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**Harvard**

Rönnfalk, M. (2018) *Fast factorised back-projection for reconstruction of tomographic images from bistatic radar measurements *. Göteborg : Chalmers University of Technology

** BibTeX **

@mastersthesis{

Rönnfalk2018,

author={Rönnfalk, Martin},

title={Fast factorised back-projection for reconstruction of tomographic images from bistatic radar measurements },

abstract={The compelling evidence for climate change has increased the importance that we
understand our environment and can properly model it to get factual prognoses. The
carbon cycle is one part, of which there exists a large uncertainty in the land biomass,
primarily forests. To improve our estimation abilities the BorealScat project is
currently running, which consists of a tower based radar measuring the response
from a forest. The data is used to reconstruct a vertical cross section image of the
forest (tomographic image), thereby having another way to estimate biomass. The
issue is that the processing of acquired data by the radar takes more time than
the current measurement rate. Therefore this thesis investigates the possibility to
implement a different reconstruction algorithm to decrease computation time.
The tower’s full bistatic antenna geometry is simulated as well as a simpler monostatic
approximation. For each of these a Global Back-Projection is implemented
and used as a reference. The Fast factorised back-projection (FFBP) algorithm is
implemented in the monostatic case, and partially implemented for the bistatic case
(called BiFFBP). Simulated data and measured data were used for development and
benchmarking of the algorithms.
A speedup fo 50% - 70% is achieved in the monostatic approximation case, which
is of the same order as the theoretical maximum; four times speedup . The partial
results for the bistatic case are demonstrated, however, time constraints hindered
the completion of the implementation.
The conclusion is that the implementation of FFBP and BiFFBP show potential to
help reduce the computational burden of the BorealScat project.},

publisher={Institutionen för rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys, Chalmers tekniska högskola},

place={Göteborg},

year={2018},

keywords={radar, SAR, bistatic, back-projection, GBP, FFBP, BorealScat.},

note={64},

}

** RefWorks **

RT Generic

SR Electronic

ID 256416

A1 Rönnfalk, Martin

T1 Fast factorised back-projection for reconstruction of tomographic images from bistatic radar measurements

T2 Fast factorised back-projection for reconstruction of tomographic images from bistatic radar measurements

YR 2018

AB The compelling evidence for climate change has increased the importance that we
understand our environment and can properly model it to get factual prognoses. The
carbon cycle is one part, of which there exists a large uncertainty in the land biomass,
primarily forests. To improve our estimation abilities the BorealScat project is
currently running, which consists of a tower based radar measuring the response
from a forest. The data is used to reconstruct a vertical cross section image of the
forest (tomographic image), thereby having another way to estimate biomass. The
issue is that the processing of acquired data by the radar takes more time than
the current measurement rate. Therefore this thesis investigates the possibility to
implement a different reconstruction algorithm to decrease computation time.
The tower’s full bistatic antenna geometry is simulated as well as a simpler monostatic
approximation. For each of these a Global Back-Projection is implemented
and used as a reference. The Fast factorised back-projection (FFBP) algorithm is
implemented in the monostatic case, and partially implemented for the bistatic case
(called BiFFBP). Simulated data and measured data were used for development and
benchmarking of the algorithms.
A speedup fo 50% - 70% is achieved in the monostatic approximation case, which
is of the same order as the theoretical maximum; four times speedup . The partial
results for the bistatic case are demonstrated, however, time constraints hindered
the completion of the implementation.
The conclusion is that the implementation of FFBP and BiFFBP show potential to
help reduce the computational burden of the BorealScat project.

PB Institutionen för rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys, Chalmers tekniska högskola,

LA eng

LK http://publications.lib.chalmers.se/records/fulltext/256416/256416.pdf

OL 30