What is the accuracy of GPS? The global positioning system (GPS) has long been applied to use cases from smart wearables to healthcare devices and industrial applications. GPS is perhaps most widely recognised among consumers for its role in satellite-based navigation systems (AKA, ‘satnavs’), but greater demand on accurate positioning is requiring GPS technologies to adapt accordingly.
Coupled with the growth in battery-powered IoT devices, and great consideration must be put to the accuracy of GPS technologies as well as their impact on battery consumption.
Demand for accurate GPS
Growing demand for precise, real-time positioning in IoT applications from smart homes to healthcare and wearables is putting the pressure on. Wearables like fitness trackers and medical monitoring devices, particularly, depend on accurate GPS data to track user movement, monitor health parameters and send alerts in case of emergencies.
It has also paved the way for technologies like multi-GNSS (global navigation satellite system) and real-time kinematic positioning (RTK) systems. Both GPS and multi-GNSS use satellites, with one key difference: how many satellites they use for positioning information. GPS will typically use one satellite system and multi-GNSS will use multiple. This means their receivers ultimately gets information from multiple sources.
Multi-GNSS and RTK positioning
Multi-GNSS systems have emerged as a potential solution to this growing demand for more precise and reliable positioning. While GPS (operated by the United States) remains the most widely used satellite navigation system, additional constellations such as Europe’s Galileo, Russia’s GLONASS, and China’s BeiDou are increasingly being integrated into IoT devices to improve positioning accuracy.
Multi-GNSS is especially useful for improving the performance of IoT devices operating in remote areas where cellular connectivity is limited or unavailable.
RTK positioning is another technology in question that is driving accuracy. RTK uses carrier-based ranging rather than code-based ranging, allowing for centimetre-level precision.
RTK achieves this high level of accuracy by correcting GPS signals in real-time using data from a fixed reference station. The reference station compares its known position with the GPS data it receives and sends correction data to the IoT device, enabling it to determine its exact location with exceptional precision.
The trade-off between power and accuracy
GPS modules can be particularly power-intensive, when performing continuous tracking or acquiring a position fix in difficult environments. For battery-powered devices concerned with battery life, maintaining GPS accuracy can sometimes come at the cost of increased power consumption.
This kind of trade-off can pose a dilemma for device designers, in trying to solve the issue of maintaining the level of GPS accuracy required by the chosen application without depleting the device’s battery life. To address this, emerging technologies are aiming to enable energy-efficient positioning.
“Assisted- and Predicted-GPS (A-GPS and P-GPS). A-GPS and P-GPS provide GPS levels of positional accuracy but use less battery power than conventional GPS,” wrote Martin Lesund, Technical Marketing Manager – Cellular IoT at Nordic Semiconductor in a contributed article for IoT Insider. They access satellite assistance data stored in a ground-based GPS database which is relayed to the IoT device via the LTE network; the IoT device can then find the satellites in seconds instead of minutes, conserving energy.
“The P-GPS technique builds on A-GPS by providing over two weeks of assistance data to the IoT device. The result is even greater power savings for devices that will sleep for long periods of time.”
Software algorithms can also play a part, by using machine learning algorithms, for example, to predict a device’s movement patterns and activating the GPS module only when necessary. For instance, if a wearable device detects that the user is stationery, it can reduce the frequency of GPS updates to conserve power.
Geofencing is an example of an algorithm-based approach that reduces power consumption. A geofencing system defines virtual boundaries around a specific area and only activates the GPS module when a device crosses these boundaries; useful for asset tracking applications.
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