Author Archives: Ludovico Biagi

Multi-fidelity, adaptive technique in design-exploration space, ANOVA-analysis

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Docente

Ludovico Biagi (mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

Prediction, samplets

Tecnologie da utilizzare

python, C++, binding, I/O on dataset

Descrizione (max 500 caratteri)

Goal This project aims to develop additional features, e.g. multi-fidelity, adaptive technique in design-exploration space, ANOVA-analysis. The results will be tested on industrial testcase of WindAssistant Trasoceanic Cargo, Energy System and on geoinformatics data (e.g. GNSS dataset).
Project Plan :
• Read and understand a reference paper on samplets, kernel-based methods, multifidelity (provided)
• Getting familiar with Bayesian Optimization, Anova, MultiFidelity algorithms
• Design, train and implement the studied algorithms
• Performance assessment on an industrial dataset as well as on geoinformatics dataset
• Cowriting a report for scientific dissemination in ECCOMAS conference and for peer-review paper

Beidou satellites orbit

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Docente

Ludovico Biagi (mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

GNSS, Beidou, orbits

Tecnologie da utilizzare

Python

Descrizione (max 500 caratteri)

The student will implement libraries to compute and plot orbits of Beidou satellites from RINEX broadcast ephemerides

Efficient Outliers rejection in positioning of mobile devices

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Docente

Ludovico Biagi (mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

GNSS, Efficient Leave One Out

Tecnologie da utilizzare

Python

Descrizione (max 500 caratteri)

GNSS provide positions estimates that are quite accurate in a good observation environment. However, in harsh conditions, blundered observations can seriously affect the accuracy of the estimated positions.
The Leave One Out method is really accurate in identifying blunders but is not efficient from a numerical point of view: this is clearly a serious problem for real time applications.
An efficient LOO method has been studied. The student will implement it and apply it to simulated GNSS data to test accuracy and efficiency.

Positioning of mobile devices

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Docente

Biagi Ludovico (mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

INS, GNSS, Kalman

Tecnologie da utilizzare

Language: python
Development environment: Anaconda

Descrizione (max 500 caratteri)

Modern smartphones acquire data from Inertial Navigation Systems and GNSS satellites: these data are hybridized and used to estimate positions and, typically, plots on webmaps. Several Android applications are also habilitated to output the raw data in specific formats. The student will implement SW to download data from smartphones, to graphically analyze them and to filter them by Kalman filtering. The SW will be tested on real data. Existing libraries for postprocessing the data will be analyzed and assessed.

GNSS point positioning

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Docente

Ludovico Biagi (mail)

Area di ricerca

Architetture

Keyword (max 3 separate da virgola)

GNSS, positioning

Descrizione (max 500 caratteri)

Implementation of python Libraries to perform standard kinematic point positioning by reading GNSS RINEX files of observations and ephemerides

GNSS point positioning

Posted on by

Docente

Ludovico Biagi (mail)

Area di ricerca

Architetture

Keyword (max 3 separate da virgola)

GNSS, positioning

Descrizione (max 500 caratteri)

Implementation of python Libraries to perform standard kinematic point positioning by reading GNSS RINEX files of observations and ephemerides