You may not be familiar with the phrase Global Navigation Satellite System (GNSS), but you probably take advantage of it every day as it encompasses all satellite based global location systems; GPS, GLONASS, Galileo, and BeiDou.
By Richard Edgar, Director of Communications Technology, Ensigma, Imagination Technologies
The seeming magic of GPS and other location-based services depends on a highly complex interplay of satellites, antennas, sensors, radio-frequency (RF) generators and receivers, and signal processing engines. The signal and data processing that brings GNSS functionality to a device near you is very power intensive, and even for devices that have relatively large batteries, such as a smart phone, using location services for continued tracking can rapidly drain its charge.
As location services move into a new generation of consumer mobile products and ever-smaller form factors, such as remote IoT edge devices on the network edge, a new approach to low-power GNSS receiver design is required. Due to extreme power constraints, designing a GNSS receiver for a battery-operated IoT system is a considerable challenge.
Today’s IoT devices are often untethered, surviving on either battery power or energy harvesting for weeks, months, or even years at a time without a battery re-charge or replacement. The GNSS receiver inside these devices must have sub-milliwatt power consumption, versus the 20-30mW of traditional GNSS receivers in a vehicle.
Designing a receiver to operate within the power constraints of a battery-powered device requires rethinking some of the basic assumptions of traditional receiver design architecture.
How GNSS Works
At its most basic, a typical GPS receiver system consists of a GNSS antenna, an RF front-end and a signal processing engine. The antenna receives and amplifies the GNSS signals from satellites; the RF front-end further amplifies the signal and digitises it for processing; and then the baseband processor decodes the digitised signals and performs a series of computationally intense signal processing operations to calculate the satellites’ position, velocity and time (PVT).
For an accurate PVT calculation, the receiver must collect data and correlate code from at least four different satellites. The signals that are received are often weak (they are coming from space, after all). When waking up, the receiver often needs up to 30 seconds to process the signal to distinguish it from other atmospheric noise.
During which time battery life is draining from the device. In fact, it’s generally accepted that baseband processing accounts for over half of the energy consumed in modern GNSS receivers.
To make GNSS receiver design even more complex, there are four major satellite constellations circling the earth. While each has been designed around a similar GNSS topology, they were architected in a different way and integrating support for each constellation into a receiver brings different power consumption implications.
An alternative design possibility is to track only one or two of the constellations instead of all four. While tracking all four will provide the fastest acquisition time and provide the most accurate solution, not every application requires such pinpoint accuracy. For an ultra-low power asset-tracking device, for instance, it might not be necessary.
Two other considerations for GNSS receiver designs are sampling rate and processing requirements. The sampling rate of a GNSS receiver, typically expressed in samples per second, or Hertz (Hz), refers to the rate at which the analog signal is sampled to be converted into digital form.
For processing requirements, the complexity of the baseband processor is impacted by the number of bits that are needed to represent the intermediate signals, the bit-width of the registers, and the minimum frequency needed to process a particular signal. As with other parameters, there is almost always a tradeoff between power and accuracy.
Software, hardware or hybrid?
A GNSS receiver can be built in hardware or software or a mix of both. The greatest advantage of a software-based GNSS receiver is flexibility. Software running on a general-purpose processor, typically a Digital Signal Processor (DSP), takes the place of a physical baseband processor. Because the receiver runs on software, it’s possible to update and extend the product with new features and functionality, which isn’t possible with a purely hardware-based receiver.
However, the volume of digitised signal data that must be processed for accurate GNSS calculations requires a high performance processor running at high frequencies. It also needs more memory storage. This leads to increased power consumption and more costly components.
In terms of both power consumption and computational load, hardware-based receivers offer greater efficiency, and hardware designs can be highly optimised and customised for the sole purpose of GNSS processing.
At Imagination, we believe that the ideal GNSS receiver solution uses both hardware and software to provide the best balance of flexibility and power. Imagination’s Ensigma GNSS IP is a hybrid hardware/software receiver based on a dedicated processing engine that uses highly flexible, generalised processing techniques.
Take a snapshot
Many GNSS chipsets synchronise satellite data in real-time and are continuously on, consuming a great deal of power as they track and acquire data from satellites. But not every application requires an always-on, real-time approach. For these applications, it is possible to periodically turn the radio on and off for extremely brief periods of time, saving power by sampling data while maintaining accuracy of signal processing.
This ‘snapshot’ approach quickly turns the receiver on and off, capturing the satellite data, storing it in memory, and then processing that data offline after the receiver is powered down. Snapshot technology is designed to work with only a few milliseconds of a raw GNSS signal.
In fact, the Ensigma receiver’s combination of hardware and software requires only 100 to 200 milliseconds of data capture at very low sample rates (generally 1-bit) to initiate signal processing. These data snapshots are stored in 128-bit memory until the storage is filled, after which the radio ceases to receive signals and the processing engine cycles through the data multiple times in fast succession to calculate the satellites’ PVT.
The snapshot technique eliminates the need to track satellites or decode navigation messages in real time, leading to dramatically reduced receiver power consumption, as low as ten milliwatts, and ideally five milliwatts. Since Imagination’s GNSS receiver can be aggressively duty cycled, average power consumption over time can be further reduced.
Designers seeking to create battery-operated IoT devices with smaller, lighter and lower-cost receivers should test drive Imagination’s Ensigma GNSS receiver IP. By employing snapshot technology on a receiver that leverages both hardware and software, the receiver can support the multiple broadcast frequencies needed for the different satellite constellations.
It also meets aggressive low-power consumption targets to run tracking and positioning algorithms and firmware to deliver an ideal ultra-low power GNSS receiver solution.