Trimble’s Dual Antenna GNSS receiver and real-time positioning service will provide centimeter-level accuracy for farmers utilizing autonomous equipment.

Trimble and Sabanto have announced the integration of Trimble BX992 Dual Antenna GNSS receivers with Trimble CenterPoint^® RTX into Sabanto’s autonomy solutions. Trimble will act as Sabanto’s key autonomous technology provider, delivering high-accuracy positioning to its fleet.

Farmers need the highest level of uptime and reliability to avoid service disruption. Leveraging Trimble’s BX992 GNSS receiver and satellite-delivered Trimble CenterPoint^® RTX corrections service, Sabanto’s autonomy solutions can now receive centimeter-level L-Band corrections nearly anywhere in the world. With precise positioning and autonomous operation, farmers can realize greater productivity, minimize downtime and input costs, and alleviate workforce shortages through the use of autonomous vehicles.

“In 2022, Trimble Ventures announced an investment with Sabanto focused on autonomous workflows in farming applications. This announcement underscores our goal to invest in early and growth-stage companies that are accelerating innovation, digital transformation and sustainability in the industries Trimble serves,” said Finlay Wood, general manager, off-road autonomy, Trimble. “It’s exciting to witness how Trimble’s technology and our Trimble Ventures relationship can accelerate the adoption of autonomy in the agriculture industry, as evidenced by this next phase of our collaboration with Sabanto.”

In addition to RTX corrections, Trimble will offer correction stream-switching enabling farmers to automatically switch from IP to satellite seamlessly, to provide the best signal in every environment.

“With a customer base in agriculture, as well as municipalities and airports with a remote environment, our customers are often in areas without reliable cell service, so a reliable correction signal is extremely important to keeping our autonomous machinery working around the clock,” said Craig Rupp, founder and CEO of Sabanto. “It’s exciting to see our two businesses find synergies that will improve ag autonomy, delivering a better experience for our farmers through continuous connectivity, regardless of the environment.”

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The GEODNET Foundation and Deep Sand Technology (DST) are working together to advance precision agriculture in rural North America.

Combining GEODNET’s high reliability data service with DST’s affordable automated tractor solutions for both new and older equipment, the companies have announced the availability of a GEODNET-compatible RTK base-station that supports centimeter-accurate operations without a UHF radio link, according to a news release. The solution will help farmers improve efficiency and yields while also reducing input costs.

GEODNET is a blockchain-based decentralized network of high-precision multi-band GNSS base stations that offers affordable GNSS corrections. Since the official launch in 2022, the network of Web3 GNSS base stations has grown to more than 3,600 worldwide, becoming a reliable solution for RTK applications in more than 1,800 cities in more than 100 countries. The goal is to have between 50,000 and 100,000 base stations by 2026.

This latest partnership will help quickly expand access to affordable high-accuracy RTK-based GPS in key U.S. agricultural and rural areas, advancing precision agriculture as well as other applications such as advanced cruise control systems in passenger cars, automated highway trucking operations, and eco-friendly electric robotic lawnmowers.

Farmers often opt to use less accurate and less repeatable WAAS signals to avoid the costs that come with RTK network fees and base stations, DST CEO Joey Koebelen said, according to the release. The company, which offers autosteering and GPS guidance, has been looking for an affordable, easy option that provides farmers with the RTK accuracy they need for automation, eliminating steering overlap and opening the door to other farming applications. GEODNET’s affordable, accurate RTK does that.

A look at GEODNET
So how does GEODNET work? The decentralized GEODENT takes a community approach to corrections, making it more affordable. Station owners set up a Satellite Mining station and are rewarded in the project’s native Polygon token, GEOD, which trades every day, GEODNET Foundation Creator Mike Horton said. When new stations join the blockchain, they prove their location using a published algorithm.

As data from the network is paid for and used by end-users, this “burns up” mined tokens. Tokens are purchased back with cash and sent to a one-way safe on the blockchain. This buyback and burn mechanism is at the core of how the network functions economically.

Horton describes GEODNET as “a very open, flexible system.” Anyone who wants to be part of the network can set up a station, use the network or build on top of the network. And because it’s all bound together by blockchain, there isn’t a company in control behind the scenes. It’s a true community approach, with everything connected through a protocol that all systems adhere to. Users can add stations to areas that don’t have any or much coverage or tap into existing stations in their area with a subscription.

“The token is how people exchange value in the ecosystem, and that’s the part that’s radical,” Horton said in an Inside GNSS article. “But it’s a way to create independent operations and allow businesses to make use of GEODNET data by also contributing. It’s like a cycle. The more people put up stations, the more successful the network becomes, and the more people then want to put time and energy into the ecosystem.”

Other use cases
Drones, robotic vehicles, augmented reality and IoT/mobile devices are other applications that can leverage GEODNET for centimeter-level location accuracy. Agriculture, of course, is a big one, particularly in Romania where some of the first base stations were established. Marius Negreanu, one of the owners of Romania based distributor EuGeo, is among those using the service there for agriculture-related applications rather than the government owed ROMPUS that only has about 50 stations.

Negreanu sells affordable autonomous tractor kits to farmers, he said, and is using the kits as a bridge to promote the network. An antenna that links to the closest GEODNET station is part of the kit that turns a manual tractor autonomous. This is something more farmers in Romania are becoming open to, as they realize the centimeter precision such kits provide lead to a larger harvest and less field consumption.

The DST collaboration is another example of how GEODNET is benefiting agriculture.

“With farm operations facing limited labor resources and rising input costs,” Horton said, “emerging technologies, such as those provided by GEODNET and Deep Sand Technology, are key to keeping healthy, affordable food on the table.”

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The 14th Multi-GNSS Asia Annual Conference (MGA2024) will be held From January 30^th to February 2^nd at Mae Fah Luang University, in Thailand. Included among the panels focusing on Latest Tech, Latest R&D and Latest Applications & Business, is a Lunar PNT Panel.

This panel will include the following invited speakers:

Lunar PNT invited panelists:

・Mr. JJ Miller (NASA, USA)

・Dr. Jung Min JOO (KARI, Korea)

・Dr. Javier Ventura-Traveset (ESA, Europe)

・TBD (GISTDA, Thailand)

・Prof. Xiongwen He (CAST, China)

・Dr. Masaya Murata (JAXA, Japan)

For more information, visit the conference website at https://www.mga-conference.com/

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GNSS-Enabled CC200A-LB Module Expands Global Connectivity Standards.

Quectel Wireless Solutions has achieved a significant milestone with its CC200A-LB satellite communication module securing major global certifications from regulatory authorities including CE, FCC, IC, and RCM. This endorsement confirms compliance with satellite network standards across key regions spanning Europe, North America, Canada, Australia, and New Zealand.

The CC200A-LB module, tailored for cost-effectiveness and ultra-low latency, establishes a robust global network connection. This capability positions it as a versatile solution for diverse applications such as maritime, transportation, heavy equipment, agriculture, mining, and oil and gas monitoring. Its primary advantage lies in providing reliable communication in areas where cellular networks face limitations.

Norbert Muhrer, President and CSO of Quectel Wireless Solutions, highlighted the module’s ability to ensure continuous and cost-effective communication for remote and mobile assets, irrespective of location.

Utilizing ORBCOMM’s cutting-edge satellite IoT connectivity and harnessing the L-band of the Inmarsat GEO constellation, the CC200A-LB offers two-way communication, low latency, and extensive global coverage. When combined with cellular modules, it enables dual-mode IoT applications, promising unparalleled reliability, redundancy, and coverage ubiquity. In areas with inadequate cellular network coverage, the module seamlessly sustains communication through satellite connections.

Notably, the CC200A-LB features a compact LCC+LGA package, measuring 37mm × 38mm × 3.35mm, and incorporates multi-constellation GNSS positioning, swiftly and precisely identifying device locations. Its user-friendly AT command set streamlines configuration and management processes.

Quectel offers flexible procurement options for the module, available independently or coupled with the appropriate Quectel antenna, expediting the time-to-market for customer devices.

In addition to the CC200A-LB, Quectel has diversified its satellite communication module portfolio, including the CC660D-LS compliant with 3GPP NTN R17 standards and the BG95-S5 and BG770A-SN modules supporting both satellite and cellular networks. GNSS-enabled features across these modules reaffirm Quectel’s commitment to enhancing global connectivity standards and advancing IoT applications across industries.

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After releasing their first MEMS-based oscillators in 2007, the team at SiTime knew there was still work to be done.

Using MEMS was a brand new concept for timing, and back then, clients were telling them the performance just wasn’t there. The team went to work to change that, developing innovative products that rival the more traditional quartz crystal oscillator options the industry has used for years.

SiTime released its latest offering, the Endura Epoch Platform, earlier this month. This ruggedized MEMS oven-controlled oscillator (OCXO), designed to provide the robust and resilient positioning, navigation and timing (PNT) services needed for defense applications, was certainly a labor of love, Executive Vice President of Marketing Piyush Sevalia said. Development took years, with the company first defining the solution back in 2011 and design work beginning in 2018. The process involved various cross functional teams working together to get the timing solution to where it is today.

“We had to figure out not just from the customer point of view what they want, what matters now and what will matter in the future, but from the technology point of view as well,” Sevalia said. “How do we get the level of stability needed under all of the different harsh conditions the device will be subjected to?”

A look at the benefits
Developing a MEMS timing solution for the aerospace and defense markets comes with a long list of challenges and performance requirements, Sevalia said. Such environments are difficult to operate in, with extreme temperatures, shock, vibration and electromagnetic interference all issues to contend with. The silicon-based Endura Epoch OCXO was designed to overcome those challenges. It features a small footprint and can be placed anywhere on the board without users having to make adjustments. Very little external force couples on the oscillator, so it has no problem handling vibration and shock, which is critical in these environments.

It is also programable to any frequency between 10 to 220 MHz, with a very short lead time for custom builds. The company hires its own analogue teams who can help solve various analogue clocking problems in-house rather than outsourcing, Sevalia said, and the devices are manufactured leveraging proven semiconductor processes that provide the reliability and quality needed for extreme conditions.

Being able to overcome common challenges natively without adjustments or compromises leads to a faster innovation cycle, Sevalia said.

“Some people compromise on the performance of the system because they can’t get the exact frequency they want. I’ve seen people redesign an entire system because it was putting out too much power into the electromagnetic spectrum,” he said. “You don’t have to do that with this device. That’s a change in the way people are doing their design work and the way they’re going to production with their devices.”

Protecting PNT
Today, defense systems are structured around GPS-based PNT, but GPS signals can be disrupted unintentionally or spoofed or jammed by nefarious actors—which can lead to various problems such as equipment malfunctions and even mission failure. This is where an ultra-stable local clock device like the Endura Epoch Platform becomes critical, serving as an accurate time reference for PNT until the GPS signal returns.

“The DOD has projects ongoing to update GPS capabilities, calling it assured PNT, and in that new systems are being designed with new GPS standards,” Sevalia said. “We expect they will want better vibration resilience and timing accuracy from the part-to-part level and a reliability point of view while still addressing SWAP-C requirements. Applications could be missiles, ground comms, radar, drones.”

The timing device has low power consumption, enhanced acceleration sensitivity, optimal g-sensitivity and long-term aging. The silicon-based MEMS device is consistent, and offers the performance needed in harsh environments where vibration and temperature changes are an issue. During GPS disruption, PNT performance is driven by the time error on the local clock, with its benchmark time error 3µs over 24 hours.

The Endura Epoch Platform is a true source of pride for the SiTime team, as it provides real value for customers, Sevalia said, and helps to solve some of their most difficult problems.

“This product changes the game by delivering a level of performance not seen before,” Sevalia said, noting there is still plenty of room for more MEMS innovation. “We’ve climbed a peak that others thought was impossible 15 years ago when the company first started.”

The post A Labor of Love: SiTime Corporation Introduces its Endura Epoch MEMS OCXOs for Defense and Aerospace Applications After Years of Development appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Speaking at the recent NAVISP conference in Noordwijk, Mark Brammer, Positioning Lead, UK National PNT Office, provided details on the UK’s new Framework for PNT Resilience and Innovation.

“The UK economy and society would suffer severe consequences from a major disruption to global navigation satellite systems [GNSS],” Brammer said, “with timing being the most critical element. The objective of the new PNT framework is not specifically to build an alternative technology. Instead, we want to focus on critical national infrastructure [CNI], PNT use cases, impacts, and solutions.”

The framework will comprise two phases, dubbed ‘epochs’. “Over the next few years, Epoch 1 will utilize current and proposed or partially funded capabilities,” Brammer said. “We will have UK-sourced timing from NTC RETSI, provided by assured means to a UK space-based augmentation system [SBAS], to a terrestrial broadcast eLORAN [enhanced long-range navigation] network, and over fiber to national GNSS interference monitoring systems.”

Tried and tested
The UK’s eLORAN capability consists of a distributed system of over-the-air, 90- 110kw transmitters based in at least four locations in the UK and Ireland. This would provide CNI timing and safety-of-life services to maritime and aviation users. “eLORAN is an internationally standardized system used by multiple nations,” Brammer said, “primarily in the maritime domain. The Department for Transport and the General Lighthouse Authority will act as system leads.”

A UK SBAS will provide PPP for enhanced geolocation performance and GNSS-health monitoring, using GPS L1 and L5 frequency sets, and providing precision navigation for air transport and autonomous vehicle operations. An international partnership with Australia is envisaged, with the UK Department for Transport as lead, working in close association with the Ministry of Defense (MOD) and the UK Space Agency (UKSA). ‘Time Over Fibre’ will provide internal UTC(NPL) timing to CNI users, including the MOD, and will be a primary means of transmission of UTC(NPL) to transmitting nodes.

These systems will compliment and ensure current GNSS services. Development of follow-on components for Epoch 2 is to be guided by the UK’s national PNT office directly and through the European Space Agency’s NAVISP program. Reader’s will know that while the UK is no longer a member of the European Union, it is still a full member of ESA.

Longer term
“In future years, Epoch 2 will continue to utilize all of the capabilities of Epoch 1, current, planned-funded or partially funded,” said Brammer. “Further, we intend to develop a regional space-based GNSS, enabled by eLORAN, encrypted for CNI. This means establishing a land-based eLORAN system which enables a small, four-satellite, regional constellation of GNSS satellites to support the UK and territories. Consider this as a UK equivalent of Japan’s QZSS.” Alongside these new elements, the UK will work to develop a LEO PNT, terrestrial broadcast 5G/Mesh/SoO system, and will promote the growth of its own wider quantum timing and navigation industry.

“The final result will be a closely integrated system of systems,” Brammer said, “bringing together traditional and AltPNT capabilities – the framework that we believe provides the highest resilience and economic opportunity.”

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Point One Navigation’s Polaris Precise Positioning Network now covers all of Great Britian, providing precision location for applications such as advanced driver assistance (ADAS), robotics, mapping, delivery and infrastructure inspection.

Ordnance Survey (OS net) base stations have been integrated into the Polaris Network, according to a news release, providing advanced positioning capabilities to this new coverage area. Polaris is an RTK corrections network that enables centimeter-level accuracy and also covers the United States, EU, Australia and Canada. Existing Polaris customers can use the UK integration immediately at no additional cost.

Point One’s integrated location platform is complemented by FusionEngine software, which further integrates inertial measurement, wheel odometry and other sensors to achieve the level of precision required—even when there are no satellite signals.

The localization service features a robust GraphQL-based API that makes it easy to integrate Polaris RTK into developer-built applications. By early next year, Point One will be able to support State Space Representation (SSR) corrections delivered by L-band, even without cellular networks or in bandwidth constrained applications.

“Point One Navigation wants precise location to be available everywhere,” Point One CEO and co-founder Aaron Nathan said, according to the release. “We are committed to bringing our Polaris RTK network to new markets and sectors, to enable existing and new applications that demand the most accurate, reliable and current location data possible. The expansion to the UK is another significant step in realizing this goal.”

Point One also recently introduced Atlas, an affordable inertial navigation system (INS) that offers high accuracy for autonomous vehicles, mapping and other applications. Atlas, designed for deployment in large fleets, provides ground-truth level accuracy in real time, simplifying engineering workflows, reducing costs and enhancing operational efficiency.

“We envision a future where businesses, researchers and automotive companies can harness the power of centimeter-level, real-time accuracy without the complexities and cost associated with post-processing,” Nathan said.

The post Point One Navigation Now Providing RTK Corrections in Great Britian appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The Association of the United States Army’s (AUSA) annual conference highlighted the growing popularity of small unmanned aircraft as well as the need to develop and refine counter-UAS systems to go up against them—all of which must operate in GPS-denied or degraded environments. Many, if not all, of the systems featured rely on precise positioning, especially in the GPS-denied environments frequently encountered on the modern battlefield.

During the conference, VectorNav introduced two new members of its GNSS/INS family to help meet such needs, the VN-210-S and VN-310-S. Both bring new GNSS capabilities and improved performance, according to the company.

The VN-210-S combines VectorNav’s IMU—composed of a three-axis gyroscope, accelerometer and magnetometer—with a new, triple-frequency GNSS receiver. The 448-channel from Septentrio (hence the S in the name) adds new capabilities, including L5 frequencies, Moving Baseline RTK with centimeter-level accuracy, and support for OSNMA message authentication and interference mitigation.

The VN-310-S also incorporates the IMU and teams it with two 448-channel GNSS receivers, along with support for OSNMA authentication and interference mitigation. For both systems, this means improved positioning performance in congested radio frequency environments or GNSS-denied areas.

Both are packaged in a precision milled, anodized aluminum enclosure designed to military standards and are IP68-rated. For ultra-low size, weight and power applications, VectorNav introduced L5 capabilities to the VN-210E (Embedded) when using an externally integrated L5-band GNSS receiver.

The VN-210-S and VN-310-S development kits are available for immediate purchase in low quantities, with full production and additional capabilities expected to be announced early in the first quarter of 2024.

PNTAX 2023

At roughly the same time as the AUSA conference, the Army conducted the fifth annual PNT Assessment Experiment, or PNTAX, which brought together joint and international defense partners and industry to experiment with emerging PNT technologies in an environment with degraded or denied GPS.

Held at White Sands Missile Range inAugust, PNTAX is part of Army Futures Command’s campaign of experimentation and continuous learning, where participants could field-test space-based, ground-based and aerial positioning technologies.

“Experiments like PNTAX provide a valuable opportunity for Soldier touchpoints that directly influence requirements,” said Mike Monteleone, director of the Army Futures Command Assured Positioning, Navigation and Timing/Space Cross-Functional Team (APNT/Space CFT), which hosted the event.

For this year’s PNTAX:

• Soldiers from the 101st Airborne Division conducted terrain walks and feedback for the Dismounted Assured Positioning System.
• Soldiers from the 1st Armored Division conducted their own training objectives, faced with threat-based GPS denied and degraded environments.
• Soldiers from the 10th Mountain Division worked with the CFT’s sensor-to-shooter team in the denied environment to learn from its effects on the links associated with the tactical architecture, while the 2nd Infantry Division conducted a variety of ground maneuver activities that enabled operations throughout the experiment.
• Allied partners from Canada and Australia joined to observe and scope future participation, while partners from the United Kingdom conducted land navigation experiments with their Soldiers. Multinational participants worked alongside their participating Soldiers and U.S. Soldiers to replicate what operations will likely look like in future, combined force settings.

The open-air denied, degraded, intermittent and limited environment at PNTAX was achieved through jamming and a variety of other threat interfaces that resembled real-world, layered approaches Soldiers might face in a multi-domain operating environment.

Next year, the Army intends to expand opportunities for allied partners, increase Soldier training activities and broaden the scope of electromagnetic spectrum experimentation.

The post AUSA Highlights Need for Systems with Resilient Navigation appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Through a series of four vehicle experiments leveraging low-cost GNSS/IMU sensors, the findings from this research indicate that low-cost HAS PPP solutions can yield results comparable to those obtained using CNES ultra-rapid products at the 68th percentile of errors.

DING YI AND SUNIL BISNATH YORK UNIVERSITY, CANADA

NACER NACIRI JPL, USA

F. JAVIER DE BLAS EUSPA, EUROPEAN UNION

ROBERTO CAPUA SOGEI SPA, ITALY

In January 2023, EUSPA officially announced the Galileo High Accuracy Service (HAS) reached initial service through the E6B signal [1]. With the availability of HAS data, users worldwide can retrieve precise GPS+Galileo orbit and clock corrections, as well as satellite code biases in real-time and for free with 24/7 operated service delivery and committed performance levels. This trend has further boosted the development of GNSS receivers and mass-market applications, such as Intelligent Transportation Systems (ITS), precise agriculture and mobile mapping [2]. While there has been a growing interest in assessing the performance of Galileo HAS in Precise Point Positioning (PPP) processing mode for civil applications, there has yet to be an investigation into the use of low-cost sensor data with HAS corrections in urban driving environments. The objective of this study is to evaluate the performance of Galileo HAS PPP in real-world driving conditions using low-cost GNSS and IMU sensors.

Rapid technological advancement

In the pursuit of accurate positioning, two advanced satellite positioning techniques have gained widespread adoption in mass-market applications: PPP and Real-Time Kinematic (RTK). Unlike RTK, which relies on Observation Space Representation (OSR) messages, PPP uses State Space Representation (SSR) data to achieve performance similar to RTK [3,4]. For this study, these SSR messages are sourced from the International GNSS Service (IGS) Analysis Centers (ACs), which provide precise satellite orbit and clock products. Additionally, the IGS has introduced Real-Time Service (RTS) to disseminate SSR corrections, which are provided in the RTCM-3 format and can be accessed through Networked Transport of RTCM via Internet Protocol (NTRIP). PPP, compared to RTK, demands a longer time to achieve centimeter-level accuracy due to its inability to eliminate certain GNSS errors, such as receiver clock errors and atmospheric delays. However, PPP offers distinct advantages, notably the absence of the establishment of local reference stations and the ability to provide continuous, high-quality Positioning, Navigation and Timing (PNT) services without being limited by baseline length.

Instead of broadcasting corrections through the Internet, a recent development in positioning communities has witnessed the emergence of the direct broadcast of SSR corrections via GNSS constellations. As a pioneer in providing GNSS augmentation services, Japan’s Quasi-Zenith Satellite System Centimeter-Level Augmentation Service (QZSS CLAS) is notable for being the first augmentation system to transmit Compact SSR (CSSR) corrections through the L6D signal in 2020, aiming to provide satellite orbit, clock, code/phase biases, and ionospheric/tropospheric corrections to GPS, Galileo and QZSS satellites across Japan [5,6]. To extend the service area for the entire Asia-Oceania region, the Japan Aerospace Exploration Agency (JAXA) introduced the Multi-GNSS Advanced Orbit and Clock Augmentation (MADOCA) system. In 2022, MADOCA initiated its PPP trail service to disseminate satellite orbit, clock, code/phase corrections for GPS, Galileo, GLONASS, BDS and QZSS satellites through the L6E signal [7]. Similarly, BDS-3 (BeiDou-3) offers customized CSSR corrections, including GPS + BDS satellite orbit/clock corrections and code biases through the B2b signal, all geared toward achieving high PPP performance for users in China and the surrounding regions [8,9]. More recently, an open Python toolkit CSSRlib has been created to leverage SSR corrections from multiple free services, allowing for a straightforward comparison and use of different augmented PPP services [10]. 

In contrast to regional services, the European Union is actively progressing in the development of the Galileo High Accuracy Service (HAS). Galileo HAS is expected to play a pioneering role by offering free Signal-in-Space (SIS) corrections to users worldwide. Unlike other PPP services that rely on denser reference station networks, current HAS corrections are generated by 15 Galileo Sensors Stations (GSS) and related infrastructure, and they are broadcasted within the Galileo C/NAV navigation message through the E6B signal at 1278.75 MHz [11]. As of January 2023, Galileo HAS initial service has been declared operational, and these corrections have been accessible both through Galileo E6-B signals and HAS Internet Data Distribution (IDD) service [1]. 

The official announcement of operational deployment of the Galileo HAS initial service has sparked significant interest in the global navigation and positioning community for exploring the potential applications of HAS PPP in civil applications. In early trials, several studies investigated HAS corrections accuracy through signal-in-space range error (SISRE) and differential code bias (DCB) differences [12, 13]. More recently, [14] provides insight into the capabilities of live HAS test signals in 2022. It was observed that these signals could deliver Galileo and GPS orbit and clock corrections with SISRE values of 10.6 cm and 11.8 cm, respectively. [14, 15] also demonstrated that GPS+Galileo HAS PPP solutions can provide real-time 95th percentile positioning performance (2-sigma) of better than 20 cm and 40 cm for cadastral surveying in the horizontal and vertical domains, respectively. Meanwhile, the maturity of GNSS and its associated augmentation services has catalyzed unprecedented growth and evolution of low-cost, multi-frequency, multi-constellation GNSS receivers and antennas. 

This surge in technological advancement has given rise to cost-effective GNSS/IMU sensor integration, which has received considerable attention within the Location-Based Services (LBS) communities [16, 17, 18]. Although progress has been made, there has been no publications of quantitative investigations of low-cost sensors HAS solutions in realistic driving scenarios. Therefore, the main contributions and novelties of this study are to answer the following questions: 1) Compared to the analysis in 2022, how do recent HAS corrections perform in terms of data availability, SISRE and DCB differences? 2) Regarding PPP performance in real-world driving environments, how comparable are HAS broadcasted corrections to CNES ultra-rapid products? 3) With the inclusion of low-cost IMU measurements, how do HAS low-cost tightly-coupled GNSS/IMU integrated solutions behave under different driving conditions?

To address the proposed questions, this article first describes the HAS corrections and the processing methodology for the HAS PPP engine. The next section depicts the experimental setup and assesses the HAS corrections in July 2023, followed by corresponding positioning performance and analysis. 

HAS Corrections Description 

Aligned with the targets proposed by the European Commission (EC), Galileo HAS Service Level 1 (SL1) has a primary goal of providing global GPS + Galileo satellite orbit, clock and biases corrections, conveyed at a data rate of 448 bits per second and structured in a format similar to CSSR. The aim is to facilitate PPP-based horizontal and vertical accuracies better than 20 cm and 40 cm, respectively, with a convergence time of 300 seconds and 99% data availability. Furthermore, Galileo HAS Service Level 2 (SL2) is designed to extend the offerings by providing atmospheric corrections to users within the European Coverage Area (ECA). This expansion makes so-called “PPP-RTK” feasible, potentially reducing the convergence time to less than 100 seconds. The full operational deployment of Galileo HAS is scheduled for the coming two to three years, promising further advancements in satellite-based positioning accuracy and capabilities [2].

As outlined in the Galileo HAS information note, the implementation of Galileo HAS is organized into three phases, as depicted in Figure 1 [2]. Phase 0 involved the successful completion of HA testing and experimentation activities between 2019 and 2022, validating Galileo’s dissemination capabilities. Phase 1, referred to as HA Initial Service, was designed to provide an SL1 service with reduced performance. This phase officially began in January 2023. HAS implementation will then advance to Phase 2, achieving full implementation of Galileo HAS and meeting performance objectives of SL1 and SL2. Current improvements being focused on include additional reference stations and the introduction of Galileo and GPS satellite phase bias corrections, which will allow for faster and more accurate PPP-AR (PPP with carrier-phase ambiguity resolution) on the part of users.

According to the Galileo HAS Interface Control Document (ICD) [19] the constituent elements of HAS corrections involve 1) Satellite orbit corrections to the broadcast ephemerides; 2) Satellite clock corrections to the broadcast ephemerides; 3) Satellite biases. It’s important to note that, as of the information available in the ICD, satellite phase biases are still under development and are not accessible to users at this time. The HAS user reference algorithm (that will be made available for free to any interested party), will ease the accessibility to this service worldwide.

HAS Orbit Corrections

The HAS service provides orbit corrections for GPS and Galileo satellites in the Satellite Coordinate System (SCS), comprising radial, along-track, and cross-track (RAC) components. These corrections are associated with the ionosphere-free antenna phase center (APC) of the satellite, specifically for GPS LNAV and Galileo I/NAV messages.

In general, HAS orbit corrections cover a range of ±10.2375 m, ±16.376 m, and ±16.376 m for the respective RAC directions, with updates occurring at 50-second intervals and a validity period of 300 seconds. Equation 1 illustrates the relationship between the HAS corrected satellite positions  and corresponding corrections δR^s.

where x_s denotes the broadcast satellite position, and  stands for the rotation matrix employed to transform the corrections from the RAC system into the designated Earth-Centered Earth-Fixed (ECEF) frame. As post-processing products from ACs are based on the center of mass (CoM), there is a viable option to convert the APC-based HAS orbits to CoM-based orbits by applying the ionospheric-free phase centre offsets (PCO) corrections sourced from the supplementary ANTEX files:

HAS Clock Corrections

As with the HAS orbit corrections, HAS clock corrections refer to the ionospheric-free combination of the GPS LNAV signals (L1 C/A and L2P) and Galileo I/NAV signals (E1 and E5b). For each satellite, the HAS corrections denoted as δC^s, are computed from the Delta Clock Correction (DCC) and Delta Clock Multiplier (DCM), falling within a range of ±40.95 m, with a 10-second update interval and a 60-second validity period. Prior to being incorporated into the ionospheric-free broadcast navigation clock errors dt^s, it’s essential to consider the relativistic correction  for Galileo satellites. Equation 3 depicts the expression for HAS clock errors:

where  and dt^s are the corrected clock error and broadcast clock error for Galileo satellites, and c is the speed of light.

HAS Satellite Code Biases

Aside from orbit and clock corrections, HAS encompasses support for satellite code biases corrections that are applied to GPS on L1 C/A, L2C, and L2P signals and Galileo on E1 C, E5A Q, and E5B Q signals. Unlike the satellite Differential Signal Bias (DSB) products, HAS code biases are disseminated in the format of Observable-specific Signal Biases (OSBs). These code corrections are framed as pseudo-absolute biases, enabling the direct application to the corresponding pseudorange measurements for users. The range of these biases spans ±20.46 m, with a 50-second update interval and a 60-minute validity period. An example of the conversion between DSB and OSB corrections is shown as:

where  are the DSB of the Galileo C1C and C5Q code observations, while  and  are the OSB of the Galileo C1C and C5Q, respectively.

Methodology and Processing Architecture

This section begins with the basic mathematical methodologies used for the PPP/IMU tightly-coupled integration, followed by the processing architecture of the York University HAS PPP processing engine.

PPP and Tightly-Coupled Methodology

The dual-frequency observations from both GPS (L1/L2) and Galileo (E1/E5b) signals are employed for PPP processing, and the uncombined PPP (UPPP) model is expressed as:

where the pseudorange and carrier-phase measurements on frequency i (i∈{1,2}) are denoted as P and Φ, respectively;  is the geometric range between satellite s and receiver r; dt_r and dt^s represent the receiver and satellite clock offset, and c is the speed of light; f_i refers to the signal frequency on i, and I and T stand for slant ionospheric delay and slant tropospheric delay, respectively; b_P and b_Φ are the code and phase biases, respectively. N is the unknown ambiguity in cycles and λ is the carrier wavelength; ε_P and ε_Φ are pseudorange and phase noise, respectively. In the HAS PPP processing, satellite clock offset (dt^s) and satellite code biases () are provided by HAS corrections.

Incorporating IMU sensor integration, this research uses the tightly-coupled method that integrates the GNSS pseudorange and carrier- phase raw measurements together with IMU measurements into the extended Kalman filter. After iterations and passing the sanity check, the variables from GNSS and IMU can be estimated as:

where δR_x,y,z and δV_x,y,z denote the position and velocity errors in ECEF coordinate system, respectively; δT_r^s stands for the zenith tropospheric delay, which is converted into slant delay with corresponding mapping function. δA_x,y,z refers to the attitude errors in the local navigation system, and b_ax,ay,az and b_gx,gy,gz are the accelerometer and gyroscope biases, respectively.

York HAS Processing Engine 

Figure 2 depicts the processing architecture for the York HAS engine. The HAS corrections and broadcast ephemeris are initially introduced and processed in the Correction Handler module of the code. Subsequently, the calculated HAS orbit, clock and code OSB corrections are directed to the GNSS Handler module. After applying the HAS corrections, the GNSS handler and IMU Handlers acquire and synchronize the raw measurements. The IMU Handler is responsible for aligning IMU raw measurements, initialization and compensating for biases estimated from the previous epoch. Subsequently, the predicted states encompassing attitude, positioning and velocity are conveyed to the TC (tightly-coupled) Handler module. In conjunction with the GNSS measurements, the TC handler undertakes the integration of GNSS and IMU data through the Extended Kalman filter processing engine, with the objective of estimating the unbiased states as shown in Equation 6. Following the quality control and sanity assessments, the York HAS engine advances to the subsequent epoch for processing.

Experimental Setup and HAS Assessment

To investigate the HAS corrections and our proposed algorithms, multiple vehicle experiments were carried out in realistic driving environments. This section introduces the corresponding experimental setup and HAS assessment. 

Measurement Campaign 

To evaluate the effectiveness of HAS corrections and the performance of the York PPP engine, a series of vehicular experiments were conducted in the vicinity of York University, Toronto, Canada. The experimental configuration, depicted in Figure 3, consists of two data collection setups: 1) The geodetic collection employs a NovAtel SPAN (comprising an OEM7 GNSS receiver and Epson IMU) integrated with a NovAtel antenna. 2) The low-cost collection equipment comprises a Septentrio Mosaic-X5 receiver paired with a Tallysman patch antenna. Furthermore, an automotive-grade Xsens MTi-7 IMU is affixed on top of the experiment vehicle. The HAS log files, decoded by NovAtel, are used as input data for the York PPP engine to generate HAS PPP/TC solutions. Additionally, a base station using a NovAtel OEM7 receiver and a geodetic-grade antenna is mounted on an open rooftop within a 5 km baseline length to provide the reference trajectory processed by the NovAtel Inertial Explorer software.

To simulate daily driving environments, four kinematic tests were conducted on different days with a similar route and different multipath profiles. Table 1 highlights the corresponding details of the four vehicle experiments, including test identifiers, collection dates, UTC timestamps, and traffic conditions. Note the traffic conditions fluctuated at different local times, primarily due to variations in traffic volume and traffic density.

Figure 4 shows an aerial street view of the vehicle experiment, which includes multiple multipath profiles like open-sky parking lots, vegetation roads, suburban roads, as well as overpasses. It is anticipated that the GNSS-only positioning solution would experience a significant degradation when the vehicle passes under an overpass due to the limited number of observations. This signal block is the rationale for integrating a low-cost IMU into the navigation solution to enhance robustness and overall positioning performance.

Assessment of HAS Corrections

To evaluate the HAS corrections, a comparative analysis is performed across various criteria, including data availability, Signal-in-Space Range Error (SISRE) and DCB differences. The decoded ASCII HAS files used in this study were provided by Hexagon | NovAtel, a member of the GISCAD- OV project team (giscad-ov.eu).

Data Availability

The results presented focus on the assessment of HAS corrections data availability over a one-week period, from July 22 to July 29, 2023. Considering the HAS orbit and clock corrections are provided with distinct timestamps, their availability is initially examined separately. As shown in Figure 5, green regions denote the presence of corrections accessible to users, while red dots represent instances where HAS corrections were unavailable during those time intervals. Note these results exclusively account for the existence of corrections, without taking into account their validity periods. Both Galileo and GPS exhibit a high degree of HAS orbit availability, with Galileo achieving close to 100% availability, and GPS at ~98%. In contrast, HAS clock availability is somewhat lower, with Galileo achieving 99% availability and GPS satellites attaining 92% availability.

Both orbit and clock corrections are integral components of PPP processing, so it is important to consider them not only in terms of data availability, but also in regard to their respective validity periods. Figure 6 illustrates satellite-specific data availability, and the analysis reveals that, on average, Galileo and GPS satellites can achieve data availability rates of 99% and 92%, respectively. These figures represent an improvement over last year’s performance, where Galileo attained 97% availability, and GPS achieved 91% [14].

Orbit and Clock SISRE Analysis

In the SISRE analysis, a direct comparison is conducted between HAS orbit and clock corrections and the final orbit and clock products provided by the Center for Orbit Determination in Europe (CODE), recognized for its high-quality products. And the detailed SISRE computation equations can be referred to in paper by [20]. Similar to the data availability analysis, the datasets gathered from July 22 to July 29, 2023, are analyzed. Figure 7 shows the SISRE results for HAS orbit 3D and clock corrections specifically on July 22. GPS and Galileo satellites are represented in blue and green dots, respectively.

Figure 8 presents an overview of the average orbital SISRE (represented in green) and total SISRE (represented in purple) for both Galileo and GPS satellites over one week. Owing to unexpected larger errors, G07, G09 and E33 satellites have been excluded from the computation and deserve further investigation. Additionally, Table 2 highlights the overall statistics, indicating HAS is capable of providing orbital and clock corrections with SISRE values of approximately 11 cm and 16 cm, respectively. These accuracy levels are consistent with those observed in 2022 [14]. 

OSB Analysis

In addition to orbit and clock corrections, HAS also provides support for satellite code bias corrections, which are applied to GPS on L1 C/A, L2C, and L2P signals, as well as to Galileo on E1 C, E5A Q, and E5B Q signals. Currently, HAS phase biases are not available to users, so the assessment of PPP-AR (PPP with carrier-phase ambiguity resolution) must wait as future work. To assess the accuracy of HAS OSBs, DCB products from the Chinese Academy of Sciences (CAS) are employed as a reference. Figure 9 and Table 3 indicate the differences in DCB 
between HAS and CAS products are at the sub-nanosecond level. This analysis aligns with the previous conclusion that HAS OSB accuracy remains consistent with the levels observed in 2022 [14]. 

Positioning Results and Analysis

SPP Solutions 

To investigate positioning performance in real-world driving conditions using low-cost sensors, two different GNSS configurations namely SPP (single point positioning) and HAS PPP are initially compared. This comparison is based on the dataset collected on July 25, 2023. SPP represents a traditional GNSS positioning technique frequently employed with low-cost GNSS receivers that are only capable of receiving GNSS pseudorange observations. Figure 10a displays the time series of horizontal errors generated by SPP and HAS PPP. These errors are represented by the red and green lines, respectively. Figures 10b and 10c show the corresponding time series for the number of processed satellites and observations. The observations reveal SPP has the capacity to process a larger number of satellites as compared to HAS PPP. This result is primarily due to the limited availability of HAS corrections. However, despite having access to fewer satellites, HAS PPP consistently delivers more accurate and stable positioning solutions overall when compared to SPP solutions. The improvement is particularly notable when considering metrics such as the 95th percentile errors, 68th percentile errors, and overall rms, as outlined in Table 4. This enhanced performance is attributed to the inclusion of precise carrier phase measurements in the HAS PPP method.

It is worth noting that SPP solutions may, at times, exhibit superior accuracy compared to HAS PPP. This idiosyncrasy occurs when SPP processes a greater number of satellites, leading to more favorable Geometric Dilution of Precision (GDOP), as demonstrated in Figure 10d. Consequently, the effective use of additional satellites and the enhancement of DOP values in HAS PPP solutions deserve further investigation. Additionally, the performance of GNSS-only solutions degrades significantly at certain epochs when the vehicle was traversing an arterial road located beneath a highway viaduct—a notably challenging environment extending over 100 meters.

Positioning Performance Comparison with HAS and CNES Products

A comparative analysis was conducted between HAS corrections and the ultra-rapid products provided by CNES. To ensure an equitable comparison, the DCB values provided by CAS are also taken into consideration when processing CNES PPP solutions, and the satellite orbit, clock and code bias corrections are applied for both GPS and Galileo constellations and processed in the same dual-frequency uncombined mode. Float solutions were examined as HAS satellite phase biases are currently not transmitted to users. Figure 11 presents the time series of low-cost PPP horizontal errors for datasets 1 to 4. The PPP solutions generated by CNES and HAS products are illustrated by blue and green lines, respectively. The red dashed line indicates the convergence threshold. Defining a precise convergence threshold in dynamic environments with frequent signal loss and filter initialization can be challenging, so a more lenient convergence threshold of 50 cm was set.

Table 5 presents a comprehensive analysis of the 95th percentile errors, 68th percentile errors, overall rms, and standard deviation for CNES (left) and HAS (right) PPP solutions throughout the datasets. CNES PPP solutions show superior accuracy and stability compared to HAS PPP solutions, primarily due to the higher availability of satellites in CNES corrections. When focusing on the 68th percentile horizontal performance, where an adequate number of satellites are available for GNSS processing, HAS PPP provides comparable positioning performance to CNES ultra-rapid PPP solutions. CNES PPP solutions generally have better performance than HAS PPP, but the results show the potential of HAS corrections in mass-market applications requiring precise navigation.

Positioning Performance Enhancement with IMU Integration

To mitigate potential positioning errors resulting from GNSS outages, we have tightly-integrated a low-cost IMU with the PPP configuration. Figures 12 and 13 present the time series of positioning errors obtained from the CNES (depicted in blue) and HAS (depicted in green) corrections, with their TC solutions shown in orange lines. It is evident the integration of the IMU leads to a substantial reduction in GNSS outage-related errors across the tested datasets. For dataset 1, which serves as an illustrative case, significant levels of 67% and 75% improvements of overall rms can be observed for CNES and HAS PPP solutions, highlighting the significant advantages of IMU integration.

Figure 14 offers a comprehensive overview of horizontal positioning errors across four datasets, encompassing four combinations of processing strategies. CNES and HAS PPP solutions are represented by blue and green bars, respectively, while their TC solutions are depicted in lighter shades. Several significant conclusions can be drawn from this analysis: 

1) As expected, CNES PPP solutions exhibit superior performance compared to HAS PPP solutions. Specifically, CNES PPP achieves 0.8 m and 0.6 m for the 95th percentile errors and overall rms, respectively, outperforming HAS PPP solutions, which achieve 1.1 m for the 95th percentile errors and 0.7 m for overall rms. However, when focusing on the 68th percentile errors, HAS PPP solutions exhibit comparable positioning performance to CNES products. 2) The TC integration demonstrates little enhancement for 68th percentile positioning, suggesting the inclusion of the IMU does not significantly impact GNSS-only solutions when a sufficient number of observed satellites is available. 3) It is noteworthy that both HAS and CNES TC solutions achieve a horizontal positioning rms of 0.5 m. This indicates the integration of a low-cost IMU effectively narrows the performance discrepancy between using HAS and CNES products, which is likely attributed to limited HAS availability, where IMU mechanization solutions play a more substantial role in determining the final positioning.

Conclusions and Future Work 

To investigate the PPP performance of HAS corrections with low-cost sensors in real-world driving environments, four vehicle experiments were conducted close to York University. The final results provide insights into addressing the posed questions:

Compared to the analysis conducted in 2022, this current study reveals an improvement in data availability. On average, the data indicates that Galileo corrections exhibit an availability rate of 99%, while GPS corrections demonstrate an availability rate of 92% during the period from July 22 to July 29, 2023. However, the SISRE and DCB differences results do not show any significant improvements regarding the accuracy of HAS corrections.

In the context of PPP performance within real-world driving environments, it is evident that CNES PPP solutions consistently outperform HAS PPP solutions when considering metrics such as 95th percentile errors, overall rms and standard deviations. However, an interesting and noteworthy finding is HAS PPP solutions demonstrate comparable, and in some cases, superior performance in terms of the 68th percentile errors. This observation highlights the significant potential of HAS corrections in Location-Based Services (LBS) applications where precise positioning is crucial.

The inclusion of the low-cost IMU leads to several important insights. First, the TC solutions do no harm to GNSS-only solutions when a sufficient number of satellites are available. Furthermore, TC solutions play a pivotal role in significantly mitigating positioning errors during GNSS outages, enhancing the robustness of positioning systems in challenging environments. Most notably, the integration of TC solutions effectively narrows the performance gap between using HAS and CNES corrections, leading to a remarkable achievement of 0.5 m rms for horizontal positioning performance, even in challenging environments. 

For future work, the analysis will be expanded to include PPP ambiguity resolution by incorporating HAS phase bias corrections when they become available. Additionally, it is anticipated that PPP-RTK will become a feasible option within the European coverage area once HAS Phase 2 is fully implemented. Furthermore, improvements to the HAS DOP will be made through Galileo broadcast navigation messages, and these HAS studies will be extended to smartphone applications. These improvements open exciting possibilities for enhancing location-based services and navigation capabilities on widely accessible mobile devices. 

Acknowledgements

The authors would like to thank the EU Horizon 2020 project GISCAD-OV (Grant Agreement 870231) and the Natural Science and Engineering Research Council of Canada for providing funding for this work. And the authors would like to thank the data contribution from the IGS and Hexagon | NovAtel (decoding HAS corrections) and acknowledge the collaboration from Sogei. Finally, the York authors would like to thank their colleagues at the GNSS Laboratory for their support in collecting field data.

This article is based on material presented in a technical paper at ION GNSS+ 2023, available at ion.org/publications/order-publications.cfm. 

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Authors

Ding Yi is a Ph.D. candidate in the Department of Earth and Space Science and Engineering at York University, Toronto, Canada. Previously, he received his undergraduate degree in Geomatics from Wuhan University in China and obtained a master’s degree in Geomatics Engineering from the University of Stuttgart, Germany. Currently, his research interests involve precise point positioning (PPP) technology and multi-sensor integration.

Nacer Naciri is a postdoctoral fellow at the NASA Jet Propulsion Laboratory. He holds a Ph.D. from York University, Canada, as well as an aeronautics engineering degree from ISAE-SUPAERO in France, and an M.Sc. in aerospace engineering from KTH Royal Institute of Technology in Sweden. His research interests involve multi-GNSS, multi-frequency PPP-AR. 

Sunil Bisnath is a Full Professor in the Department of Earth and Space Science and Engineering at York University, Toronto, Canada. He received his Ph.D. in Geodesy and Geomatics Engineering from the University of New Brunswick. For over 25 years, he’s actively researched GNSS processing algorithms for positioning and navigation applications.

F. Javier de Blas is the Commercial and High Accuracy Service Manager at the EU Agency for the Space Programme (EUSPA). He has been leading the implementation of the Galileo HAS and CAS services, while actively contributing to Galileo Services’ Management activities within the Agency. He holds a M.Sc. degree in Aeronautical Engineering and a master’s degree in Airport and Air Navigation Systems from the Technical University of Madrid.

Roberto Capua is responsible for GNSS R&D at Sogei, the technological partner of Ministry of Economy and Finance of Italy. He received his master’s in Electronic Engineering from Sapienza Università di Roma and has 25 years of experience in the field of GNSS applications, research and development for public and private organizations. His areas of activity include advanced GNSS augmentation systems for high accuracy and integrity, GNSS software receivers and GNSS surveying.

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ESA intends to extend the NAVISP program. The fourth phase of the program, to be dubbed NAVISP Next, will be officially proposed for approval at the next ESA the Ministerial Conference in 2025.

NAVISP Next will continue the work of bolstering the competitiveness of the European positioning, navigation and timing (PNT) industry, aiming to surpass its current 17% global market share and achieve a target range of 20-30%. The program will outline strategies to spread its influence across the entire value chain, promoting private public partnership (PPP) approaches with leading market entities. The aim will be to diversify funding sources, enabling the leveraging of funds from non-space sectors.

Speaking at the recent NAVISP Industry Days 2023 at ESA’s Space Research and Technology Centre (ESTEC) in Noordwijk, the Netherlands, NAVISP Program Manager Pierluigi Mancini provided some background to current global technology trends, of which PNT, he said, is the backbone. “The geopolitical situation continues to evolve,” he said, citing, “European concerns about security and sovereignty, as demonstrated by recent EU acts pertaining to chips and critical raw materials, and the UK’s declaration of a new PNT strategy.

“New Space economic dynamics now favor the concentration or vertical integration of infrastructure and services,” Mancini said, “while technology markets are demanding more and better PNT. These markets include defense, consumer products, automotive, transport and logistics, finance and critical infrastructure.” He also cited the rising global trend towards PTA (protect, toughen and augment) strategies driving PNT enhancement, including space-based augmentation system (SBAS) expansion and new, non-GNSS-related PNT development, i.e. alternative, assured and/or complimentary PNT.

Market standing

“Right now, consumer automotive is the largest downstream market for PNT,” Mancini said, “followed by smartphones and wearables driving chipset sales and adoption of services. The multi-PNT trend is influencing downstream markets as well, with drone, finance and driverless vehicle applications all growing.” According to ESA, GNSS now surpasses satellite communications as the largest, space-based, downstream revenue source, with multi-GNSS and multi-frequency receivers also on the rise. “And we see new opportunities for space missions protecting overall GNSS capacity,” said Mancini, “with secondary payloads onboard new constellations, interference monitoring, etcetera.”

For NAVISP, a key priority continues to be strengthening its presence across the PNT value chain, which means understand PNT-supported verticals, developing PPP approaches with market owners, and supporting European PNT-related ecosystems. “One of the keys to our ensuring future market positioning,” Mancini said, “is to understand the new markets for these disruptive technologies. There may be a large risk involved in investing is these technologies today, but that means more opportunity for market growth tomorrow.”

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