSAS) fixed on the NTUA test vehicle roof-top sensor platform.  

At a pre-processing stage the raw GNSS data have undergone through a Hatch filer.  This step allows to smooth iteratively the noisy code pseudorange measurements using the precise (but ambiguous) phase carrier measurements.  Data analysis includes two processing strategies. We employ the PANG-NAV open-source software released by LabPANG (PArthenope Navigation Group Laboratory) to compute the SPP (Single Point Positioning) solution in two ways.  We produce the standard and the RAIM-based SPP solution using different parameter setups.  The paper presents quantitative results and comparisons between the two smartphone-based solutions and the reference trajectory, and reveal the potential (benefits and limitations) of using the RAIM technique for smartphone positioning.

How to cite: Haxhi, A., Perakis, H., Mpimis, T., and Gikas, V.: Testing of a Combined Hatch Filter / RAIM Algorithm for SPP Smartphone Kinematic Positioning in GNSS Harsh Environments, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-49, https://doi.org/10.5194/iag-comm4-2022-49, 2022.

Interference and jamming of Global Navigation Satellite System (GNSS) signals can lead to inaccurate Position, Velocity and Time (PVT) information which will result in crucial integrity and even security problems. The poor stability and accuracy of the GNSS receivers’ internal clocks, i.e. quartz oscillators, additionally impact the situation since the receiver is not able to detect the spoofing signals due to the low-quality oscillator. High-precision atomic clocks have been utilized to enhance GNSS PVT results. However, its large size, heavy weight and high-power consumption limit its deployment scenarios. Miniature atomic clock (MAC) is a promising alternative that trades off between the frequency stability and the limitations of an atomic clock.

This paper investigates the potential of chip-scale atomic clocks (CSACs) as external clocks of GNSS receivers for fingerprinting the receivers. Fingerprinting is referred to unique receiver clock features and it is characterized by receiver clock’s physical behavior like Allan Deviation (ADEV), Time Interval Error (TIE) and correlation between time series. Thus, derivation from this clock behavior can be used as an indicator for abnormal signal reception, e.g. by spoofing or jamming [1]. We gathered GNSS data observed in various scenarios. A kinematic car experiment was executed on a cart road of the south of Hannover surrounded by farmland six times [2]. About two-hours measurement data was received in 1Hz sampling rate. Another fast-driving experiment was conducted along the route consisting of a highway, an urban area in city Siegen, three tunnels and a small road with plaster, and an about 1.5 hours dataset was collected in 10Hz sampling rate. Then, a flight experiment was realized in Dortmund, with the same equipment setup and receiving about 2.5 hours data in 10Hz sampling rate [3]. For each kinematic experiment, a reference trajectory was obtained from high-quality Inertial Measurement Unit (IMU) and GNSS carrier phase measurements. Correspondingly, the operation setup of the same clocks was tested in a static condition. Each GNSS receiver of the same type (Javad TRE_G3T DELTA) either uses its internal clock, or is connected to one of the five CSACs or an atomic clock. The five CSACs, in chronological order of production, are Microsemi SA.45s CSAC, Jackson Labs CSAC, Jackson Labs OCXO, Spectratime LCR900, Microsemi MAC SA.35m. Besides, the high-precision atomic clock Standard Research Systems (SRS) PRS10 and the high-stability ovenized quartz oscillator SRS SC10 are treated as the reference. The combinations of the features, derived from the above three metrics which relate to the frequency stability of the clocks, are explored. We will show the feasibility of receiver fingerprinting with CSACs in different dynamic environments, and investigate the number of necessary features and the shortest data period to fingerprint the receivers.

[1] Borio, Daniele, et al. "Gnss receiver fingerprinting for security-enhanced applications." Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016). 2016.

[2] Krawinkel, Thomas. “Improved GNSS navigation with chip-scale atomic clocks.” München: Verlag der Bayerischen Akademie der Wissenschaften, 2018. 2018.

[3] Jain, Ankit, and Steffen Schön. "Influence of Receiver Clock Modeling in GNSS-based Flight Navigation: Concepts and Experimental Results." 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS). IEEE, 2020.

How to cite: Lin, Q. and Schön, S.: Feasibility of CSAC-Assisted GNSS Receiver Fingerprinting in Dynamic Environments, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-6, https://doi.org/10.5194/iag-comm4-2022-6, 2022.

Abstract:

 The increasing development of GNSS techniques enables solving geodetic problems on both local and global scales. Parallelly, complex algorithms have been proposed and can also be solved well by Machine Learning (ML). However, ML techniques are sometimes not sensitive enough to gain results with a high probability for some cases, like sparse data or non-stationary GNSS time series. In this study, we use a combination of Human and Machine learning (H&M) to improve the classification performance of continuous GNSS stations. First, 427 permanent GNSS stations are obtained from the EUREF network to train ML models. The models are then applied to classify the quality of 939 continuous observation stations from two projects, EIFEL and IPOC, carried out by the German Research Centre for Geosciences (GFZ), Potsdam, Germany. Next, we independently validate the ML models' reality through a MATLAB program, GNSS metadata, and seismic data. Finally, all data of these 1366 stations are used to re-train the ML models. The main criteria to classify are the number of outliers, jumps in GNSS time series, root mean square errors, observation time-spans, and stability of the crustal motion velocity fields. Applying the approach of the H&M combination improves the performance of the ML models up to 92% while using only ML methods remains ~68%. These ML-based classification models can be applied to estimate the quality of permanent GNSS stations and to manage big databases. The result is the basis for selecting suitable control and monitoring stations in crustal deformation monitoring as well as in civil and industrial applications.

Keywords:

GNSS station classification, Machine learning, Human & Machine learning combination.

How to cite: Le, N., Männel, B., Deng, Z., Luong, T. T., and Schuh, H.: Improving Classification Performance of Continuous GNSS Stations Using a Combination of Human and Machine Learning, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-20, https://doi.org/10.5194/iag-comm4-2022-20, 2022.

The bottleneck of precise GNSS based applications is caused by the receiver antenna and their precision and accuracy. This work aims to contribute to the design of a model and the development of metrics to estimate and evaluate GPS/GNSS antenna calibration values in several networks. At present, there is neither information on the absolute accuracy of antenna calibration values nor a consistent handling of their uncertainties. Rather, these uncertainties repeatedly introduce inaccuracies into time series, which are used to determine global and regional reference frames as a basis for a broad variety of geophysical approaches such as meteorology, hydrography, etc. Several contributions have addressed the issue of the desired quality of GNSS receiver antenna calibrations and the assessment of their impact on GNSS data processing. All approaches lead to the open question regarding the precision and accuracy as well as stability of receiver antenna phase centre corrections. However, comprehensive and fundamental answers to this scientific question are difficult to achieve as complex interactions prevent simple estimation.

In this paper, the authors present results regarding the stability of receiver antenna calibrations in the context of time, calibration facility and strategy to help GNSS operators of regional and global GNSS stations to estimate the impact of calibration values on their sites. The quality of the calibration values also has a direct impact on the derived results, such as the zenith path delay (ZPD). We show that deviations of up to 5 mm for different high-grade antenna types occur. In addition, the normal distribution of pattern differences deviations and systematic effects have been found that lead to drifts and offsets in the parameter domain. The frequency dependence is underlined as well, e.g. L1 versus L2(P) and L2(C). The temporal stability of the calibration values is a fundamental issue, which is discussed in this context. Based on a sample of more than 30 different geodetic grade antennas, we identified variations like drifts and azimuth dependencies with magnitudes of up to 5 mm on each individual frequencies. Furthermore, the stability of the type mean versus individual calibrations shows larger differences on the signals L2 and hence leads to higher variances in the derived ionosphere-free linear combination. The results are examined using PPP time series. The derivation of metrics will be an important step to improve the consistency of regional and global GNSS products.

How to cite: Kersten, T., Dawidowicz, K., Krzan, G., Kröger, J., and Schön, S.: On the design of robust and consistent metrics for the stability of receiver antenna calibration sets, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-25, https://doi.org/10.5194/iag-comm4-2022-25, 2022.

The recent advances in Information Technology (IT) and Micro-Electromechanical Systems (MEMS) technologies and their global adoption in contemporary smartphone and PDA devices enables the introduction of novel approaches for indoor positioning applications that combine multi-sensor capabilities.

In this regard, Radio-frequency (RF), high accuracy ranging technologies operating in the Ultra-Wide Band (UWB) spectrum have recently been introduced in contemporary smartphone devices. Additionally, the adoption of Wi-Fi RTT technology in the most recent smartphone devices facilitates Peer-to-Infrastructure (P2I) medium level accuracy ranging in a widespread and seamless manner together with the standard web access functionality. Applications requiring absolute positioning of moderate to low accuracy may depend on Wi-Fi RTT-only systems, while high-accuracy UWB ranging would facilitate cases demanding safety-critical proximity reliant standards. Positioning architectures optimally utilizing these Two-Way Ranging (TWR) technologies may provide increased coverage and flexibility for indoor conditions in cases that a higher level of accuracy and availability is required.

This study aims at utilizing RF-based range measurements and to combine them optimally into a Pedestrian to Infrastructure (P2I), as well as, Pedestrian to Pedestrian (P2P) collaborative functional model aided by inertial measurements for indoor positioning. The implementation of the proposed approach utilizes simulation-based TWR data from four infrastructure nodes to four roving nodes, whereas operational elements for each technology, such as sampling rate, data formatting and communications scheduling are taken into account.

The distinct working scenarios examined in this study are as follows.  Firstly, we examine separately the performance of the two technological approaches (i.e., Wi-Fi RTT and UWB) for P2I positioning scenarios.  Secondly, we study the performance of the fuse the combined use of these technologies.  For this purpose, we employ a scenario featuring a mixture of Wi-Fi RTT anchor and UWB static rover ranges. Finally, the potential (benefits and limitations) of the inclusion of IMU-based Azimuth information in the KF computation is evaluated for all scenarios. The results obtained from this investigation indicate a potential improvement in position accuracy of the order of 29% and 37% for Wi-Fi RTT/ UWB and Wi-Fi RTT/ UWB/ IMU solutions accordingly.

How to cite: Perakis, H. and Gikas, V.: Towards collaborative multi-agent positioning based on combined Wi-Fi RTT/ UWB/ IMU measurements, 2nd Symposium of IAG Commission 4 “Positioning and Applications”, Potsdam, Germany, 5–8 Sep 2022, iag-comm4-2022-41, https://doi.org/10.5194/iag-comm4-2022-41, 2022.