A low power RF front-end for L1/E1 GPS/Galileo and GLONASS signals in CMOS 65nm technology

Rivela, G.; Scavini, P.; Grasso, D.; Castro, M.; Calcagno, A.; Avellone, Giuseppe; Mauro, Alfio Di; Cali, G.; Scaccianoce, S.

doi:10.1109/icl-gnss.2011.5955260

Cited by 9 publications

(7 citation statements)

References 8 publications

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“…A simplified frequency domain model of H is derived from a real GNSS integrated component [3] and illustrated in Figure 4 with the purposes of assessing the ideal performance of the estimator (Algorithm-1) and to introduce a general discussion on the computation technique.…”

Section: Ideal Performancementioning

confidence: 99%

“…The block H 1 represents an image rejection polyphase filter [3], which is mostly flat in the group delay at the GLONASS frequencies and is neglected in the model. The filter models are synthesized in the digital domain with a high oversampling factor.…”

Section: A Analog Front-end Modelmentioning

confidence: 99%

“…The reception of the Galileo E1 Open Service (OS) Signal will have to be activated on "Galileo Ready" receivers. With minor re-configuration of the analog front-end, both Galileo and GPS can be conveyed on the same signal path [3]. The wider pre-correlation bandwidth required by Galileo, however, exposes the incoming signals to larger variations in the front-end group delay and magnitude.…”

Section: Introductionmentioning

confidence: 99%

“…Practical aspects related to the autonomous estimation of the analog front-end, implemented on low cost receivers, are treated in Section III. Ideal Performances are introduced in Section IV with the help of a model derived from a real GNSS front-end [3]. Section V focuses on the digital front-end and analyzes the pseudorange biases arising from interference cancellation by IIR notch filtering.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Correction of pseudorange errors in Galileo and GLONASS caused by biases in group delay

Pisoni

Mattos

2012

2012 6th ESA Workshop on Satellite Navigation Technologies (Navitec 2012) &Amp; European Workshop on GNSS Signals and Signal Pr

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Both Galileo E1 OS and GLONASS L1 signals require a wider pre-correlation bandwidth than GPS C/A. The GLONASS channels are uniformly spaced on a frequency division grid, and occupy some 8MHz in total, whereas Galileo E1 OS has sidebands that are separated by about 2MHz. Being wideband is an advantage because of sharper correlation peak (Galileo) and better interference rejection; however it also exposes distant spectral components of the signal to larger variations of the front-end transfer function. Group delay differences are mostly caused by the analog components like the SAW filter or the integrated analog front-end whereas magnitude can be affected by signal conditioning done in the digital domain, for example by the insertion of recursive filters aimed at interference cancellation. These impairments must be estimated and compensated. The benefits for the consumer multiconstellation receiver are an improved precision and an enriched set of potential applications, including timing.

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Section: Ideal Performancementioning

confidence: 99%

Section: A Analog Front-end Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Correction of pseudorange errors in Galileo and GLONASS caused by biases in group delay

Pisoni

Mattos

2012

2012 6th ESA Workshop on Satellite Navigation Technologies (Navitec 2012) &Amp; European Workshop on GNSS Signals and Signal Pr

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“…We hypothesise that algorithm complexity is a driving factor in the energy budget, especially in the early stages of the processing chain such as the Digital Signal Processing (DSP). Improvements in hardware technology should lead to a decrease in energy consumption, as seen in the last decade of research in this area [7]- [10]. While both hardware and software design will drive energy consumption, our review focuses on the software side.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Low-Power GNSS

Grenier

Lohan

Ometov

et al. 2023

IEEE Commun. Surv. Tutorials

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With the miniaturization of electronics, Global Navigation Satellite Systems (GNSS) receivers are getting more and more embedded into devices with harsh energy constraints. This process has led to new signal processing challenges due to the limited processing power on battery-operated devices and to challenging wireless environments, such as deep urban canyons, tunnels and bridges, forest canopies, increased jamming and spoofing. The latter is typically tackled via new GNSS constellations and modernization of the GNSS signals. However, the increase in signal complexity leads to higher computation requirements to recover the signals; thus, the trade-off between precision and energy should be evaluated for each application. This paper dives into low-power GNSS, focusing on the energy consumption of satellite-based positioning receivers used in battery-operated consumer devices and Internet of Things (IoT) sensors. We briefly overview the GNSS basics and the differences between legacy and modernized signals. Factors dominating the energy consumption of GNSS receivers are then reviewed, with special attention given to the complexity of the processing algorithms. Onboard and offloaded (Cloud/Edge) processing strategies are explored and compared. Finally, we highlight the current challenges of today's research in low-power GNSS.

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A BeiDou hardware receiver based on the STA8088 chipset

Pisoni

Mattos²

2013

2013 International Conference on Localization and GNSS (ICL-GNSS)

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A low power RF front-end for L1/E1 GPS/Galileo and GLONASS signals in CMOS 65nm technology

Cited by 9 publications

References 8 publications

Correction of pseudorange errors in Galileo and GLONASS caused by biases in group delay

Correction of pseudorange errors in Galileo and GLONASS caused by biases in group delay

A Survey on Low-Power GNSS

A BeiDou hardware receiver based on the STA8088 chipset

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