The angle of arrival estimation of multiple sources plays a vital role in the field of array signal
processing as MIMO systems can be employed at both the transmitter and the receiver end
and the system capacity, reliability and throughput can be significantly increased by using array
signal processing. Almost all applications require accurate direction of arrival (DOA) estimation
to localize the sources of the signals. Another important parameter of localization systems is
the array geometry and sensor design which can be application specific and is used to
estimate the DOA.
In this work, various array geometries and arrival estimation algorithms are studied and then a
new scheme for multiple source estimation is proposed and evaluated based on the
performance of subspace and non-subspace decomposition methods. The proposed scheme
has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation
and Bartlett estimation techniques. The new scheme has a better performance advantage at
low and high signal to noise ratio values (SNRs).
The research work also studies different array geometries for both single and multiple incident
sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna
array elements. This research also considers the shape of the ground plane and its effects on
the angle of arrival estimation and in addition it shows how the mutual couplings between the
elements effect the overall estimation and how this error can be minimised by using a decoupling
matrix.
At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver
base station is designed and tested. The antenna radiation patterns in the azimuth angle are
almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral
with striplines feeding network and biased components to improve the impedance
bandwidth. The antenna provides the benefit of small size, and re-configurability and is very
well suited for the asset tracking applications.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/17143 |
| Date | January 2017 |
| Creators | Asif, Rameez |
| Contributors | Abd-Alhameed, Raed, Noras, James M., Jones, Steven M.R., See, Chan H. |
| Publisher | University of Bradford, Faculty of Engineering and Informatics |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, PhD |
| Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
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