Design, key functionalities, and performance requirements placed on modern aircraft navigation systems must adhere to the needs imposed by the progressively growing UAS/UAM and eVTOL markets. Especially for the terminal phases of flight (autonomous landing) and high-accuracy applications in urban and airport areas, performance levels required for safe operations can be even more strict than those for the today’s commercial aircraft.

In the paper, design, implementation, and real-time validation of Honeywell’s new Kalman filter-based Radar Altimeter Inertial Vertical Loop (RIVL) prototype is addressed. The system aims to provide high accuracy and integrity estimates of vertical parameters (Altitude above ground and vertical velocity). Inspired by the legacy BIVL technology, the prototype benefits from the dedicated Kalman filter and Honeywell’s proprietary method to address issues related to unknown terrain.

In Kalman filter, vertical acceleration estimate provided by AHRS (based on inertial sensor (IMU) measurements) and measurements from the radar altimeter aiding are fused. The part of the system is patent pending technology addressing issue of unknow terrain profile which provides required stability of the system output together with required accuracy in the final landing phase.

Once tested in simulation environment (proof-of-concept), the RIVL algorithm was ported to a rapid prototyping platform. Subsequently, data collection has been performed via both crane-test and flight-test onboard the CS-23 category aircraft (representative flight environment). Experimental results (in terms of accuracy) from both data collection phases will be included in the paper as well.

Our preliminary results indicate that the RIVL prototype provides reliable estimates of aircraft’s vertical height (above the terrain) and vertical velocity at required performance levels mandatory for UAS/UAM/eVTOL high-accuracy operations in urban and airport areas, including autonomous landing.

Foot-mounted inertial navigation can achieve high accuracy from poor quality sensors by performing zero-velocity updates (ZVU) every step. ZVUs keep sensors calibrated and minimize drift in the position solution. To get the best performance, the ZVU algorithm needs to be carefully tuned. This paper demonstrates the benefit of adapting that tuning to terrain type. Four terrain types are considered: concrete; grass; pebble and sand.

Using inertial measurement unit (IMU) context detection as a foundation, this paper aims to determine optimum ZVU parameters for various terrains. Our previous work from 2023 [1] uses context detection with MEMS IMUs to identify terrains using a k-Nearest Neighbor (kNN) algorithm with 99.24% accuracy. Using an IMU attached to the right foot, data was collected across four terrains for ZVU specific parameters – gyroscope magnitude threshold value, zero velocity accelerometer magnitude threshold, zero-velocity interval duration, and time between each zero-velocity occurrence. Figures 1 - 2 show examples of the parameters during the walking cycle.

Figure 1 ZVU walking parameters in the pedestrian walking cycle as shown using accelerometer magnitude.

Figure 2 ZVU walking parameter in the walking cycle as shown using gyroscope magnitude.

The four parameters comprise the tuning for the ZVU algorithm used for pedestrian navigation. The gyroscope and accelerometer thresholds are the maximum values where the stance phase begins and identify zero-velocity intervals. The zero-velocity interval duration and time between occurrences identify when the ZVU should be applied. The terrains are also separated into two classes: hard (concrete and grass) and soft (pebble and sand). Hard terrains are classified by firm foundations whereas soft terrains, the ground gives way during walking.

Figure 3 contains a percent change comparison between hard and soft terrains. There is a 112.1% difference in accelerometer threshold values and 41.4% difference in interval durations between the two classes.

Figure 3 Percent change comparison of hard and soft terrain classes.

With the large differences between surface hardness it is expected that terrain-dependent ZVU algorithms will significantly improve on current fixed parameter algorithms. An assessment of position accuracy will be included in the final paper.

The international interest in the Moon is rising again and several countries are launching projects to explore the Moon. As part of the Moonlight Programme, the European Space Agency (ESA) is developing Lunar Communication and Navigation System (LCNS) services with its industrial partners. In parallel, ESA is collaborating with North American Space Agency (NASA) and Japan Aerospace Exploration Agency (JAXA) to define the LunaNet interoperability specification. Among others, this specification will define the GNSS-like Augmented Forward Signal (AFS), for which the data component will send clock and ephemeris data of the LCNS satellites, which is essential for a Position, Navigation and Timing (PNT) system.
On Earth, the Global Navigation Satellite Systems (GNSS), such as Galileo, provide high precision positioning globally with a constellation of satellites. One of the key aspects of these systems is the navigation message conveying the satellite position and velocity to the user in a way that keeps the validity and accuracy as good as possible. The accuracy of the navigation message depends on the orbit model, the fitting algorithm, and the binary representation. For example, for the Galileo satellite the representation is provided by a set of 16 parameters.
The Moon orbits, specifically the Elliptical Lunar Frozen Orbits (ELFO), are quite different compared to the GNSS Medium Earth Orbits (MEO). The Kepler orbit parameters representation is different and the orbit is subjected to different perturbations.
This paper will present a novel orbit model for the LCNS that can support ELFOs. The paper will introduce the ELFO dynamics, the state-of-the-art on lunar orbit models and the problem of designing a model that can cope with these orbits. The paper will compare different models for ELFO to show the performance of the new model in terms of accuracy and number of bits (required to broadcast the information).

Low Earth Orbit (LEO) satellites can be integrated with classic GNSS, 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 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 LEO signals, such that the dynamic stress perceived by the receiver is mitigated. The legacy code and carrier control loops are retained and complemented with deep aiding, realized through code-phase and frequency predictions, as produced by the navigation engine.

Observable predictions are derived from the receiver to satellites relative kinematics and LEO orbits shall be accurately estimated before loop aiding can start. To overcome this “chicken-and-egg” situation, LEO broadcast ephemeris shall be either uploaded to the receiver at startup or downloaded from the navigation message, while temporarily tracking and decoding in unaided mode.

A Xona PULSAR™ Demonstration Signal in the L-Band was used to simulate the LEO constellation. Special firmware was developed to support the reception of this signal on the STMicroelectronics TeseoV triple-band GNSS chipset. Regular GPS L1 C/A signals were also simulated and synchronized with LEO. As part of the platform validation process, single point and PPP solutions for Xona stand-alone were generated.

Other practical aspects of the Xona PULSAR™ receiver are also discussed, including assistance during acquisition, handling of the navigation message for large constellations, observable integrity metrics and safety aspects.

The Xona simulations were mostly static open sky, yet the application focus is kept on difficult land scenarios for automotive, where the proposed architecture is expected to provide benefits in terms of increased availability and robustness.

With the growing dependency of many critical applications on Global Navigation Satellite Systems (GNSS), the importance of the integrity of GNSS signals has been higher than ever. As the availability of commercial off-the-shelf (COTS) jammers and spoofers rises, there is growing need for real-time interference detection to effectively apply mitigation techniques. Over the years, many interference detection techniques have been developed, verified, and validated. Pre-despreading detection techniques have increased the effectiveness of monitoring systems with limited computational capabilities. For spoofing detection, the Structural Power Content Analysis (SPCA) method, which exploits the periodic nature of the transmitted Pseudo-Random Noise (PRN) codes from the GNSS satellites, has widely been found to be effective in these systems. In this paper results from lab- and field-tests are presented and the real-time applicability of SPCA on spoofing signals is evaluated and found to be an effective and accurate spoofing detection technique. The method, however, was also found to trigger when subjected to several jamming waveforms and scenarios. Through analysis it is demonstrated that this is due to intermodulation products of the jamming signals that are caused by the delay-and-multiply operation performed as part of the SPCA algorithm. Evaluation of these jamming waveforms and events shows that additional signal processing techniques are required to increase the robustness of the SPCA method and the capability of monitoring systems to distinguish between different interference types. Additionally, optimization of the signal and noise filters used in SPCA can increase isolation between the signal and noise energy measurements, and further improve the suppression of intermodulation products due to jamming signals.

Medium frequency (MF) R-Mode is a terrestrial positioning, navigation and timing system which implements the frequency division multiple access (FMDA) concept with 500 Hz bandwidth per transmitter. The underlying idea is to exploit the DGNSS correction broadcast service as means for navigation. Thus, the transmitted signal is composed by a 100 bit/s minimum shift keying (MSK) carrying data and two aiding carriers at Hz from the channel central frequency. The ranges are derived from the phase estimates of aiding carriers. Therefore, their signal quality needs to be evaluated. Due to the continuous nature of the signal and the presence of the nearby MSK (Figure 1), a measure of the true in-band signal quality is difficult to be obtained.

Assessing the quality of a received navigation signal is of fundamental importance to predict the navigation receiver performance. The signal to noise ratio (SNR) and the carrier to noise density () ratio indicators are often used for this purpose. Both indicators are also used to optimize the receiver algorithms, to monitor the healthiness of the transmitted signals and to improve the positioning estimators.

This paper presents a method to estimate the for MF R-Mode signals. We consider the particular case of using the discrete Fourier Transform (DFT) as base algorithm to estimate the signals’ within our MF R-Mode receiver. We describe the framework for R-Model signal processing, as well as the definition of a estimator used for MF R-Model signals. Monte Carlo simulation are performed to characterize the estimator performance. Additionally, in-field measurements are used to validate the approach. As visible in Figure 2, the measured ranging performance (gray-scale points) follows the theoretical lower bound of the performance which proves that the estimated is a good indicator to measure the received signal quality under optimal propagation condition.

The European Commission (EC) is taking steps towards the implementation of a Galileo Timing Service. The Service is now formally part of the mission of Galileo Second Generation, and it puts emphasis to serve critical infrastructures.

To implement a proper Service implies to put all the necessary elements in place to be able to meet the defined level of performance. In order to ensure the correct processing of the Service signals and a minimum level of performance of the user receiver, corresponding standards are needed. Therefore, a fundamental element in the Galileo Timing Service concept is the standardisation of Galileo Timing Receivers.

The STARLITE project (Preparation of Standards for Galileo Timing Receivers) funded by EC is the first international initiative to develop Standards for GNSS timing receivers.

The target users for the standard are all Galileo Timing users, with special focus on critical infrastructures within Telecommunications, Finance and Energy Sectors.

The standard leverages on the specificities of the Galileo Timing Service. This will become fundamental in order to ensure the end-to-end performance for those users operating a receiver compliant with the standard. At the same time, the Standard allows the use of other systems to further enhance the performance.

The project helped to establish a formal Working Group (WG9) for the development of the Standard under CEN/CENELEC JTC5.

The aim of this paper is to provide a summary of the main outcomes of the activities developed in the frame of STARLITE project and WG9, in particular, the Galileo Timing Receiver functional and performance requirements, the associated Tests and the Guidelines for Installation and Maintenance of the equipment.

Securing GNSS signals: a software solution for Galileo signal authentication

1. A. Ramírez, A. Chamorro, S. Cancela, D. Calle, GMV

The utilization of GNSS services has become pivotal in various aspects of our daily lives. Whether it is mass-market activities like sports tracking, user guidance, or critical domains such as banking, telecommunication timing, aviation, and automotive solutions, GNSS plays a fundamental role. However, the substantial growth witnessed in the last decade has made GNSS a target for potential attackers.

To enhance future services, the Galileo program is adding a layer of security through the Galileo Assisted Commercial Authentication Service (ACAS). This service complements the Galileo Open Service Navigation Message Authentication (OSNMA) by introducing signal authentication through Commercial Service signals.

In this framework, the ACAS employs a unique approach to protect pseudoranges by incorporating authentication features. These features are implemented at the spreading-code level, utilizing spreading code encryption on the signal to perform Spreading Code Authentication. The service is based on the re-encryption and publication of short-duration spreading sequences from an existing encrypted signal, such as the Galileo E6C signal. The re-encryption process enables the receiver to autonomously retrieve the required sequences without continuous communication with an external server.

This paper details a commercial software solution implementing the ACAS service, designed for integration across a wide array of applications. The software retrieves and decrypts spreading sequences using OSNMA keys transmitted through the Signal-In-Space (SIS). The description on the functionalities is thoroughly described, including FFT-based circular convolution methods for signal acquisition processes, code phase and Doppler computation, pseudorange comparison, and authentic PVT computation.

A comprehensive solution description of the ACAS software solution, highlighting multiple integrations for diverse use cases. Testing in nominal and adverse scenarios, including Signal-In-Space tests, to showcase its real-time operational robustness will be presented. Results are analyzed using key performance indicators, leading to conclusions that assess the software solution's performance, capabilities in real scenarios, and suggestions for further improvements.

The paper explores the usage of LEO-PNT (Positioning, Navigation, and Timing) for providing navigation integrity to GNSS (Global Navigation Satellite System) constellations. LEO mega constellations, positioned between GNSS and users, offer closer-to-the user geometry, improving performance, reducing Time To Alarm (TTA) and enabling integrity monitoring without complex ground segments of any sort. The aim is to use future LEO mega constellations as the Integrity Monitor for a forthcoming European Global Navigation Satellite System (EGNSS), specifically focused on automotive users, emphasizing minimal onboard satellite capabilities without ground involvement. This plan builds on earlier studies, anticipating performance for the upcoming LEO-PNT In-Orbit-Demonstration (IOD constellation).
The strategy focuses on using GNSS receivers onboard LEO satellites to gather MEO-LEO observables (step 1), broadcasting dedicated integrity messages through the LEO-User navigation band (step 2). It simplifies previous strategy that required high-data-rate communication channels at the cost of reducing some flexibility. Leveraging onboard Precise Point Positioning (PPP) of LEO-PNT satellites, derived PPP sub-products form a dedicated integrity navigation message broadcasted to users in step 2.

Users integrate this data from visible LEOs, locally implementing an Integrity Monitor in step 3. This monitor checks individually each GNSS MEO satellite, aligning with Integrity Concept's Fault Tree Analysis (FTA) for failure modes like satellite clock events or pseudorange errors. The accuracy of the check needs to be in the order of 20 cm to meet the EGNSS performance.

Service Volume Simulations are presented that demonstrate the feasibility of the proposed solution based on existing on-board GNSS receivers’ features and the future full LEO constellations and promising results with the upcoming 4-satellite IOD LEO constellation.

Current Satellite-Based Augmentation Systems (SBASs) improve the positioning accuracy and integrity of GPS satellites and provide safe civil aviation navigation services for procedures from en-route to LPV-200 precision approach over specific regions. SBAS Systems already operate, such as WAAS, EGNOS, GAGAN and MSAS.

The development of operational SBAS systems is in transition due to the extension of L1 SBAS services to new regions and the improvements expected by the introduction of Dual Frequency Multi-Constellation (DFMC) services, which allow the use of more core constellations such as Galileo and the use of the ionosphere-free L1/L5 signal combination.

Following the UK's withdrawal from the European Union (EU), the use of EGNOS's Safety of Life (SoL) services in UK airspace ended. The UKSBAS testbed is a demonstration and feasibility project in the framework of ESA's Navigation Innovation Support Programme (NAVISP) sponsored by the UK's HMG with the participation of the Department for Transport and the UK Space Agency. UKSBAS main objective is to deliver a new L1 SBAS signal in space (SiS) from May 2022 in the UK region using Inmarsat's 3F5 geostationary (GEO) satellite and Goonhilly Earth Station as signal uplink over PRN 158, as well as L1 SBAS and DFMC SBAS services through the Internet. SBAS messages are generated by GMV's magicSBAS software fed with data from Ordnace Survey's stations network.

This paper provides an assessment of the performance achieved by UKSBAS services during the last two years of operations at SiS and user level, including a number of experimentation campaigns performed in the aviation and maritime domains comprising ground tests at airports, flight tests on aircraft and sea trials on a vessel. This assessment includes, among others, service availability (e.g.: APV-I, LPV-200), Protection Levels (PL) and Position Errors (PE) statistics over the service area and in a network of receivers.