FPGA design for on-board measurement of intermittency from in-situ satellite data

Deak, Norbert; Cret, Octavian; Munteanu, Costel; Teodorescu, E.; Echim, Marius

doi:10.1002/essoar.10506109.1

Cited by 2 publications

(3 citation statements)

References 13 publications

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“…This study is part of a broader effort devoted to building a complex semi‐autonomous digital signal processing library, able to apply on‐board various digital signal processing techniques. The current version of the library already includes modules devoted for the spectral and statistical analysis of fluctuations (Deak et al., 2018, 2021; Opincariu et al., 2019; Turicu et al., 2022). Here we discuss a new feature, allowing to detect directional discontinuities.…”

Section: Introductionmentioning

confidence: 99%

Detecting Discontinuities From In Situ Space Measurements: Method and FPGA Implementation

Munteanu

Turicu

Cret

et al. 2022

Earth and Space Science

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A clear understanding of data variability recorded in space is vital for scientists and space mission controllers. Consequently, automatic tools designed to extract relevant key-descriptors of variability are extremely useful. Nevertheless, solutions to adapt such algorithms for on-board computers are still rare. In this paper we describe an algorithm that detects directional discontinuities of in situ measured variables, and its implementation on Field-Programmable Gate Array (FPGA) devices with an application on directional discontinuities of the interplanetary magnetic field (IMF).The abrupt changes in the orientation of the IMF, referred to as directional discontinuities (DDs), are known to trigger geomagnetic storms and substorms, with significant impact on ground-based and spaceborne technologies (e.g., Tsurutani et al., 2011, and references therein). DDs are important when estimating the solar wind propagation time from an upstream solar wind monitor to a downstream target (e.g., Haaland et al., 2010;Mailyan et al., 2008;Munteanu et al., 2013). IMF discontinuities play a key role in understanding the micro-scale structure of the solar wind and have been shown to be associated with energetic particle acceleration (e.g., Bandyopadhya et al., 2020;Tessein et al., 2013), and plasma heating (e.g., Osman et al., 2012;Qudsi et al., 2020). With an average occurrence rate of one or two per hour, IMF discontinuities are abundant structures in the solar wind (e.g., Newman et al., 2020) and represent an omnipresent source of variability for the terrestrial plasma environment.Two general classes of idealized Magnetohydrodynamic (MHD) discontinuities can be distinguished: stationary structures, that is, discontinuities that do not propagate with respect to the ambient plasma (tangential discontinuities (TDs) and contact discontinuities), and propagating discontinuities (rotational discontinuities (RDs) and shocks). The most frequent small-scale discontinuities in the interplanetary space are the abrupt changes in the direction of the magnetic field, predominantly expected for TDs and RDs (e.g., Paschmann et al., 2013).Two main classes of algorithms to detect solar wind discontinuities are proposed in the literature. The first class includes algorithms searching for changes in the magnetic field direction (

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Section: Introductionmentioning

confidence: 99%

Detecting Discontinuities From In Situ Space Measurements: Method and FPGA Implementation

Munteanu

Turicu

Cret

et al. 2022

Earth and Space Science

Self Cite

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“…In a recent series of papers (Deak et al, 2018(Deak et al, , 2021Opincariu et al, 2019;Turicu et al, 2022;Munteanu et al, 2022), we used the INA software extensively during the design, implementation and validation phases of hardware, Field-Programmable Gate Array (FPGA) implementations of various analysis methods. In Deak et al (2018), the INA software implementation of PDFs computation, was the starting point for the FPGA implementation of the same method.…”

Section: Introductionmentioning

confidence: 99%

“…Opincariu et al (2019) added spectral analysis to our FPGA toolbox, again, starting from ideas and algorithms implemented in INA. Deak et al (2021) used the INA mathematical kernel and algorithm for the Flatness parameter calculations, and generated an FPGA implementation of this method. In Turicu et al (2022), a local stationarity measure is implemented in FPGA, again, based on an INA software implementation of the same measure.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Nonlinear Analysis (INA) Software for Space Plasma Turbulence

Munteanu

Kovács

Echim

2022

Preprint

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We built an integrated nonlinear analysis software -INA-designed to study space plasma turbulence and intermittency. The MATLAB programming environment was used for the algorithmic development and implementation of methods for spectral analysis, multiscale fluctuations and multifractal analysis. The performance of INA is demonstrated using magnetic field measurements from the Cluster 3 spacecraft during an inbound pass through the Earth's magnetosheath region. We show how specific features of the power spectral density (PSD) can be mapped to localised time-frequency regions in the spectrogram representation, and identify multiple intermittent events using the wavelet-based local intermittency measure (LIM). Multiscale probability density functions (PDFs) showed clear departures from Gaussianity, signifying the presence of intermittency. Structure functions (SFs) and rank-ordered multifractal analysis (ROMA) revealed the multifractal nature of the analysed signal. INA is freely distributed as a standalone executable file to any interested user, and provides an integrated, interactive, and user-friendly environment in which one can import a dataset, customize key analysis parameters, apply multiple methods on the same signal and then export high-quality, publication-ready figures. These are only a few of the many distinguishing features of INA.

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FPGA design for on-board measurement of intermittency from in-situ satellite data

Cited by 2 publications

References 13 publications

Detecting Discontinuities From In Situ Space Measurements: Method and FPGA Implementation

Detecting Discontinuities From In Situ Space Measurements: Method and FPGA Implementation

An Integrated Nonlinear Analysis (INA) Software for Space Plasma Turbulence

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