The Analysis of Sophisticated Direction of Arrival Estimation Methods in Passive Coherent Locators
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In passive coherent locators (PCL) systems, noise and the precision of direction of arrival (DOA) estimation are key issues. This thesis addresses the implementation of sophisticated DOA estimation methods, in particular the multiple signal classification (MUSIC) algorithm, the conventional beam forming (CBF) algorithm, and the algebraic constant modulus algorithm (ACMA). The goal is to compare the ACMA to the MUSIC, and CBF algorithms for application to PCL. The results and analysis presented here support the use of constant modulus information, where available, as an important addition to DO...
In passive coherent locators (PCL) systems, noise and the precision of direction of arrival (DOA) estimation are key issues. This thesis addresses the implementation of sophisticated DOA estimation methods, in particular the multiple signal classification (MUSIC) algorithm, the conventional beam forming (CBF) algorithm, and the algebraic constant modulus algorithm (ACMA). The goal is to compare the ACMA to the MUSIC, and CBF algorithms for application to PCL. The results and analysis presented here support the use of constant modulus information, where available, as an important addition to DOA estimation. The ACMA offers many simple solutions to noise and separation related problems; at low SNR levels, it provides much more accurate estimates and yields reasonable separation performance even in the presence of challenging signals.
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