GNSS Optimization Boosts Wearable Device Performance

Imagine being able to pinpoint your exact location whether you're in a dense urban jungle, deep in a forest, or even in the middle of the open ocean. This remarkable capability is made possible by Global Navigation Satellite Systems (GNSS). While many people use "GPS" as a catch-all term, GNSS actually encompasses a much broader network of satellite positioning systems. This article explores the fundamentals of GNSS, its components, and the key factors affecting its performance in wearable devices.

Global Navigation Satellite Systems (GNSS) consist of constellations of satellites that transmit positioning and timing data to GNSS receivers. These receivers use the data to determine their precise location. By definition, GNSS provides global coverage, with the major systems including:

• Galileo (Europe): The EU's global satellite navigation system designed to deliver high-precision, reliable positioning services.
• GPS (United States): The first operational GNSS and still the most widely used system worldwide.
• GLONASS (Russia): Russia's global satellite navigation system offering similar services to GPS.
• BeiDou (China): China's independently developed global navigation system providing positioning, navigation, and timing services.

In addition to these global systems, regional Satellite-Based Augmentation Systems (SBAS) like Europe's EGNOS enhance accuracy by correcting signal measurement errors and providing integrity information. While GPS remains the most recognized system, GNSS is the technically accurate term encompassing all global satellite positioning systems.

Several key factors influence GNSS performance in wearable devices:

The trend toward slim, compact wearable devices presents challenges for antenna design. Optimal performance requires relatively large antenna volumes, which conflicts with the desire for small form factors. Additionally, antennas perform best when positioned away from the wrist and body, as these can interfere with signal reception.

Different chip manufacturers prioritize various aspects like power consumption, performance in specific scenarios, and target user groups, leading to variations in positioning accuracy across devices.

Environmental dynamics significantly impact data accuracy:

• Walking: Body obstruction and arm movement create challenges, with watches typically in poor signal reception positions.
• Running: Similar to walking but with watches in medium reception positions.
• Cycling: Forward-leaning posture typically obstructs signals, with devices in medium-to-good reception positions when stationary on handlebars.
• Swimming: No body obstruction but challenges from arm movement and submersion, requiring at least one second of surface exposure for signal acquisition.

Specific environments present unique challenges:

• Urban canyons: Tall buildings cause multipath effects (signal reflection) and rapidly changing satellite visibility.
• Forests: Dense foliage leads to signal attenuation.
• Open water: Limited surface exposure time and water reflection make this one of the most challenging environments for GNSS wearables.

Advanced algorithms help compensate for environmental factors like body obstruction, arm movement, and dynamic conditions. These are developed collaboratively by GNSS chip manufacturers and wearable companies.

In modern wearables, GNSS tracks speed, distance, and location—critical metrics for fitness tracking. When satellite signals are unavailable, many devices use built-in accelerometers to estimate these values from wrist movement. Some advanced models incorporate barometers to enhance elevation data, initially calibrated using GNSS information.

Users can typically select from multiple satellite system combinations:

• GPS + GLONASS: The default recommendation offering excellent global coverage and reliability.
• GPS + Galileo: The EU's navigation system alternative.
• GPS + QZSS: Primarily enhances GPS performance in the Asia-Oceania region.

A-GPS significantly improves performance by predicting satellite positions and orbits in advance, reducing initial positioning time. This data is typically updated daily via companion apps. The benefits are most noticeable in challenging conditions, where A-GPS can also improve route tracking and distance accuracy.

However, A-GPS requires approximate location knowledge. If users move more than 100 km (60 miles) from their last known position, initial positioning may take longer.

GNSS technology has become indispensable in modern life, particularly in wearable devices. Understanding its principles, performance factors, and optimization techniques enables users to maximize the benefits of this remarkable positioning technology across various environments and activities.