Positioning

Selecting the Best Positioning Technology – IoT For All

future-dyanmics





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Determining the position of an object in space can be challenging. Environment, interference, accuracy, and range are all critical factors that need to be taken into consideration when contemplating a solution. Technologies initially conceived to transfer data have in varying degrees been adapted to offer a way of positioning portable wireless devices. Familiar technologies such as Bluetooth (iBeacons), WiFi, Zigbee and Ultra-Wideband (UWB) represent a few. GPS is probably the most widely recognized technology; however, its lack of suitable accuracy, high power consumption, and the fact it is designed as an outdoor solution excludes it as viable option for many IoT applications.
There is a different approach, one that uses a technology for positioning based on a much lower radio frequency band (sub-GHz, license-free SRD/ISM). The primary advantage is achievable signal transmission range, both outdoors, underground, and indoors in a single deployment. Implementing a reliable and relatively accurate positioning system (±5 meters 85 percent of the time) can be achieved at a low TCO rate, the density of “anchor points” throughout the site is lower than the other short-range technologies with faster deployment and less site disturbance. It also has the following benefits:
There are two well-known principles for performing positioning of devices using radio signals. The first method is based on the received signal strength indicator (RSSI) from a transmitter, and the second method is based on estimating the range between a transmitter and a receiver known as ToF (Time-of-Flight).
The RSSI based positioning is built on the relationship between the mapping between the RSSI and range, as illustrated in the following figure.
From the figure we can see that there are two different parts in the range-to-RSSI mapping. In the first part (shorter ranges) we can see that small differences in range give large changes in RSSI. This will make the conversion to range from RSSI robust against measurement errors. In the second part of the curve, we can see that the curve is very flat, meaning that larger changes in the range will not influence the RSSI values that much. In this part of the curve, the conversion from RSSI to range is sensitive to measurement errors.
As the mapping between range-to-RSSI can be different under different radio environments, it is also difficult to apply an accurate model for all cases. RSSI based positioning is very useful at shorter ranges. For larger ranges the estimation error can be too large to be useful.
ToF based positioning can also be divided in two main cases: Time Difference of Arrival (TDoA) and round-trip time (RTT). TDoA requires that the anchor points are synchronized, e.g,. as in 3G/4G/5G cellular systems. A device can measure the time difference of the radio signal transmitted from the anchor points. These time differences can then be used in a “multilateration” algorithm to determine the position.
The RTT method does not require that anchor points are synchronized. Instead, it is required that the round-trip time can be measured accurately. This can, for instance, be achieved by transmitting a known radio signal to an anchor point. Upon detection of the signal reply, after a known time offset, the anchor point will transmit a new radio signal that the device will detect. The device can then estimate the round-trip time by subtracting the known time offset. These round-trip estimates will, after converting to range, be used in the multilateration algorithm.
Considerable thought should be given to TCO (Total Cost of Ownership) when deploying positioning technology. You must consider how flexible the solution is, how much disturbance will occur during deployment, the ongoing maintenance costs, and if both indoor and outdoor positioning will be needed. The list is extensive.
There is no silver bullet as each approach has pros and cons – however, what we can say about the most widely recognized positioning technologies is that they are all limited in range giving up to several tens of meters between the wireless device and network “anchor points” installed especially in indoor or industrial/harsh environments. Additionally, they offer positioning with varying degrees of accuracy or require exceptionally dense network deployments. Performing positioning of devices using radio signals offers a potential, alternative solution that may be the best fit depending on your use case.


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future-dyanmics

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