Noise reduction approach for DOA estimation
Various Directions of Arrival (DOA) estimation techniques are presented to estimate the directions of arrival of sources. Most super-resolution algorithms require to know the number of sources present in the scenario for accurate DOA estimation. In this work, we present a new DOA estimation...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2015
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Online Access: | http://hdl.handle.net/10356/64804 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Various Directions of Arrival (DOA) estimation techniques are presented to estimate
the directions of arrival of sources. Most super-resolution algorithms require to know the
number of sources present in the scenario for accurate DOA estimation. In this work, we
present a new DOA estimation algorithm which provides distinct source direction peaks with
unknown number of sources. The working principle, as will be discussed in this work, is
similar to that of the Minimum-Norm algorithm. With unknown number of sources, the
performance of Minimum-Norm-like algorithm asymptotically approaches that of the
Minimum-Norm algorithm. With the working principle similar to that of the Minimum-Norm
algorithm, the presented algorithm is expected to have better capability to resolve closely situated
sources than the Maximum Entropy (ME) approach. With the optimization problem
solved only once, the computational cost of this Minimum-Norm-like algorithm is
significantly reduced compared to the recently proposed MUSIC-like algorithm. |
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