Synopsys and Nestwave have developed a complete low-power global navigation satellite systems (GNSS) solution for integrating accurate geolocation functionality into battery-operated internet of things (IoT) modems, without the need for an additional dedicated GNSS chip. The solution is based on Nestwave’s geolocation IP incorporating Synopsys’ IoT communications IP subsystem with integrated ARC EM9D processor IP.
The ARC IoT communications IP subsystem is an integrated hardware and software solution that combines Synopsys’ DSP-enhanced ARC EM9D processor, hardware accelerators, dedicated peripherals, and RF interface to deliver efficient DSP performance for ultra-low bandwidth IoT applications. Nestwave’s GNSS solution takes advantage of the ARC EM9D processor’s efficient DSP capabilities and ability to add dedicated hardware accelerators or custom instructions using APEX technology to reduce frequency requirements, giving customers additional performance bandwidth. The ARC EM9D processor is supported by the MetaWare toolkit, which includes a rich library of DSP functions, allowing software engineers to rapidly implement algorithms from standard DSP building blocks.
Nestwave has developed an ultra-low power, advanced GNSS solution for use in IoT applications. When integrated with an IoT modem such as NB-IoT, Cat M1, LoRa or Sigfox, it offers low-cost geolocation for emerging applications such as asset tracking, smart factories, and smart cities, without the need for an external GNSS chip. Nestwave says its new approach to signal acquisition, ranging and tracking means its technology enables improved indoor sensitivity, better accuracy and shorter time-to-first-fix. It does this based on determining time-of-arrival (TOA) using unique methods of signal filtering and estimation to improve accuracy in the presence of signal impairments and multipath.
According to Nestwave, in conventional signal filtering systems, received signals are often filtered using a symmetrical matched filter (MF). The impulse response of such filters is typically a sinc function. MF solutions can optimize data symbol detection in noisy/multipath environments where information is contained (and useful) in both direct and multipath signal components. However, for TOA estimation, it’s necessary to eliminate the energy contained in multipath components – not use it. Nestwave has developed a near-causal filtering approach which enables better identification of the direct positioning signal path.
Once the signal is filtered, the TOA needs to be estimated. Nestwave said conventional techniques are either inadequate in dense multipath and NLOS (near line-of-sight) environments, or for the cases of maximum-likelihood (ML) and MUSIC algorithms, unreliable and impractical due to the intense processing requirements. Nestwave has developed several advanced, robust estimation solutions which result in near-ML optimality but with reduced complexity in dense multipath.
A key to its approach is to simplify how the multipath components are treated, as determined by actual (or expected) channel conditions, e.g. a power-delay profile. Nestwave sorts multipath components into two classes: (1) nuisance paths that require joint estimation and (2) paths that can be treated as colored noise. By reducing the number of paths (= direct path + nuisance paths) for estimation, this approach exponentially reduces the complexity of ML computation with little loss of accuracy.
All combined, better filtering and estimation techniques can be used to improve geolocation accuracy and reduce power consumption even when faced with real-world impairments such as dense multipath and NLOS conditions.
“Today’s advanced navigation systems are facing unique challenges when being implemented in power-constrained IoT devices,” said Ambroise Popper, CEO at Nestwave. “By combining Nestwave’s low power geolocation software with Synopsys’ efficient ARC IoT Communications IP Subsystem, we can deliver a geolocation solution that offers greater accuracy, lower power consumption, and lower cost compared to existing GNSS solutions.”
“Emerging IoT applications are demanding geolocation functionality with high-accuracy and ultra-low power consumption,” said John Koeter, senior vice president of marketing and strategy for IP at Synopsys. He added that the combined solution will help designers significantly improve geolocation performance, reduce frequency requirements and lower overall power consumption for battery-powered IoT applications.