Antennas and Front-End in GNSS

Antenna and front-end play a key role in global navigation satellite system (GNSS) receivers where multi-frequency and multi-constellation services are used simultaneously to produce high-precision position, navigation, and timing information. Being the first element on the receiver system, specifications on the antenna for multi-constellation GNSS applications can be challenging. Especially, integration of the antenna into the target platform, either mobile or stationary, may severely affect antenna performance. This is usually an issue for small-size antennas where measured stand-alone antenna performance in ideal conditions is usually not descriptive of actual performance on the platform. Furthermore, carrier phase tracking has become popular among algorithm developers to obtain high accuracy and anti-spoofing at the same time which demand minimal phase centre variation of the antenna within the intended GNSS band. Spoofing and jamming of GNSS receivers is a growing concern especially for aerial vehicles with ever-increasing applications of drones. These requirements demand different characteristics on the antenna and front-end than traditional applications. One of the most utilized forms of GNSS antenna is ceramic patch, due to its low height, low cost, and relatively good narrow band performance. Simulations of this particular antenna in terms of axial ratio and impedance bandwidths, axial ratio variation over elevation, and half-power beam width are carried out and discussed with comparison to its counterparts. Another critical part of the receiver is its front-end where huge amount of signal amplification with minimal distortion takes place. Long integration times (>1 ms) in GNSS signal processing also puts severe requirements on the software and temperature-compensated crystal oscillator. For mass production, the front-end should be implemented in the form of an integrated circuit. Front-end architectures from traditional superheterodyne to zero/low-intermediate frequency configurations are presented. Advantages and disadvantages of each configuration are outlined in view of multi-band and multi-standard GNSS receivers

CMOS ASIC Design of Multi-frequency Multi-constellation GNSS Front-ends

With the emergence of the new global navigation satellite systems (GNSSs) such as Galileo, COMPASS and GLONASS, the US Global Positioning System (GPS) has new competitors. This multiplicity of constellations will offer new services and a much better satellite coverage. Public regulated service (PRS) is one of these new services that Galileo, the first global positioning service under civilian control, will offers. The PRS is a proprietary encrypted navigation designed to be more reliable and robust against jamming and provides premium quality in terms of position and timing and continuity of service, but it requires the use of FEs with extended capabilities. The project that this thesis starts from, aims to develop a dual frequency (E1 and E6) PRS receiver with a focus on a solution for professional applications that combines affordability and robustness. To limit the production cost, the choice of a monolithic design in a multi-purpose 0.18 µm complementary metal-oxide-semiconductor (CMOS) technology have been selected, and to reduce the susceptibility to interference, the targeted receiver is composed of two independent FEs. The first ASIC described here is such FEs bundle. Each FE is composed of a radio frequency (RF) chain that includes a low-noise amplifier (LNA), a quadrature mixer, a frequency synthesizer (FS), two intermediate frequency (IF) filters, two variable-gain amplifiers (VGAs) and two 6-bit flash analog-to-digital converters (ADCs). Each have an IF bandwidth of 50 MHz to accommodate the wide-band PRS signals. The FE achieves a 30 dB of dynamic gain control at each channel. The complete receivers occupies a die area of 11.5 mm2 while consuming 115 mW from a supply of a 1.8 V. The second ASIC that targets civilian applications, is a reconfigurable single-channel FE that permits to exploit the interoperability among GNSSs. The FE can operate in two modes: a ¿narrow-band mode¿, dedicated to Beidou-B1 with an IF bandwidth of 8 MHz, and a ¿wide-band mode¿ with an IF bandwidth of 23 MHz, which can accommodate simultaneous reception of Beidou-B1/GPS-L1/Galileo-E1. These two modes consumes respectively 22.85 mA and 28.45 mA from a 1.8 V supply. Developed with the best linearity in mind, the FE shows very good linearity with an input-referred 1 dB compression point (IP1dB) of better than -27.6 dBm. The FE gain is stepwise flexible from 39 dB and to a maximum of 58 dB. The complete FE occupies a die area of only 2.6 mm2 in a 0.18 µm CMOS. To also accommodate the wide-band PRS signals in the IF section of the FE, a highly selective wide-tuning-range 4th-order Gm-C elliptic low-pass filter is used. It features an innovative continuous tuning circuit that adjusts the bias current of the Gm cell¿s input stage to control the cutoff frequency. With this circuit, the power consumption is proportional to the cutoff frequency thus the power efficiency is achieved while keeping the linearity near constant. Thanks to a Gm switching technique, which permit to keep the signal path switchless, the filter shows an extended tuning of the cutoff frequency that covers continuously a range from 7.4 MHz to 27.4 MHz. Moreover the abrupt roll-off of up to 66 dB/octave, can mitigate out-of-band interference. The filter consumes 2.1 mA and 7.5 mA at its lowest and highest cutoff frequencies respectively, and its active area occupies, 0.23 mm2. It achieves a high input-referred third-order intercept point (IIP3) of up to -1.3 dBVRMS

A New Acquisition Algorithm with Elimination Side Peak for All BOC Signals

A new inhibition side peak acquisition (ISPA) algorithm is proposed for binary offset carrier (BOC) modulated signals, which will be utilized in global navigation satellite systems (GNSS). We eliminate all side peaks of the BOC correlation function (CF) by structuring special sequences composed of PRN code and cycle rectangular sequences. The new algorithm can be applied to both generic sine-and cosine-phased BOC signals, as well as to all modulation orders. Theoretical and simulation results demonstrate that the new algorithm can completely eliminate the ambiguity threat in the acquisition process, and it can adapt to lower SNR. In addition, this algorithm is better than the traditional algorithms in acquisition performance and inhibition side peak ability

A New Acquisition Algorithm with Elimination Side Peak for All BOC Signals

A new inhibition side peak acquisition (ISPA) algorithm is proposed for binary offset carrier (BOC) modulated signals, which will be utilized in global navigation satellite systems (GNSS). We eliminate all side peaks of the BOC correlation function (CF) by structuring special sequences composed of PRN code and cycle rectangular sequences. The new algorithm can be applied to both generic sine- and cosine-phased BOC signals, as well as to all modulation orders. Theoretical and simulation results demonstrate that the new algorithm can completely eliminate the ambiguity threat in the acquisition process, and it can adapt to lower SNR. In addition, this algorithm is better than the traditional algorithms in acquisition performance and inhibition side peak ability

Cooperative Relative Positioning for Vehicular Environments

Fahrerassistenzsysteme sind ein wesentlicher Baustein zur Steigerung der Sicherheit im Straßenverkehr. Vor allem sicherheitsrelevante Applikationen benötigen eine genaue Information über den Ort und der Geschwindigkeit der Fahrzeuge in der unmittelbaren Umgebung, um mögliche Gefahrensituationen vorherzusehen, den Fahrer zu warnen oder eigenständig einzugreifen. Repräsentative Beispiele für Assistenzsysteme, die auf eine genaue, kontinuierliche und zuverlässige Relativpositionierung anderer Verkehrsteilnehmer angewiesen sind, sind Notbremsassitenten, Spurwechselassitenten und Abstandsregeltempomate. Moderne Lösungsansätze benutzen Umfeldsensorik wie zum Beispiel Radar, Laser Scanner oder Kameras, um die Position benachbarter Fahrzeuge zu schätzen. Dieser Sensorsysteme gemeinsame Nachteile sind deren limitierte Erfassungsreichweite und die Notwendigkeit einer direkten und nicht blockierten Sichtlinie zum Nachbarfahrzeug. Kooperative Lösungen basierend auf einer Fahrzeug-zu-Fahrzeug Kommunikation können die eigene Wahrnehmungsreichweite erhöhen, in dem Positionsinformationen zwischen den Verkehrsteilnehmern ausgetauscht werden. In dieser Dissertation soll die Möglichkeit der kooperativen Relativpositionierung von Straßenfahrzeugen mittels Fahrzeug-zu-Fahrzeug Kommunikation auf ihre Genauigkeit, Kontinuität und Robustheit untersucht werden. Anstatt die in jedem Fahrzeug unabhängig ermittelte Position zu übertragen, werden in einem neuartigem Ansatz GNSS-Rohdaten, wie Pseudoranges und Doppler-Messungen, ausgetauscht. Dies hat den Vorteil, dass sich korrelierte Fehler in beiden Fahrzeugen potentiell herauskürzen. Dies wird in dieser Dissertation mathematisch untersucht, simulativ modelliert und experimentell verifiziert. Um die Zuverlässigkeit und Kontinuität auch in "gestörten" Umgebungen zu erhöhen, werden in einem Bayesischen Filter die GNSS-Rohdaten mit Inertialsensormessungen aus zwei Fahrzeugen fusioniert. Die Validierung des Sensorfusionsansatzes wurde im Rahmen dieser Dissertation in einem Verkehrs- sowie in einem GNSS-Simulator durchgeführt. Zur experimentellen Untersuchung wurden zwei Testfahrzeuge mit den verschiedenen Sensoren ausgestattet und Messungen in diversen Umgebungen gefahren. In dieser Arbeit wird gezeigt, dass auf Autobahnen, die Relativposition eines anderen Fahrzeugs mit einer Genauigkeit von unter einem Meter kontinuierlich geschätzt werden kann. Eine hohe Zuverlässigkeit in der longitudinalen und lateralen Richtung können erzielt werden und das System erweist 90% der Zeit eine Unsicherheit unter 2.5m. In ländlichen Umgebungen wächst die Unsicherheit in der relativen Position. Mit Hilfe der on-board Sensoren können Fehler bei der Fahrt durch Wälder und Dörfer korrekt gestützt werden. In städtischen Umgebungen werden die Limitierungen des Systems deutlich. Durch die erschwerte Schätzung der Fahrtrichtung des Ego-Fahrzeugs ist vor Allem die longitudinale Komponente der Relativen Position in städtischen Umgebungen stark verfälscht.Advanced driver assistance systems play an important role in increasing the safety on today's roads. The knowledge about the other vehicles' positions is a fundamental prerequisite for numerous safety critical applications, making it possible to foresee critical situations, warn the driver or autonomously intervene. Forward collision avoidance systems, lane change assistants or adaptive cruise control are examples of safety relevant applications that require an accurate, continuous and reliable relative position of surrounding vehicles. Currently, the positions of surrounding vehicles is estimated by measuring the distance with e.g. radar, laser scanners or camera systems. However, all these techniques have limitations in their perception range, as all of them can only detect objects in their line-of-sight. The limited perception range of today's vehicles can be extended in future by using cooperative approaches based on Vehicle-to-Vehicle (V2V) communication. In this thesis, the capabilities of cooperative relative positioning for vehicles will be assessed in terms of its accuracy, continuity and reliability. A novel approach where Global Navigation Satellite System (GNSS) raw data is exchanged between the vehicles is presented. Vehicles use GNSS pseudorange and Doppler measurements from surrounding vehicles to estimate the relative positioning vector in a cooperative way. In this thesis, this approach is shown to outperform the absolute position subtraction as it is able to effectively cancel out common errors to both GNSS receivers. This is modeled theoretically and demonstrated empirically using simulated signals from a GNSS constellation simulator. In order to cope with GNSS outages and to have a sufficiently good relative position estimate even in strong multipath environments, a sensor fusion approach is proposed. In addition to the GNSS raw data, inertial measurements from speedometers, accelerometers and turn rate sensors from each vehicle are exchanged over V2V communication links. A Bayesian approach is applied to consider the uncertainties inherently to each of the information sources. In a dynamic Bayesian network, the temporal relationship of the relative position estimate is predicted by using relative vehicle movement models. Also real world measurements in highway, rural and urban scenarios are performed in the scope of this work to demonstrate the performance of the cooperative relative positioning approach based on sensor fusion. The results show that the relative position of another vehicle towards the ego vehicle can be estimated with sub-meter accuracy in highway scenarios. Here, good reliability and 90% availability with an uncertainty of less than 2.5m is achieved. In rural environments, drives through forests and towns are correctly bridged with the support of on-board sensors. In an urban environment, the difficult estimation of the ego vehicle heading has a mayor impact in the relative position estimate, yielding large errors in its longitudinal component

Standardization Roadmap for Unmanned Aircraft Systems, Version 1.0

This Standardization Roadmap for Unmanned Aircraft Systems, Version 1.0 (“roadmap”) represents the culmination of the UASSC’s work to identify existing standards and standards in development, assess gaps, and make recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D. The roadmap has examined 64 issue areas, identified a total of 60 gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 40 gaps/recommendations have been identified as high priority, 17 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 36 cases, additional R&D is needed. The hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will be widely promoted and discussed over the course of the coming year, to assess progress on its implementation and to identify emerging issues that require further elaboration

Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0

This Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0 (“roadmap”) is an update to version 1.0 of this document published in December 2018. It identifies existing standards and standards in development, assesses gaps, and makes recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D. The roadmap has examined 78 issue areas, identified a total of 71 open gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 47 gaps/recommendations have been identified as high priority, 21 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 53 cases, additional R&D is needed. As with the earlier version of this document, the hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will continue to be promoted in the coming year. It is also envisioned that a mechanism may be established to assess progress on its implementation

Data Processing and Modeling on Volcanic and Seismic Areas

This special volume aims to collecg new ideas and contributions at the frontier between the fields of data handling, processing and modeling for volcanic and seismic systems. Technological evolution, as well as the increasing availability of new sensors and platforms, and freely available data, pose a new challenge to the scientific community in the development new tools and methods that can integrate and process different information. The recent growth in multi-sensor monitoring networks and satellites, along with the exponential increase in the spatiotemporal data, has revealed an increasingly compelling need to develop data processing, analysis and modeling tools. Data processing, analysis and modeling techniques may allow significant information to be identified and integrated into volcanic/seismological monitoring systems. The newly developed technology is expected to improve operational hazard detection, alerting, and management abilities