Choosing Among High-Accuracy Location Solutions
Jan 17, 2013
Marketing analytics firm ABI Research recently predicted revenue from location-based services to surpass $4 billion this year, bolstered by widespread adoption of smartphones. Ubiquity of the smartphone platform and rapidly maturing high-accuracy mobile location technologies have spawned many new applications and advertising opportunities that rely on accurate location information. Consumer applications such as health and fitness (on track for 100 million downloads this year) and family tracking (37 million downloads this year), enterprise applications such as fleet management and asset tracking, and location solutions for public safety and security are driving this impressive growth. Wireless operators are doing their part by upgrading networks to meet the demand for high-accuracy location-based services. However, high-accuracy location technologies are not all alike. This inaugural guest blog provides an overview and taxonomy of the high-accuracy mobile location technologies that increasingly impact how we live and work.
U-TDOA (Uplink Time Difference of Arrival)
U-TDOA estimates the location of a mobile device by measuring the time it takes signals to travel between the device and specialized fixed infrastructure installed in the cellular network – in fact, the “uplink” nomenclature refers to signals that travel from the device to the network. It is the difference in signal travel time from the device to two measuring stations (the TDOA part of the acronym) which creates a hyperbolic line-of-position on which the device must lie; by intersecting TDOA hyperbola from many measuring stations, a final location estimate is derived. In the same way that the network carrier installs antennas and base station receivers to service each air interface technology (2G/3G/4G), the measuring stations also require hardware upgrade to remain compatible with continuing network evolution.
Assisted GPS (A-GPS)
A-GPS is a location solution wherein a specialized receiver chip in the mobile device measures the time of arrival of signals from the constellation of orbiting GPS satellites. Interestingly, since the receiver chip solves for the three spatial dimensions plus time, there need to be simultaneous measurements from at least four GPS satellites. The “assisted” in A-GPS refers to aiding information that the cellular network may provide to the handset in order to overcome the startup and sensitivity issues that GPS receivers frequently experience. In clear and open sky conditions, GPS and A-GPS can achieve very impressive accuracy; however, this technology often works poorly or not at all in urban or indoor environments. While the smartphones that are the focus of many emerging location-based services and applications are predominantly equipped with the specialized receiver chips and algorithms for GPS/A-GPS positioning, many existing handsets and feature-phones lack this capability.
RF Pattern Matching (RFPM)
RFPM is a high-accuracy location system which utilizes received signal strength, time of arrival, and other measurements made by the mobile device to determine location via a high-reliability client/server architecture. This technology leverages the power of a geo-referenced cellular Predicted Signature Database (PSD) which uses high-fidelity signal propagation models, network topology, terrain information, antenna type and orientation, tree canopy and clutter data, and accurate building floor plans to improve the location accuracy to within 50 meters in difficult urban and indoor environments. One interesting characteristic of RFPM is that non-line-of-sight conditions in dense urban and indoor settings impart structure and complexity to the PSD models, which in turn yields improved “fingerprinting” accuracy in these very challenging environments. Surprisingly, since all measurements are made by the mobile device as part of its normal mobility protocol, there is no dedicated hardware required in the network and no specialized signal processing in the handset.
Included in the taxonomy of cellular-based location methods are cell-ID and enhanced cell-ID. Cell-ID is a lower-cost version that assigns the mobile device location to the center of the serving cell tower coverage area; enhanced cell-ID may improve on simple cell-ID by including in addition some parametric models of the local environment.
A hybrid solution incorporating more than one sensor technology can further improve the accuracy and robustness of a mobile location system. The best hybrid solutions should seek to exploit the best strengths of each individual location technique in a complementary manner. For example, A-GPS and RFPM have been successfully combined in a number of deployments to deliver consistent performance, time-to-fix, and yield across a range of environments including urban, suburban, rural, outdoor, and indoor situations. Furthermore, in many cases a hybrid solution can offer a cost-effective method of delivering the high-accuracy location capability that many wireless operators require.
Ubiquitous mobile location is a capability, long in development, whose time has finally arrived. Those of us at the forefront of this industry, who have been fighting these technology battles for many years, see signs that our efforts are now coming to fruition. From the earliest days, a primary focus of ours has been serving mobile subscribers in ways that were meaningful to them and that improved their quality of life. For example, one of the leading challenges is how to accurately locate an emergency caller, whether they are indoors or outdoors, and no matter if they have the latest smartphone or a six-year old 2G feature-phone.
The challenges of ubiquitous mobile location will only grow as mobile subscribers increasingly come to rely upon their devices not only for the vast majority of voice calls (both indoors and outdoors), but also for data services and to manage a seamless blend between the digital world and the physical world around them. It should be apparent that location accuracy performance and reliability requirements vary by the type of application they serve; this in turn drives the selection of the appropriate location technology. Other factors, such as network cost and handset battery consumption, also come into play when choosing a high-accuracy location solution. In future blogs, I look forward to exploring the rapidly-expanding uses for high-accuracy wireless location.