Abstract:
A smart antenna system combines multiple antenna elements with a signal
processing capability to optimize its radiation pattern automatically in response to
the signal environment. Widespread interest of smart antenna has continued for
several decades due to their use in numerous applications. As a whole Smart
Antennas examine all aspects of array signal processing, delivering a detailed
treatment of antenna array processing schemes, adaptive algorithm to adjust
weighting, direction of arrival (DOA) estimation methods, and diversity combining
methods that combat fading and reduce error. The objective of this work is to
provide a comprehensive study on various techniques concerning estimation of
received signals on directions of arrival (DOA).The goal is to achieve maximum
SNR, resolution, sensitivity by comparing some techniques. In order to obtain
the best possible cancellation of unwanted interferences the gain of the low noise
amplifier (LNA) must be adjusted. For optimum processing the typical objective is
to maximize the output signal to noise ratio (SNR). For an array with a specified
response in the direction of the desired signal, this is achieved by minimizing the
mean output power of the processor subject to be specified constraint. In the
absence of errors, the beam pattern of the optimized array has the desired
response in the signal direction and reduced response in the direction of
unwanted interference.
In this research work the three types of DOA estimation method are considered.
Firstly conventional method includes spectral estimation, minimum variance
distortion less response estimator. Secondly optimal method includes linear
prediction, maximum entropy, and maximum likelihood. Finally various Eigen
structure methods are also described which includes different versions of multiple
signal classification (MUSIC) methods, minimum norm methods, estimation of
signal parameters via rotational invariance technique (ESPRIT) method and the
weighted subspace fitting method. The power and beam pattern expressions of
various techniques have been computed and the output has been analyzed to
compare the various estimation methods. It has been found that the structured
estimation techniques give the better resolution, better sensitivity than the
conventional and optimal methods.
