Accuracy is a prevailing goal in global navigation satellite systems (GNSS). And while location-tracking on our mobile phones is significantly more precise than it was 10 years ago, we still see hiccups at the circuit-level when identifying one’s location indoors or in dense city environments.
Nestware is an IoT geolocation company that provides hybrid-signal technology to IoT modem and DSP vendors. Recently, the company announced that it is combining its soft-core GPS navigation IP with Synopsys’ IoT communications IP subsystem to provide a low-power GNSS solution that can be integrated into IoT modems—cutting the cost of a dedicated GNSS chip altogether.
Nestware’s core IP integrated into an IoT modem. Image used courtesy of Nestware
This announcement gives us the opportunity to review the key tenets of GNSS technology and analyze the solution presented in the Nestware-Synopsys collaboration.
A Brief Review of GNSS Technology
GNSS is a mesh network of satellites, orbiting over terrestrial areas and providing a location fix by transmitting timing data to GNSS receivers.
Modern reception requires multiple channels (frequency band regions) to accurately estimate a location fix on a GNSS-enabled device. Discrete carrier frequencies range from 1176.45 MHz to 1575.42 MHz with legacy modulation schemes using binary (BPSK) or quadrature phase-shift key (QPSK).
According to Microsoft, GNSS receivers can consume up to 200 mW of power when performing acquisition and tracking but should consume less than 1 mW in sleep mode.
The payloads in GNSS are designed to identify the positioning of objects. Image used courtesy of Navigation Technologies
Newer modulation techniques, such as binary offset carrier (BOC), allocate energy around sub-carriers. The objective of these modulation techniques is a useful datalink, including the ability to differentiate between the triangulation satellites and provide estimated distances.
In GNSS, accuracy is defined as the difference between the measured and known metrics of time, speed, and position of the satellite network. Location accuracy is affected by a variety of factors including signal loss due to multipath and non-line-of-sight conditions in urban areas.
Nestwave has patented algorithms that mitigate multipath problems, which drives higher accuracy.
Optimized Algorithms Reduce Active Processing
According to one of Nestwave’s blog posts on signal processing, received signals are processed using symmetrical matched filters (MF) in conventional systems. MF processes multipath components as part of the received signal, but for time-of-arrival estimation, multipath elements must be eliminated.
Nestwave’s near-causal filtering approach allows a device to identify the direct positioning signal path. Once the multipath elements are filtered, the maximum-likelihood estimation time-of-arrival algorithm becomes computationally viable. Nestwave claims its solution is 4.5 times more efficient than other environments with multipath.
Improved sensitivity with Nestwave’s patented algorithms provides better accuracy than standard GNSS receivers. Image used courtesy of Nestwave
For IoT devices relying on long-term battery operation, Nestwave says geolocation tasks are completed far more rapidly, leaving the device to return to a sleep state.
Enhanced Hardware for Geolocation
As part of the collaboration, Synopsys plans to contribute its DesignWare ARC IoT communications IP subsystem to Nestwave’s geolocation algorithms and cloud architecture. The resulting GNSS solution is aimed to achieve a 10 times power reduction.
So, what’s included in this new solution?
The ARC subsystem provides the DSP-enhanced EM9D low-power processor with dedicated peripherals. APEX-integrated hardware accelerators are used to off-load Viterbi decoding and trigonometric calculations of GNSS signals from the processor.
Block diagram of Synopsys’ ARC IoT communications IP subsystem at the heart of low-power IoT modems. Image used courtesy of Synopsys
The generic digital RF front-end allows external vendor RF transceivers, which could enable interesting triangulation efficiencies with Nestwave’s hybrid approach to geolocation, using other technologies such as 4G/5G signal multilateration or Wi-Fi sniffing.
Integrating Hardware and Software to Improve IoT Power Efficiency
The collaboration between Synopsis and Nestwave exemplifies the increasing integration between software and hardware engineering teams.
John Koeter, Synopsys’ senior VP of marketing and strategy for IP, explains that this collaboration “will help designers significantly improve geolocation performance, reduce frequency requirements, and lower overall power consumption for battery-powered IoT applications.”
Market applications in farming, smart cities, or geolocation management of static corporate assets are driving the demand for IoT devices to operate on battery life cycles measured in years, not days (like our cellular devices).
By optimizing hardware power consumption and algorithm run-time efficiency, designers can facilitate longer equipment maintenance cycles and improve battery-powered IoT installation viability.