MUSIC and MVDR DOA estimation algorithms with higher resolution and accuracy
Farida Akbari, Shahriar Shirvani Moghaddam, Vahid Tabataba Vakili
Abstract
Farida Akbari, Shahriar Shirvani Moghaddam, Vahid Tabataba Vakili
Abstract
One of the most important research works on the field of adaptive array antennas is to increase the accuracy and resolution of Direction Of Arrival (DOA) estimation in a joint state. In this investigation, two well-known DOA estimation algorithms, MUltiple SIgnal Classification (MUSIC) and Minimum Variance Distortionless Response (MVDR) are modelled and simulated in new proposed array geometry. This paper provides a comparison between Uniform Linear Array (ULA) and Proposed Array (PA) geometries in resolving narrowband signal sources located closely. Proposed array adds two elements to the ULA in top and bottom of the array axis. DOA estimation performance has been compared in terms of accuracy and resolution threshold. Simulation results show that ULA cannot detect the sources located at close angles to the array endfire as well as middle angles and isn't able to resolve closely spaced sources in this area successfully. The proposed array can remove this drawback while having an identical accuracy for middle angles. Consequently, by using the proposed array, a better resolution and performance is achieved for the border angles with almost the same array size and computational complexity in both MUSIC and MVDR algorithms.
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One of the most important research works on the field of adaptive array antennas is to increase the accuracy and resolution of Direction Of Arrival (DOA) estimation in a joint state. In this investigation, two well-known DOA estimation algorithms, MUltiple SIgnal Classification (MUSIC) and Minimum Variance Distortionless Response (MVDR) are modelled and simulated in new proposed array geometry. This paper provides a comparison between Uniform Linear Array (ULA) and Proposed Array (PA) geometries in resolving narrowband signal sources located closely. Proposed array adds two elements to the ULA in top and bottom of the array axis. DOA estimation performance has been compared in terms of accuracy and resolution threshold. Simulation results show that ULA cannot detect the sources located at close angles to the array endfire as well as middle angles and isn't able to resolve closely spaced sources in this area successfully. The proposed array can remove this drawback while having an identical accuracy for middle angles. Consequently, by using the proposed array, a better resolution and performance is achieved for the border angles with almost the same array size and computational complexity in both MUSIC and MVDR algorithms.
Key concepts: Narrowband, Algorithm, Direction of arrival, Computer science, Multiple signal classification, Sensor array, Computational complexity theory, Minimum-variance unbiased estimator