Tag: Hybrid PPP-RTK

  • Hybrid RTK: A scalable path to high‑precision positioning for the IoT era

    Hybrid RTK: A scalable path to high‑precision positioning for the IoT era

    The world is rapidly filling with connected devices. IoT Analytics reports that 18.5 billion IoT devices were online in 2024, with growth accelerating toward an expected 21.1 billion by the end of 2025 and 39 billion by 2030. As artificial intelligence drives demand for richer, more precise device data, the need for reliable, high‑accuracy positioning becomes foundational.

    Yet today’s GNSS infrastructure — including cellular-based real‑time kinematic (RTK) networks — was never designed for this scale. Billions of devices — from vehicles to drones to industrial sensors — depend on location data, but the traditional GPS model struggles under three converging pressures: (1) massive device growth, (2) rising accuracy requirements, and (3) increasing vulnerability to interference.

    These pressures are reshaping expectations for positioning, navigation and timing (PNT) and creating demand for a new, more resilient delivery model.

    Why Accuracy and Resilience Matter More Than Ever

    Autonomous systems are the clearest example of the accuracy challenge. Xona Space Systems CTO Dr. Tyler Reid notes that safe autonomous driving requires 10 cm accuracy 95% of the time and 30 cm accuracy at “eleven nines” reliability. Standard GPS, accurate only to several meters, cannot meet these thresholds — even with traditional enhancement techniques.

    At the same time, GNSS signals face growing threats. Spoofing and jamming events are now daily occurrences in parts of Europe, and U.S. federal agencies increasingly require contract bidders to incorporate resilient PNT technologies alongside legacy GNSS.

    Finally, the explosion of IoT devices introduces a network‑scale challenge. Many of these devices could benefit from high‑precision positioning, but continuous unicast RTK streams are not an efficient use of cellular networks, especially as billions of devices come online.

    Together, these factors point to a simple conclusion:

    A new delivery model for high‑precision GNSS corrections is needed — one that is accurate, resilient, and scalable.

    Why a Hybrid Approach Is Required

    RTK positioning is the gold standard for centimeter‑level accuracy. It works by combining GNSS signals with correction data from a known base station. However, traditional RTK has two major limitations:

    1. Coverage constraints — corrections must be delivered within a limited range of the base station due to the fact that accuracy diminishes the further the GNSS base is from the rover.
    2. Network constraints — corrections are typically delivered over cellular networks, which become inefficient at scale.

    Precise Point Positioning (PPP‑RTK) can extend range and reduce dependency on local base stations, but today’s PPP‑RTK implementations are proprietary and lack a common standard.

    To support billions of devices — many mobile, many mission‑critical — the industry needs a correction‑delivery model that is:

    • Nationwide
    • Efficient at scale
    • Resilient to interference
    • Cost‑effective for high‑volume IoT deployments

    This is where hybrid RTK becomes essential.

    Introducing Hybrid RTK: A Dual‑Path Delivery Model

    Hybrid RTK refers to the dual‑path delivery of GNSS correction data, consisting of:

    • Primary path: ATSC 3.0 broadcast
    • Fallback path: Cellular (LTE/5G)
    • Upstream messaging: Cellular for acknowledgments or device telemetry

    Compared to a satellite-based RTK solution or even a cellular-only RTK solution, hybrid RTK will deliver corrections over a far more reliable and scalable network, because it’s both broadcast and terrestrial-based.

    Why broadcast first?

    ATSC 3.0 provides:

    • One‑to‑many multicast efficiency
    • Predictable capacity and uniform latency
    • Wide coverage footprints
    • Strong penetration in dense urban environments
    • Lower cost per delivered bit

    This makes it ideal for distributing high‑precision correction data to large numbers of devices simultaneously — something cellular networks are not optimized for.

    Why cellular second?

    Cellular fills in:

    • Coverage gaps where ATSC 3.0 is not yet deployed
    • Uplink needs (e.g., device status, position feedback)
    • Mobility scenarios requiring two‑way communication

    The result is a resilient, nationwide correction layer that scales with IoT growth.

    EdgeBeam Wireless: A New Entrant with a Broadcast‑First Architecture

    EdgeBeam Wireless is deploying a hybrid RTK network that leverages the existing infrastructure of U.S. television broadcasters — including secure facilities, hardened towers, and nationwide engineering resources — for both over-the-air RTK delivery and collocating GNSS base stations.

    This approach provides several advantages:

    • Accelerated deployment of GNSS base stations designed to complement existing base networks.
    • Lower infrastructure costs than cellular‑only RTK networks.
    • High reliability through broadcast delivery.
    • Scalable distribution for dense IoT environments.
    • Nationwide reach as ATSC 3.0 coverage expands.

    EdgeBeam’s broadcast‑first model — branded by the company as  “Enhanced GPS” or  “eGPS” — is best understood simply as hybrid RTK with broadcast as the primary downlink. While this hybrid approach does require some additional hardware to receive the broadcast, pricing is already very competitive to cellular because these chips will be found in every television set in the country. Moreover, EdgeBeam already has products available for end users that want to leverage a hybrid network without having to do any development work.

    Broadcast RTK: A New Network Layer at the Edge

    Broadcast RTK uses ATSC 3.0 to distribute GNSS correction data over the last mile. This creates a new edge network layer that can support both GNSS and other data applications, including:

    • High‑precision GNSS corrections
    • Multicast distribution of positioning data
    • Offloading of appropriate high‑volume traffic (e.g., video) from cellular networks
    • Enterprise‑grade reliability for industrial and transportation systems

    By shifting the heavy downlink load to broadcast, cellular networks are freed to handle uplink messaging and mobility support — a more efficient division of labor.

    This hybrid architecture is not just about improving individual device accuracy. It enables something more powerful.

    A New Generation of Shared Situational Truth

    When many devices operate on the same centimeter‑accurate reference frame at the same time, a new capability emerges: Shared Situational Truth (also known as shared situational awareness).

    This refers to a consistent, real‑time understanding of location and timing across a fleet, system, or environment. Hybrid RTK enables this by delivering synchronized, high‑precision PNT to large numbers of devices simultaneously. By offloading RTK delivery to a broadcast network, cellular and other communication networks can then be used to share a device’s position and other data with other local devices.

    What is being shared?

    • Precise location
    • Precise timing

    Who is sharing it?

    • Vehicles
    • Fleets
    • Drones
    • Industrial robots
    • Infrastructure sensors
    • Emergency services
    • Insurance and logistics platforms

    What does it enable?

    Examples include:

    • Safer ADAS/ADS through lane‑level awareness
    • Collision avoidance for drones and autonomous systems
    • Fleet optimization using precise, time‑aligned movement history
    • Improved insurance models through reliable behavior measurement
    • Faster accident resolution with time-synchronized location records
    • Infrastructure‑to‑vehicle coordination for road hazards or construction zones

    In transportation alone, EdgeBeam’s hybrid RTK solution could make entire traffic systems safer and more predictable — not just individual vehicles.  And importantly, this can be done far more efficiently than via just a cellular-based solution.

    Conclusion: A Foundational Shift in PNT Delivery

    The convergence of IoT growth, accuracy demands, and GNSS vulnerabilities is forcing a rethinking of how high‑precision positioning is delivered. Hybrid RTK — with broadcast as the primary downlink and cellular as a complementary path — offers a scalable, resilient, and cost‑effective solution.

    For industries ranging from automotive to logistics to public safety, the shift from “nice‑to‑have” to “must‑have” high‑precision PNT is already underway. As hybrid RTK networks expand, the ability to deliver centimeter‑level accuracy at scale will unlock new applications, new efficiencies, and new expectations for how devices understand and interact with the world.

    EdgeBeam Wireless is building this new correction layer — one designed for the billions of devices that will depend on precise, reliable positioning in the years ahead.

  • New players offering GNSS correction services

    New players offering GNSS correction services

    Thirty years ago, more than a decade before most people had even heard of GPS, receiver manufacturers and surveyors were already improving on it by providing and using correction services to compensate for errors in the system—including clock drift, orbit errors, signal errors, atmospheric errors and multipath.

    Today, dozens of public and commercial correction services enable users to achieve accuracies of decimeters, centimeters or even millimeters. Also, many GNSS processing services correct measurements taken in the field using data from reference points. Increasing positioning accuracy has become the cornerstone of modern GNSS practice.

    The current boom for correction services is driven mostly by the demand for high accuracy from the automotive industry (including the development of self-driving cars), as well as smart consumer devices and various forms of automation. Automotive companies and telecoms are deploying infrastructure around the globe to provide centimeter-level positioning. GNSS satellites also can transmit corrections directly, as the Japanese CLAS service from the QZSS constellation does, and Galileo’s High-Accuracy Service (HAS) soon will. To compensate for receiver-side issues — multipath, jamming and spoofing — some GNSS receivers also incorporate advanced positioning algorithms.

    Clock and orbit errors are specific to each satellite; they do not depend on the position of the receiver. But atmospheric errors are introduced when the signal travels from the satellites to the user. Reference stations (base stations) of GNSS receivers installed at fixed and precisely surveyed positions provide corrections that compensate for both sets of errors to the rovers carried by field crews. When connected, reference receivers spread over a geographic area form reference networks, such as that of continuously operating reference stations (CORS). Achieving maximum accuracy requires initializing the receiver, which can take a few seconds to several minutes, depending on the type of corrections.

    Established and new methods

    Two established methods have been used for decades.

    Real-time kinematic (RTK). In RTK, a receiver obtains correction data from a single base station or a local reference network in the same area.

    Precise point positioning (PPP). While accessible from anywhere in the world, receiver initialization for PPP can take up to 30 minutes. Also, a few PPP correction services only provide corrections for satellite clock and orbit errors and not for atmospheric errors, limiting users to a lower accuracy level than with RTK.

    Hybrid PPP-RTK. In recent years, new methods have emerged. Hybrid PPP-RTK combines near-RTK accuracy and quick initialization times with the global access of PPP. It relies on a network of reference stations within about 150 kilometers of each other. The stations collect GNSS data and calculate both satellite and atmospheric correction models. The network then broadcasts these corrections via internet, satellites or cellphone towers to subscribers, who can use them to achieve sub-decimeter accuracy.

    Each of these methods has advantages and disadvantages (see table 1). RTK, which relies on communication between the user and the local correction service, provides centimeter accuracy over small areas. PPP-RTK and PPP broadcast corrections and require a lighter infrastructure, making them scalable for mass-market and industrial applications. The new services are cheaper and more user-friendly than traditional correction services.

    TABLE 1: Differences of various correction methods. (Chart: Septentrio)
    TABLE 1: Differences of various correction methods. (Chart: Septentrio)

    CORS/VRS

    Traditional reference networks — often called CORS or virtual reference station (VRS) networks — have long been a source of differential GPS (DGPS) and RTK corrections, mainly for surveying and mapping applications, which require high accuracies.

    “Most CORS in the United States are strictly for providing high-accuracy correction data to GNSS users who need to know their position to less than an inch,” said Alex Ngu, applications engineer at Trimble. “However, some — like Utah’s TurnGPS network and the North Carolina Geodetic Survey (NCGS) — have considered dabbling in using them to double up for weather monitoring.” In some regions, such as Japan and Washington state, CORS are also used to study plate tectonics and provide early warning of earthquakes.
    CORS receivers often operate in remote locations and may be powered by solar panels. Therefore, they require low power consumption and the ability to configure, run and update remotely. They also need to archive on-board measurements and withstand harsh environments.

    Changes in the market

    As the market for GNSS corrections changes, so does the role of CORS networks. They are increasingly used for industrial automation that needs centimeter accuracy, including construction and agriculture. “Now, due to the growth in autonomous systems, such as autonomous cars, people are looking at corrections in a completely different way and with more focus on mass markets,” said Gustavo Lopez, market access manager at Septentrio. Septentrio lets customers choose which correction service to use.

    “CORS/VRS networks will keep focus on performance and on adding constellations and signals, but nothing major is expected to happen in these traditional systems,” Lopez said. They will continue to exist because they focus on centimeter-level accuracy for survey, construction, mining, machine control and precision agriculture. “What will really change the market are these new services with 10-cm to 20-cm accuracies, which also offer a new way of delivering the data, namely broadcasting rather than using two-way communication methods.” This helps with adoption by emerging applications, Lopez said.

    He predicts that applications needing 10- to 50-centimeter acurcy will migrate to cheaper services, including new consumer applications, advanced driver-assistance systems (ADAS), professional applications such as robotics, UAVs, logistics and internet of things (IoT) applications.

    Mobile technologies adopting dual-frequency chipsets also will need correction services. “We will see more and more telecoms interested in providing GNSS corrections as a service, as is already the case in Asia and Europe,” Lopez said. “A few CORS/VRS networks will try to capture part of this emerging applications market by reusing their technology or partnering with other companies to provide a more transparent solution.”

    One might think that the rapid expansion of the market for corrections would make it possible for traditional CORS networks to make 1-cm accuracy available at a much lower price. The roadblock is high infrastructure costs, Lopez explained. CORS/VRS networks are expensive to maintain because they require a high density of stations. New services that use broadcasting technology and PPP-RTK positioning modes rely on less dense networks.

    New uses for old CORS

    A key benefit of a VRS is that performing RTK positioning across the area it covers does not require guarding a separate GPS base station. Using VRS, the CORS network acts essentially as a continuous reference station within the entire network, enabling RTK positioning using a single rover in the field.

    Randy Osborne, VRS network manager at Louisiana State University’s Center for GeoInformatics, reports a growth in new applications beyond surveyors. VRS expanded to precision agriculture, and then into applications such as lidar and UAVs. “We are also seeing strange applications that we never thought of. For example, plumbing companies use it to navigate underground from a truck that has a position on the network, and then they vector from the truck underground into pipelines,” Osborne said. Subscribers also include companies performing survey work for fracking and petrochemical projects.

    OSR vs. SSR

    Most GNSS correction services are based either on the observation state representation (OSR) or on a state space representation (SSR) of the errors. OSR and SSR use different techniques, delivery mechanisms and core technologies.

    OSR. Legacy GNSS correction service providers supply OSR correction services; examples are RTK and networked RTK (RTN). They rely on transferring corrected GNSS observations from the nearest reference station to the rover using a standardized format. They focus on a geographic region and target surveying, machine control and precision agriculture, providing centimeter-level accuracy up to about 30 kilometers of the nearest reference station. Because these services require bi-directional communications and large bandwidth, it is hard to ramp them up for mass-market applications.

    SSR. By contrast, new players in the market for correction services, as well as some of the larger legacy ones, provide SSR correction services. SSR uses a network of reference stations to model major errors over large areas. They then transfer this model to the rovers, which create local error models and apply them to their GNSS observations. Depending on the service, accuracy ranges from less than 5 cm to 20 cm, convergence times from 10 seconds to 30 minutes, and coverage from continental to global. Because SSR corrections are broadcast, they can be more easily distributed through internet connections and L-band satellite channels. Because all the rovers rely on the same stream of GNSS correction data, SSR services work well for mass-market applications. The growth in SSR technology is driven mainly by the needs of the automotive industry but is sufficiently generic for adoption in other markets.

    The challenge of vertical accuracy

    A CORS receiver stands atop the Old River Auxiliary Control Structure, a floodgate system in a branch of the Mississippi in central Louisiana. (Photo: Trimble)
    A CORS receiver stands atop the Old River Auxiliary Control Structure, a floodgate system in a branch of the Mississippi in central Louisiana. (Photo: Trimble)

    While OSR and SSR have comparable accuracies on a horizontal plane, they differ greatly in their vertical accuracy and initialization times, Osborne said. “When we look at CORS for active control and positioning in the National Spatial Reference System, we are mainly trying to get a handle on the vertical part, as it is the hard problem to solve,” he said.

    High-precision vertical accuracy is a challenge for any GNSS-based method. Conventional surveying is still the gold standard. With differential leveling, like with digital levels, results in millimeters are possible. Post-processed GNSS, using data from a good geometry of CORS or base data, can yield results under 2 cm vertical, as can real-time OSR methods like RTK and RTN. SSR solutions, like PPP and hybrids, are presently achieving 5 cm at best. An Achilles heel for SSR vertical solutions is the lack of data for localized sources of error, like tropospheric conditions. Semi-dense networks of CORS can feed ionospheric data to speed PPP convergence, but not the level of tropospheric data needed to match the vertical results that OSR and conventional methods can.

    Trimble

    Trimble GNSS base-station receivers have been used for 40 years on every continent, according to the company. Today, products in use as CORS stations typically are Alloys, NetR9s and NetR5s. The company operates more than 300 networks worldwide, incorporating more than 5,000 CORS receivers.

    Trimble offers a full spectrum of solutions, services and subscriptions related to CORS networks. They range from supplying CORS software, hardware and services, to providing network management services to run a secondary backup system for a network, or even operating a network on behalf of its owner. For those who just want a high-accuracy correction to support their surveying, GIS or machine guidance and control work, “Trimble operates one of the largest CORS networks in the world to which users can subscribe — Trimble VRS Now, Trimble RTX and OmniSTAR services,” Ngu said.


    Feature photo:

    In Long Beach, California, correction services support the 250-foot-high Gerald Desmond Bridge project. Trevor Rice (left), president of D. Woolley & Associates, joins Kimberley Holtz, director of survey, Port of Long Beach. (Photo: Trimble)