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    <name>Conference Paper</name>
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          <name>Title</name>
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              <text>Computational Modelling of Complex Systems for Democratizing Higher Education: A Tutorial on SAR Simulation</text>
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          <name>Subject</name>
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              <text>Colaboratory; Jupyter; Python; Reproducible research; SAR</text>
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              <text>Engineering systems like Synthetic Aperture Radar (SAR) are complex systems and require multi-domain knowledge to understand. Teaching and learning SAR processing is intensive in terms of time and resources. It also requires software tools and computational power for preprocessing and image analysis. Extensive literature exists on computational models of SAR in MATLAB and other commercial platforms. Availability of computational models in open-source reproducible platforms like Python kernel in Jupyter notebooks running on Google Colaboratory democratizes such difficult topics and facilitates student learning. The model, discussed here, generates SAR data for a point scatterer using SAR geometry, antenna pattern, and range equation and processes the data in range and azimuth with an aim to generate SAR image. The model demonstrates the generation of synthetic aperture and the echo signal qualities as also how the pulse-to-pulse fluctuating range of a target requires resampling to align the energy with a regular grid. The model allows for changing parameters to alter for resolution, squint, geometry, radar elements such as antenna dimensions, and other factors. A successful learning outcome would be to understand where parameters need to be changed, to affect the model in a specific way. Factors affecting Range Doppler processing are demonstrated. Use of the discussed model nullifies use of commercial software and democratizes SAR topic in higher education.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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          <name>Creator</name>
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              <text>Govind P.J.; Kumar N.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 723-734.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-19-9379-4_52" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-9379-4_52&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161159942&amp;amp;doi=10.1007%2F978-981-19-9379-4_52&amp;amp;partnerID=40&amp;amp;md5=4fbc35a7d0928619019b0d0917cb2770" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161159942&amp;amp;doi=10.1007%2f978-981-19-9379-4_52&amp;amp;partnerID=40&amp;amp;md5=4fbc35a7d0928619019b0d0917cb2770&lt;/a&gt;</text>
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              <text>ISSN: 23673370; ISBN: 978-981199378-7</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Govind P.J., CHRIST (Deemed to be University), Kengeri, Bangalore, India; Kumar N., CHRIST (Deemed to be University), Kengeri, Bangalore, India</text>
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