Fitness wearable application in one of important category in consumer solution with GNSS (Global Navigation Satellite System). In general, fitness wearables are wrist-worn devices, and they can record the trajectory and provide the statics of speed and total distances for fitness trainers, for example, runners, cyclists, and swimmers. As the more constellations (GPS, GLONASS, Galileo, Beidou, etc..) and frequencies (L1, L2, L5, etc.) are available for civilian use, high-end wearable products with multi-GNSS are expected to provide better positioning reliability.

Not only the positioning performance, but wearables require efficient power consumption because of limited volume of battery. Power-efficient positioning technology for wearable applications is a crucial factor for GNSS chip vendors. The family of AG3335 can support multi-GNSS with single band (L1) or dual bands (L1 and L5), and the maximum number of satellites is up to 75.

We proposed several strategies to meet the requirement of power consumption in wearable application, and to sustain the acceptable trajectory performance. The strategies include constellation optimizations, adaptive L5, and DTM (Duty Tracking Mode). RF unit, DSP unit, Position unit in AG3335 series chipset are deployed adaptively to minimize overall power consumption. The constellation optimization could lower power consumption by selecting the best sets from the available constellations, for example, GPS+BEIDOU, and GPS+GAILEO, when the existed measurements are sufficient to estimate position with acceptable accuracy.

The number of used satellites can be greatly decreased to save more DSP and CPU resources significantly, and power consumption could be lower about 40.3% and 26.3% for L1 and L5, respectively. The benefit of L5 mainly focuses on the multipath mitigation due to higher chip rate, especially in deep urban area. Adaptive L5 allows that AG3335 freely turns on/off the circuits related to L5 to save 38.2% power consumption if AG3335 determined the multipath effect is endurable.

Moreover, AG3335 inherited GLP (GNSS low power) feature from MT3333, AG3335 extended concept of GLP to save more power when the motion of device is significantly slow, or the signal condition is qualified. Open water swim GNSS accuracy is another challenge in wearable applications and significantly different than regular fitness (cycling, running, etc.) accuracy. The major reason is that the swimmer’s wrist/arm goes underwater and raises above the water frequently to interrupt and affect GNSS signal reception. This paper also proposed an algorithm to migrate positioning in fitness application to swimming activity. Our algorithm is capable to estimate the position when swimmers rise arm with stable signal-to-noise ratio but keeps 1-Hz positioning output to sustain low power consumption.

Learn more on https://www.ion.org/gnss/virtual-abstract-view.cfm?paperID=11242