Estimation of Direction of Arrival (DOA) via Beamforming
A signal Processing Perspective
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Estimating the direction of arrival is an important task in different applications including radars, sonar and communications. Due to noise and interfering sources, accurate parameter estimation is a difficult task. By using array of sensors, it is possible to mitigate the noise problems. By combining the sensors' outputs in an efficient method, array processing results in an enhancement of the signal-to-noise ratio much better than that of a single sensor's output. Multiple sensors can be used for estimating parameters of more than one signal. Using beamforming techniques, the array can steer...
Estimating the direction of arrival is an important task in different applications including radars, sonar and communications. Due to noise and interfering sources, accurate parameter estimation is a difficult task. By using array of sensors, it is possible to mitigate the noise problems. By combining the sensors' outputs in an efficient method, array processing results in an enhancement of the signal-to-noise ratio much better than that of a single sensor's output. Multiple sensors can be used for estimating parameters of more than one signal. Using beamforming techniques, the array can steer electronically rather than looking for different sources by mechanical movement. Spatial filtering is carried out using beamforming to separate different signals having same frequency but different spatial locations. This thesis deals with different beamforming techniques for DOA estimation. High resolution techniques such as Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) which are subspace based techniques are also discussed.
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