Wearable GNSS: Achieving the Lowest Power Consumption

Steve Mole

Abstract:	Existing wearable GNSS solutions require separate, stand-alone chips for GNSS, sensor control and integration software. In this paper, we show how replacing multiple, discrete chips with a single chip creates a more efficient solution, reduces power consumption and maintains the performance now expected from consumer GNSS devices. In particular, we will show how: • Power is reduced from hundreds of milliwatts in current designs to ten mW. • Chip architecture evolution explaining how, thanks to improvements in process technology predicted by Moore’s Law, different discrete chips have been merged to single chip architectures. • Trade-offs affect accuracy and power consumption. • Integration of MEMS sensors and GNSS improve accuracy and lower power consumption The wearable wireless product market is predicted to grow to exceed $6bn in 2018. As these products enter the mass market, the desire to achieve the lowest power consumption while maintaining high accuracy has become more important than ever. The first wearable technology designs resembled small cellphones: discrete GNSS, sensor and application processor (AP) chips requiring a total of hundreds of milliwatts to maintain high accuracy position. Combining chips and smart algorithms to allow offload of sensor integration software from the AP to a smaller micro-controller allows a reduction in the peak power consumption. Moore’s law is an observation that the number of transistors in a dense integrated circuit doubles approximately every two years. Thus, over the last ten years the number has risen by approximately 1000 and chip complexity which would have been unthinkable ten years ago is now possible. This now allows multiple discrete chips to be merged into single, more complex chips. With the current trend for higher performance from smartphone GNSS chips, multi-constellation hardware is increasingly common with an accompanying trend for higher power consumption. This paper shows how accuracy can be traded against power consumption to maintain performance that satisfies the user’s requirements in different user context states (eg. Walking, running, cycling). Lastly, smart integration of MEMS sensors with GNSS allows dynamic, power-efficient configuration changes that maintain the required accuracy for different user context states.
Published in:	Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015) September 14 - 18, 2015 Tampa Convention Center Tampa, Florida
Pages:	345 - 360
Cite this article:	Mole, Steve, "Wearable GNSS: Achieving the Lowest Power Consumption," Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 345-360.
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