Domenico Di Grazia

The rapid evolution of the automotive industry towards autonomous and connected vehicles, necessitates the development of highly accurate and reliable navigation systems. Precise Point Positioning (PPP) has emerged as a critical technology in this domain, potentially offering centimeter-level accuracy, which is a fundamental requirement for safe and efficient autonomous driving. The Galileo High Accuracy Service (HAS) is a key enabler for PPP, providing precise orbit and clock corrections, as well as satellite clock biases. This paper explores the innovative integration of Global Navigation Satellite System (GNSS) meta-signals with Galileo HAS corrections specifically tailored for the demanding automotive sector. Urban environments, characterized by dense buildings and complex geometries, pose significant challenges to GNSS reliability due to severe multipath effects. Wide-band modulations, such as the Galileo’s AltBOC signal, offer inherent multipath mitigation capabilities. However, the direct acquisition and processing of AltBOC signals demands specialized hardware, often incompatible with the cost, size, and power constraints of typical automotive receivers. The synthetic meta-signal approach allows reconstructing AltBOC measurements from sideband signals, effectively replicating the benefits of wide-band modulations without requiring additional hardware modifications. The implementation of the meta-signal approach is realized using the STMicroelectronics’ TESEO VI GNSS receiver, a triple-band multi-constellation platform. An ad-hoc firmware was developed to implement the meta-signal paradigm, incorporating Half-Cycle Ambiguity Resolution (HCAR) and a robust pseudorange jump detector. The PPP solution is built upon the JRC User Navigation Engine (JUNE), which features GNSS measurement pre-processing, cycle slip detection and correction. Navigation estimation is performed using an Extended Kalman Filter (EKF) exploiting uncombined code and carrier phase measurements within a PPP Single Difference algorithm. The EKF state vector includes receiver position, velocity and acceleration, tropospheric and ionospheric delays and carrier phase ambiguities. The Galileo HAS free service is used, and the corresponding orbit and clock corrections are applied to the raw measurements. Extensive tests were conducted in diverse automotive environments, to assess the performance of PPP integrating synthetic meta-signals with HAS corrections. Preliminary results demonstrate a reduction in code noise and achieve millimeter-level accuracy for reconstructed carrier phases. These findings underscore the potential of the meta-signal approach to enhance GNSS performance without requiring additional hardware modifications. This comprehensive evaluation of positioning accuracy and reliability provides valuable insights into the practical integration of meta-signals with Galileo HAS corrections for automotive applications.

LEO-PNT systems are poised to revolutionize GNSS by delivering superior resilience, accuracy, and robustness. This paper presents a novel Hardware-in-the-Loop (HIL) evaluation of integrating LEO-PNT augmentation into kinematic Precise Point Positioning (PPP) for dynamic users. Conducted at the Joint Research Centre (JRC) facilities, the study utilizes a comprehensive, end-to-end test bed that includes RF signal generation for a multi-tier LEO-PNT constellation, the integration of the innovative STMicroelectronics Teseo VI LEO-compatible receiver, and a dedicated, configurable PPP algorithm capable of processing HIL-generated raw measurements. Our results demonstrate the substantial benefits of LEO-PNT augmentation in significantly improving positioning accuracy within challenging, high-dynamic automotive scenarios. Crucially, this study underscores the critical role of HIL testing in stress-testing and identifying specific areas for enhancement in both receiver hardware and algorithm implementation—essential steps for the successful, real-world deployment of LEO-PNT technologies.

The synthetic meta-signal reconstruction approach enables the generation of wideband Global Navigation Satellite System (GNSS) measurements from side-band observations. This approach is of particular interest for automotive market devices where, for instance, hardware constraints do not allow full-band Galileo Alternative Binary Offset Carrier (Alt-BOC) processing. In this paper, the applicability of the synthetic GNSS meta-signal paradigm is extended by introducing a half-cycle ambiguity detector for the reconstructed carrier phases and a jump detector for the pseudoranges. These accessories make the reconstruction approach more robust and suitable for mass market devices. Tests conducted using the STMicroelectronics TeseoV receiver demonstrate the validity and potential of this approach.

Low Earth Orbit (LEO) satellites complement classic GNSS by offering stronger signals, improved visibility, and system redundancy. Typical high speeds in LEO orbits generate rapid variations of the receiver-to-satellite geometry, which can improve the convergence of Precise Point Positioning (PPP) algorithms. However, high dynamics also induce strong Doppler rates at the receiver, which make the tracking procedures more difficult. In this paper, a loosely combined navigation and tracking architecture is applied to a Xona PULSAR™ Demonstration Signal in the L-Band such that the dynamic stress perceived by the receiver is mitigated. Other practical aspects of the Xona PULSAR™ receiver will be also discussed.

Modern global navigation satellite systems (GNSSs) feature advanced modulations such as the alternative binary offset carrier (AltBOC) and the Beidou satellite navigation system (BDS)-3 asymmetric constant-envelope binary offset carrier (ACE-BOC). Full processing of such modulations requires receiver front-ends with large bandwidths and significant computational resources to implement wideband correlations. An alternative is to use the synthetic meta-signal reconstruction approach that operates at the measurement level and requires limited additional resources with respect to the processing of individual signal components. This approach has been implemented in the STMicroelectronics STA8135GA GNSS chipset and serves as further extension of the capabilities of the STMicroelectronics Teseo V automotive triple-band multi-constellation receiver, which now supports the AltBOC and ACE-BOC modulations. Analysis was conducted in the measurement domain, assessing the quality of the AltBOC and ACE-BOC reconstructed observations. Receiver performance was also tested in the position domain: the benefits of meta-signal reconstruction approach were clearly demonstrated also for automotive grade receivers.

Satellite acquisition is a crucial procedure in GNSS receiver operation, which becomes particularly challenging when no assistance information is available - the so-called cold start conditions. In this paper, a machine learning approach will be introduced to improve the acquisition strategy. In detail, a reinforcement learning algorithm will be implemented to learn an optimal acquisition strategy.

Global Navigation Satellite System (GNSS) receiver evolution moves through the paths of interoperability among different satellite systems and the support of modern composite signals. To improve the receiver accuracy, the tracking sensitivity, and the resilience versus jamming, modern signals have introduced dual (pilot plus data) components. Pilot signals design on L1 carrier for GPS, BeiDou (phase 3), and Quasi-Zenith Satellite System (QZSS) are implemented by tiered codes, with a very long Secondary Code (SC), which can be difficult to acquire. This article will analyze and validate an efficient algorithm for secondary code phase estimation, with the objectives to minimize the total dwell time and to limit the processing complexity. Details will be provided about the performance tradeoff versus other classic algorithms, based on the exhaustive construction of power histograms, for all the SC phases. A method for fast reacquisition of the SC phase, based on time propagation, will be also illustrated to extend the practical usability of the estimator under difficult conditions, characterized by obscurations and signal impairments, typical of automotive scenarios.

Loosely Coupled architectures based on Micro Electromechanical Systems (MEMS) Inertial Navigation Systems (INS), and multi-band GNSS are widely adopted to improve the availability of the integrated solution under difficult conditions, characterized by frequent obscurations of the GNSS signal. Typical scenarios include automotive urban tracks or open sky under dynamics, in presence of bridges and short tunnels. Low Earth Orbit (LEO) satellites also fall in this scope, as their lower altitude results in a Doppler curve with stronger rate variations, which sum up to receiver dynamics and are more challenging to track than traditional GNSS. In this paper, a hybrid solution is presented, where a classic loosely coupled scheme is complemented by deep integration. The INS-aided solution combines with GNSS satellites velocities and accelerations to derive code, Doppler, and Doppler rate observables predictions. Validation and performance assessment are conducted on a compact two-chip hardware platform, based on the state-of-the-art multi-band GNSS receiver STA8135 (TeseoV) and the MEMS IMU ASM330LHH from STMicroelectronics. Deep aiding has the potential to broaden the applicability of loosely coupled INS integration to the cases where signal weakness and the combined user to satellites dynamics exceed the tracking loops capability. Partially obscured automotive scenarios, reception of attenuated signals under high dynamics and assisted LEO satellites acquisition and tracking are among the applications that can benefit from the proposed scheme.

The increase of electronic content for advanced features such as Advanced Driver Assistance Systems (ADAS), and autonomous driving, the use of Over-The-Air (OTA) for updating the related software (SW) combined with the increased number of reported hacking attacks to these systems have highlighted the need of introducing cybersecurity features in automotive products. United Nations Economic Commission for Europe (UNECE) World Forum for Harmonization of Vehicle Regulations and International Organization for Standardization (ISO) have introduced regulations and standard respectively enforcing cybersecurity for automotive cars and components. This contribution introduces the cybersecurity concept and some security aspects for the evolution of the current STMicroelectronics GNSS receiver STA8100MA TeseoV/STA9100MGA TeseoAPP family, also briefly summarizing the cybersecurity development flow and its link with Functional Safety.

Among on-board sensors, the Global Navigation Satellite System (GNSS) receiver plays a key role because of its unique capability of absolute and precise localization. Autonomous vehicles guidance and assistance, resilient timing and an increased demand for higher safety levels are motivating a rapid evolution toward multi-band GNSS receivers in the automotive (and industrial) segments. Triple-band GNSS has gained interest in the past years and found application in professional receivers and reference stations, mostly because of faster carrier-phase ambiguity resolution, stronger integrity constraints over linear combinations and higher signal availability for Real-Time Kinematic (RTK) algorithms. The deployment of new services for high-accuracy positioning, like Galileo HAS, BeiDou PPP-B2b and Quasi Zenith Satellite System (QZSS) CLAS is also taking benefit from the availability of multiple bands. In this latest applicative scenario, the third frequency plays a different role, acting as an additional downstream channel for the GNSS correction data. Signal modernization is definitely another strong enabler for the adoption of triple-band. With specific reference to system design and signal processing aspects, this article discloses a new compact GNSS chipset for automotive, capable to generate coherent triple band observables and correction data streams, including a demodulator for QZSS Code Shift Keying (CSK). The frequency plans, the supported mix of legacy and modernized signals and relevant Key Performance Indicators (KPI) are discussed for selected configurations, typically encountered in automotive precise-positioning and timing.