Consulting Editor | AEC
Centimeters for everyone! The “glass floor” of high-precision satellite-based positioning and measurement has been broken and democratized. With the progressive advances in the hardware, software, terrestrial infrastructure, and multiple constellations of navigation satellites themselves, have come advances in methods to augment the signals you receive with additional data. Such data takes raw, uncorrected navigation satellite capabilities from default precisions in the range of several meters, to sub-meter, and even centimeters — in real-time.
Understanding more about how these various technologies, methods, and services work, what precisions to expect, and respective hardware, software and communications prerequisites for each, users can make informed decisions as to which to choose for their field applications. From agriculture, to marine, construction, surveying, mapping and asset management, there are positioning methods and services suitable for each.
Corrections and augmentations add more and higher accuracy data to the GNSS signals your equipment receives to help mitigate multiple sources of error that otherwise limit standalone GPS and GNSS results. These are derived from terrestrial tracking networks, to improve clock and orbit “products”, and may also include data from global, regional, or localized ionospheric and tropospheric models. Various augmented data can be delivered via radio, the Internet, or communications satellites. Delivery of augmentations by public or commercial generators of this add-on data is broadly referred to as “positioning services”. These augmentation methods and services fall into two key categories, and with some hybrids of both:
Differential: Observation Space Representation (OSR) leverages differentials between the observations of the user’s field receiver (usually referred to as a “rover”) and fixed base receivers (or networks of bases). The difference between base/network and rover helps determine how much sources of error, like ionospheric and tropospheric, can be modelled and (for lack of better term) “corrected”.
Precise point positioning: State Space Representation (SSR) implementations and methods use improved clock and orbit data, and delivers this to the rover, sometimes adding in data from global or regional ionospheric models. So, instead of differential data derived from localized observations, SSR data is a representation of modelled “states” of resource data at the moment (or valid for sliding windows of time). Precise point positioning (PPP) is the common method for applying SSR data, minimizing systematic errors based on messages in the data.”
GPS (Navstar), the first of the systems and in many ways the gold standard, has now been joined by other global constellations of satellites. Europe’s Galileo, Glonass of the Russian Federation, China’s Beidou, India’s NavIC, Japan’s QZSS, and many regional augmentation system satellites (SBAS). Combined, these systems comprise a system of systems: Global Navigation Satellite Systems, or GNSS. Get used to the term.
The skies are crowded, now with almost four times as many navigation satellites as in the legacy GPS-only era — with many more signals. One of the biggest benefits of this is that we have more satellites in view than ever before, which especially comes in handy in sky-view-challenged environments like under light tree canopy and in urban canyons.
Uncorrected: Uncorrected, GPS/GNSS is quite imprecise, and can take time to come up with a position. GNSS does ranging using the satellite signals. The simplest and least expensive GNSS receivers, like those in phones, early recreational handheld units (without any augmentation turned on), can get the basic information directly from the GNSS satellites, and yield positions within a few meters.
But there are a lot of sources of error in that equation. Most of the augmentation approaches concentrate on addressing these four key sources of error: clock, orbit, iono, and tropo. And there can be a delay in getting to the best position a receiver could be expected to achieve. This is known as “time to first fix” TTFF. Once a receiver “knows” its rough location, subsequent positions can be derived much more quickly. But if you walk out of the building with the tiny GPS chip in your phone, and if there is no augmentation, you may notice that your position is wildly off for a short while.
Pluses: Free
Negatives: Imprecise, slow TTFF
Expected precision: 1m–20m
Cellular Carrier Augmentations: There is great value in at least having positions for phones being within a few meters, not only for personal navigation, commercial applications, and especially public safety, but also in getting to those precisions rapidly. For example, the Federal Communications Commission (FCC) of the US has mandated that all cell phones sold must be capable of using a simple augmentation that is known as “AGPS” (assisted or augmented GPS). This to overcome the TTFF delay, so that semi-precise locations are available more rapidly for public safety responses. There are similar systems in many countries.
Pluses: May be included with your cellular service, improves TTFF
Negatives: Imprecise, requires a cellular service
Expected precision: 1m–10m
SBAS: Satellite Based Augmentation Systems gather observation data from regional, nationwide, or even continental networks of continuously operating GNSS stations. Together with models of iono and tropo data (depending on the system), the “correction” data is broadcast to end users from dedicated GEO satellites (that will maintain a location above a specific region as the Earth rotates).
For instance, in North America, the Wide Area Augmentation System (WAAS), was chartered by the Federal Aviation Administration (FAA). In Europe, the equivalent is EGNOS, GAGAN in India, MSAS and QZSS in Japan, SDCM of the Russian Federation, SNAS/BDSAS in development in China, SPAN for Australia and New Zealand, and others in development for South America and the Caribbean (SACCSA), KASS (Korea), and an initiative for SBAS for Africa and the Indian Ocean (ASECNA).
Pluses: Civilian SBAS is free
Negatives: SBAS satellites must be in view, hardware must have such systems enabled
Expected precision: 1m–5m (sometimes better depending on the respective system)
Broadcast DGPS: Early applications, like marine navigation, took advantage of GPS for applications like harbor approaches. Having previously relied on sextants, compass, and certain radio beacon solutions, the initial 10-meter precision of early uncorrected GPS was a game changer. Soon after the first differential solutions were delivered from fixed GPS bases and companion dedicated coastal radio towers to ships. Commonly referred to as DGPS, networks of such towers were also sometimes established inland to support river navigation and low-precision terrestrial applications like mapping.
Pluses: Typically, free broadcast services
Negatives: Requires compatible radio receiver. Many DGPS systems being phased out
Expected precision: 1m–3m (sometimes better depending on the respective system)
Real-Time Kinematic — RTK: This method is resolving sources of error by differentially examining the observations received at both a fixed “base” and the field “rover”. The corrections are often transmitted by base and rover radios (e.g. UHF, spread spectrum, long range Bluetooth, WiFi) or, via I.P. (cellular). The Achilles Heel of RTK is that the precision degrades over distance from the base. 10 km is the simple rule of thumb, though longer distances can be achieved depending on conditions like Space weather (ionospheric).
Pluses: High precision. Fast TTFF
Negatives: Need to set up or have access to a base receiver. Base can be stolen. Base setup and local conditions like multipath can impact the quality. Need to resolve geodetic reference of the base (if applicable). Degradation of solution over long baselines
Expected precision: 2cm–5cm
Network RTK — NRTK\RTN: Networks of base stations have been set up encompassing wide regions, whole states, cities, and countries — to form real-time networks (RTN). These can provide both single-base solutions from individual stations and often multiple styles of “network solutions”. Provided you have cellular coverage, you fire-up the rover, connect, and off you go with high-precision results on an established reference framework.
Pluses: High precision. No base needed. Work is done on a common geodetic reference. Most RTN do automated integrity checking. Solution good over longer baselines. Fast TTFF. Better orbits and tectonic loading models are often applied
Negatives: Need cellular comms. May need a subscription
Expected precision: 2cm–5cm
Global Positioning Services — PPP (Standard): There is a technique for deriving high precisions that is similar to SBAS in that it does not necessarily require a dense network of local reference stations like RTN, and the corrections can be delivered by communication satellites. By applying high-quality clock and orbit data to the processing of GNSS observations, one can now derive positions in the order of 2cm-5cm. But there is a long convergence time for standard services, that can range from 15-30 minutes. Once the solution has converged, you can go about at the high precision work.
Examples of such systems are Trimble RTX, Leica SmartLink, and Hemisphere’s Atlas. It is not uncommon for such PPP services to offer different flavors, and different precisions and price points for different types of end users.
Pluses: High precision. No base needed. No need to resolve geodetic reference. No baseline limits. No cell comms needed
Negatives: Long convergence time. May need a subscription
Expected Precision: 2cm–5cm
Global Positioning Services – PPP (Fast): The key drawback of standard real-time PPP is, as noted, convergence time. But there have been great improvements in the past few years. Commercial positioning services in particular have augmented their own global tracking networks with data from local and regional semi-dense (100-300-km spacing) networks of ground stations. The global networks generate high-quality clock and orbit data, and the local/regional networks add in elements like iono model data, and even (for some) tropo models. This has not only reduced the initial convergence time to under a minute, even faster in some cases, but can also improve results. These semi-dense networks, for fast PPP are rapidly propagating. For instance, the RTX Fast service now covers most of Europe and the US and Canada.
Autonomous Applications PPP and Hybrids: Dozens of developers are creating new networks of ground infrastructure or purchasing data from existing RTN to create real-time positioning services to feed integrated systems being designed and built for autonomy. Sapcorda, HERE, Swift Navigation and many more, including several of the manufacturers of high precision GNSS gear, have already stepped into the PPP-for-autonomy ring and Trimble for example is on the road with the GM Super Cruise system (that has just surpassed the 6 million mile mark for hands-free driving).
The requirements for autonomy tilt more towards resiliency and reliability than to precision. Autonomous vehicle solutions involve multiple sensors, and do not rely on GNSS alone.
There are a number of issues to consider when choosing a positioning solution — price point, hardware requirements, precision requirements, personnel training considerations, sky-view limitations, the need for relative or absolute accuracy, availability of services in a given location, etc.
Choosing the right solution is application by application. For example, why do construction companies often put up a base at construction sites for RTK instead of using RTN or PPP? Many construction companies are working with fine vertical. They are always going to try and use the solutions that give that absolute best vertical solution. If they are roughing something in there’s no worry at all for using a network or even some kind of PPP.
Then there are the numerous choices of not only PPP positioning services providers, but multiple flavors from each. For example, Trimble’s RTX has different flavors, as does some of the other PPP positioning services providers. One flavor is ViewPoint RTX (sub-meter) for asset inventory, and rough mapping — at a low price point. For farmers looking for half-meter pass-to-pass precision, there is RangePoint RTX, also at a low price point. For certain asset inventory and mapping applications, users are looking decimeter precision. For this, there is FieldPoint RTX.” Again, as the precision goes up, the price goes up. And then there is the tier that is essentially survey grade — centimeters. CenterPoint RTX gets you 2 cm once it is converged, and this is where the “fast” PPP services come into play.
We are publishing a much longer version of this article online this month, adding more info to help you understand the many options. Look for published case studies on positioning services providers websites, for applications similar to yours. And do test drives of various options. One size does not fit all, so fortunately there is a whole range of options. And we can be sure that many more are in the works.
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