Determining a point location requires trilateration relative to known location points – anchor points. GPS works the same way, with the anchor points being the satellites in the sky. For indoor, where GPS not available, the anchor points should be objects with known locations. The foundation of any accurate location estimation is an accurate distance estimation from the anchor points. With RF technologies, there are 2 common ways for range estimation:
RSSI – Received Signal Strength Indication
RSSI based distance estimation is based on the physical principle that the signal strength decreases as the distance between the transmitter and receiver grow. However, this is a very rough indication, as the signal strength decreases due to many reasons other than distance (human body effects and antennas which are no true omnic are simple examples). In the indoor environment, the accuracy of RSSI further reduces due to multipath effects. The free space path loss model (on which RSSI is based) is invalid for an indoor environment, and a valid model is very site specific, and the variations between sites and over time. Calibrating an accurate path loss model to a specific environment is a quite complex operation by itself, and where people are moving it is not very practical (the people themselves change the model with their body).
As a result, a typical practical location accuracy of the RSSI-based system implemented with WIFI APs and BLE beacons is ~3 meters. RSSI can be used with WIFI APs and BLE beacons in an application like wayfinding, where few meters accuracy is sufficient. But it cannot be referred to as accurate location technology.
ToF – Time of Flight
Very simple principle: the radio waves travel at the speed of light, so measuring the time it takes to the waves (or a packet) to travel from point A to B, and you know the distance. Yet, there are significant implementation challenges.
The key issue is to discriminate between the arrival of the direct path (the straight line between the transmitter and receiver) and the multipath (reflections from the ceiling, walls, objects, people…) which comes after. Note that sometimes the direct path is weaker than the reflections, for example where the direct path travels through a thick wall, and the multipath is a reflected through the air.
To get an accurate measurement of the time of flight, one must be able to separate the direct path from the reflections. This means, that the time duration of the RF pulse, needs to be shorter than the accuracy you are targeting.
As for the accuracy of the measurements themselves: Speed of light, commonly denoted as c is ~300,000 Km/s, or precisely 299,792,458 meters per second in a vacuum (and a bit less in air). As an example, the light will travel almost 30 cm in 1 Nanosecond, so in order to get to centimeters’ accuracy, you need to measure time in sub-nanosecond accuracy. To get good resolution it is also important to have very short signal on the time domain, to discriminate between the reflections, and this is where UWB kicks in.
Ultra Wide Band (UWB) technology uses very short pulses duration, less than 2 nanoseconds. Because of the short pulses in the time domain, UWB has an extremely wideband signal in the frequency domain (at least 500MHz, sometimes more than 1000MHz). This makes UWB suitable for ToF measurements, with accuracy better than 1 foot.
UWB is used as PHY layer of IEEE 802.15.4a standard. The frequency range is 3.5GHz – 10GHz, though different countries are using different bands.
Note that because UWB is using wide unlicensed frequency bands, the standard mandates low power emission so it will not interfere with other devices. This imposes a challenge for the range in which UWB can be used.
The short pulse duration of UWB makes it the best technology for accurate ToF measurements. When used with 500MHz bandwidth for example, the distance accuracy can get to ~10cm clear conditions. This fundamental capability enables to build powerful accurate location engines.