Stability of CubeSat Clocks and Their Impacts on GNSS Radio Occultation

Global Navigation Satellite Systems’ radio occultation (GNSS-RO) provides the upper troposphere-lower stratosphere (UTLS) vertical atmospheric profiles that are complementing radiosonde and reanalysis data. Such data are employed in the numerical weather prediction (NWP) models used to forecast global weather as well as in climate change studies. Typically, GNSS-RO operates by remotely sensing the bending angles of an occulting GNSS signal measured by larger low Earth orbit (LEO) satellites. However, these satellites are faced with complexities in their design and costs. CubeSats, on the other hand, are emerging small and cheap satellites; the low prices of building them and the advancements in their components make them favorable for the GNSS-RO. In order to be compatible with GNSS-RO requirements, the clocks of the onboard receivers that are estimated through the precise orbit determination (POD) should have short-term stabilities. This is essential to correctly time tag the excess phase observations used in the derivation of the GNSS-RO UTLS atmospheric profiles. In this study, the stabilities of estimated clocks of a set of CubeSats launched for GNSS-RO in the Spire Global constellation are rigorously analysed and evaluated in comparison to the ultra-stable oscillators (USOs) onboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-2) satellites. Methods for improving their clock stabilities are proposed and tested. The results (i) show improvement of the estimated clocks at the level of several microseconds, which increases their short-term stabilities, (ii) indicate that the quality of the frequency oscillator plays a dominant role in CubeSats’ clock instabilities, and (iii) show that CubeSats’ derived UTLS (i.e., tropopause) atmospheric profiles are comparable to those of COSMIC-2 products and in situ radiosonde observations, which provided external validation products. Different comparisons confirm that CubeSats, even those with unstable onboard clocks, provide high-quality RO profiles, comparable to those of COSMIC-2. The proposed remedies in POD and the advancements of the COTS components, such as chip-scale atomic clocks and better onboard processing units, also present a brighter future for real-time applications that require precise orbits and stable clocks.

Tectonic Context and Possible Triggering of the 2019–2020 Puerto Rico Earthquake Sequence

An historically unprecedented seismic moment was released by crustal events of the 2019–2020 earthquake sequence near southwest Puerto Rico. The sequence involved at least two, and perhaps three interacting fault systems. The largest Mw 6.4 event was likely triggered by left lateral strike-slip events along the eastern extension of the North Boquerón Bay-Punta Montalva fault zone. The mainshock occurred in a normal fault zone that extends into a region where previous studies documented extensional deformation, beyond the Ponce fault and the Bajo Tasmanian fault. Coulomb stress changes by the mainshock may have triggered further normal-faulting aftershocks, left lateral strike-slip events in the region where these two fault zones interacted, and possibly right lateral strike-slip aftershocks along a third structure extending southward, the Guayanilla fault zone. Extension directions of the seismic sequence are consistently north-northwest–south-southeast-oriented, in agreement with the Global Navigation Satellite Systems-inferred motion direction of eastern Hispaniola relative to western Puerto Rico, and with crustal stress estimates for the overriding plate boundary zone.

An eLoran Signal Cycle Identification Method Based on Joint Time–Frequency Domain

The eLoran system is an international standardized positioning, navigation, and timing service system, which can complement global navigation satellite systems to cope with navigation and timing warfare. The eLoran receiver measures time-of-arrival (TOA) through cycle identification, which is key in determining timing and positioning accuracy. However, noise and skywave interference can cause cycle identification errors, resulting in TOA-measurement errors that are integral multiples of 10 μs. Therefore, this article proposes a cycle identification method in the joint time–frequency domain. Based on the spectrum-division method to determine the cycle identification range, the time–domain peak-to-peak ratio and waveform matching are used for accurate cycle identification. The performance of the method is analyzed via simulation. When the signal-to-noise ratio (SNR) ≥ 0 dB and skywave-to-groundwave ratio (SGR) ≤ 23 dB, the success rate of cycle identification is 100%; when SNR ≥ −13 dB and SGR ≤ 23 dB, the success rate exceeds 75%. To verify its practicability, the method was implemented in the eLoran receiver and tested at three test sites within 1000 km using actual signals emitted by an eLoran system. The results show that the method has a high identification probability and can be used in modern eLoran receivers to improve TOA-measurement accuracy.

Evaluation of Real-Time Kinematic Positioning and Deformation Monitoring Using Xiaomi Mi 8 Smartphone

Modern low-cost electronic devices can achieve high precision for global navigation satellite systems (GNSSs) and related applications. Recently, the pseudo-range and carrier phase have been directly obtained from a smartphone to establish a professional-level surveying device. Although promising results have been obtained by linking to an external GNSS antenna, the real-time kinematic (RTK) positioning performance requires further improvement when using the embedded smartphone antenna. We first investigate the observation quality characteristics of the Xiaomi Mi 8 smartphone. The carrier-to-noise-density ratio of L5/E5a signals is below that of L1/E1 signals, and the cycle slip and loss of lock are severe, especially for L5/E5a signals. Therefore, we use an improved stochastic model and ambiguity-resolution strategies to improve the short-baseline RTK positioning accuracy. Experimental results show that the ambiguity fixing rate can reach approximately 90% in 3 h of observations when using the embedded antenna, while the GPS/Galileo/BDS single-frequency combination is more suitable for smartphones. On the other hand, convergence takes 10–30 min, and the RTK positioning accuracy can reach 1 and 2 cm along the horizontal and vertical directions, respectively, if ambiguity is resolved correctly. Moreover, we verify the feasibility of using a mass-produced smartphone for deformation monitoring. Results from a simulated dynamic deformation experiment indicate that a smartphone can recognise deformations as small as 2 cm.

Rapid Static Positioning Using a Four System GNSS Receivers in the Forest Environment

Global Navigation Satellite Systems (GNSS) are crucial elements used in forest inventories. Forest metrics modeling efficacy depends on the accuracy of determining sample plot locations by GNSS. As of 2021, the GNSS consists of 120 active satellites, ostensibly improving position acquisition in forest conditions. The main idea of this article was to evaluate GIS-class and geodetic class GNSS receivers on 33 control points located in the forest. The main assumptions were operating on four GNSS systems (GPS, GLONASS, Galileo, and BeiDou), keeping a continuous online connection to the network of reference stations, maintaining occupation time-limited to 60 epochs, and repeating all the measurements three times. Rapid static positioning was tested, as it compares the true performance of the four GNSS systems receivers. Statistical differences between the receivers were confirmed. The GIS-class receiver achieved an accuracy of 1.38 m and a precision of 1.29 m, while the geodetic class receiver reached 0.74 m and 0.91 m respectively. Even though the research was conducted under the same data capture conditions, the large variability of positioning results were found to be caused by cycle slips and the multipath effect.

Security that Matters: General Knowledge and Correlations in the Context of Applied Satellite Navigation, Specific Interference-Events and the Use of the GNSS-Technology

Navigation through global navigation satellite systems (GNSS) has become an indispensable part of modern life with threats such as GNSS interference, making it necessary to uncover relevant psychological aspects in the context of the GNSS construct, diverse interference events, and the use of related technologies. A total of n = 122 subjects participated in an online survey, which included scales and specifically constructed items on GNSS usage, acceptance, dependence, and self-assessed sense of direction and relevance of basic psychological needs. In addition, frequently emphasized factors influencing acceptance and use of diverse technologies were recorded according to the Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al., 2003). Correlation analyses showed that the frequency of GNSS use was associated with both effort expectation of appropriate technologies, hedonistic motivation, habits of using GNSS-enabled devices, and specific aspects of mobility. In terms of reported GNSS dependency, negative correlations were found with self-assessed orientation ability. It was also possible to identify voluntariness in the use of related technologies, the age of the users, and the relevance of self-determination as essential variables in the context of GNSS use. The results underline the need for further investigation of psychological aspects and contribute to existing discussions in the context of various threat scenarios.

Land Subsidence in the Texas Coastal Bend: Locations, Rates, Triggers, and Consequences

Land subsidence and sea level rise are well-known, ongoing problems that are negatively impacting the entire Texas coast. Although ground-based monitoring techniques using long-term global navigation satellite systems (GNSS) records provide accurate subsidence rates, they are labor intensive, expensive, time-consuming, and spatially limited. In this study, interferometric synthetic aperture radar (InSAR) data and techniques were used to map the locations and quantify rates of land subsidence in the Texas Coastal Bend region during the period from October 2016 to July 2019. InSAR-derived land subsidence rates were then validated and calibrated against GNSS-derived rates. The factors controlling the observed land subsidence rates and locations were investigated. The consequences of spatial variability in land subsidence rates in Coastal Bend were also examined. The results indicated that: (1) land subsidence rates in the Texas Coastal Bend exhibited spatial variability, (2) InSAR-derived land subsidence rates were consistent with GNSS-derived deformation rates, (3) land subsidence in the Texas Coastal Bend could be attributed mainly to hydrocarbon and groundwater extraction as well as vertical movements along growth faults, and (4) land subsidence increased both flood frequency and severity in the Texas Coastal Bend. Our results provide valuable information regarding not only land deformation rates in the Texas Coastal Bend region, but also the effectiveness of interferometric techniques for other coastal rural areas around the globe.

A Survey of Localization Methods for Autonomous Vehicles in Highway Scenarios

In the context of autonomous vehicles on highways, one of the first and most important tasks is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take into account the information from several sensors and fuse them with data coming from road maps. The localization problem on highways can be distilled into three main components. The first one consists of inferring on which road the vehicle is currently traveling. Indeed, Global Navigation Satellite Systems are not precise enough to deduce this information by themselves, and thus a filtering step is needed. The second component consists of estimating the vehicle’s position in its lane. Finally, the third and last one aims at assessing on which lane the vehicle is currently driving. These two last components are mandatory for safe driving as actions such as overtaking a vehicle require precise information about the current localization of the vehicle. In this survey, we introduce a taxonomy of the localization methods for autonomous vehicles in highway scenarios. We present each main component of the localization process, and discuss the advantages and drawbacks of the associated state-of-the-art methods.

How to make a multi-billion dollar thermometer

The United States’ Global Positioning System (GPS), and similar geolocation systems such as Galileo, GLONASS, and Beidou are used by people all over the globe. Modern receivers of these global navigation satellite systems can track multiple satellites from different constellations. Casual, non-technical users are probably aware that the positional information provided is typically accurate to within a few meters. We could expect physics students to infer that, because these systems rely on the travel time of radio signals, this implies time measurement accuracy on the scale of tens of nanoseconds. This feature has led to GPS-enabled Internet time servers providing stratum 1 accuracy for under $1000. In this paper, we will show that we can couple a GPS unit to a field programmable gate array (FPGA) to determine the temperature in a room. The more serious application of this GPS-FPGA pairing is to provide precise time-stamping of events, thereby synchronizing data collection between stations across a room or across the globe.

Comparison of Different Hardware Configurations for 2D SLAM Techniques Based on Google Cartographer Use Case

One of the most challenging topics in Robotics is Simultaneous Localization and Mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others LiDARs (Light Detection and Ranging), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.g. the ones available in the Inertial Measurement Units and wheel odometry sensors. Evaluation of different SLAM algorithms and possible hardware configurations in real environments is time consuming and expensive. For that reason, in this paper we evaluate the performance of different hardware configuration used with Google Cartographer SLAM algorithms in simulation framework proposed in 1. Our use case is an actual robot used for room decontamination. The results show that for our robot the best hardware configuration consists of three LiDARs 2D, IMU and wheel odometry sensors. The proposed simulation-based methodology is a cost-effective alternative to real-world evaluation. It allows easy automation and provides access to precise ground truth. It is especially beneficial in the early stages of product design and to reduce the number of necessary real-life tests and hardware configurations.