Due to relatively simple implementation, Uniform Linear Array (ULA) is a popular geometry for array signal processing. Despite this advantage, it does not have a uniform performance in all directions and Angle of Arrival (AOA) estimation performance degrades considerably in the angles close to endfire. In this article, a new configuration is proposed which can solve this problem. Proposed Array (PA) configuration adds two elements to the ULA in top and bottom of the array axis. By extending signal model of the ULA to the new proposed ULAbased array, AOA estimation performance has been compared in terms of angular accuracy and resolution threshold through two well-known AOA estimation algorithms, MUSIC and MVDR. In both algorithms, Root Mean Square Error (RMSE) of the detected angles descends as the input Signal to Noise Ratio (SNR) increases. Simulation results show that the proposed array geometry introduces uniform accurate performance and higher resolution in middle angles as well as border ones. The PA also presents less RMSE than the ULA in endfire directions. Therefore, the proposed array offers better performance for the border angles with almost the same array size and simplicity in both MUSIC and MVDR algorithms with respect to the conventional ULA. In addition, AOA estimation performance of the PA geometry is compared with two well-known 2D-array geometries: L-shape and V-shape, and acceptable results are obtained with equivalent or lower complexity.
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 (P A) 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.
ULA is the most common geometry exp lo ited in array signal processing. In the beamforming operation, employing the ULA leads to obtaining narrower beamwidth with respect to other geometries in similar element numbers. Recently, Shirvani and Akbari proposed a new array by adding two elements to the ULA in top and bottom of the array axis, named as SAA. Th is new array offers a considerable imp rovement in DOA estimation performance in detection and resolution of signal sources placed at angles close to the array endfires. In this article, the performance of the proposed SAA is investigated especially in beamforming and co mpared with ULA. LMS and NLMS algorith ms that are popular adaptive beamforming methods are used for evaluation and co mparing the performance of SAA and ULA. Considering array factor, mean square erro r and bit error rate metrics, simu lation results show improved convergence speed and higher data transmission accuracy in different signal source locations, boresight angles as well as endfire ones, for SAA with respect to ULA.
Uniform linear array (ULA) geometry does not perform well for direction of arrival (DOA) estimation at directions close to the array endfires. Shirvani and Akbari solved this problem by displacing two elements from both ends of the ULA to the top and/or bottom of the array axis. Shirvani-Akbari array (SAA) presents a considerable improvement in the DOA estimation of narrowband sources arriving at endfire directions in terms of DOA estimation accuracy and angular resolution. In this paper, all new proposed SAA configurations are modelled and also examined, numerically. In this paper, two well-known DOA estimation algorithms, multiple signal classification (MUSIC) and minimum variance distortionless response (MVDR), are used to evaluate the effectiveness of proposed arrays using total root mean square error (RMSE) criterion. In addition, two new scenarios are proposed which divide angular search to two parts, directions close to array endfires as well as middle angles. For middle angles, which belong to (−70 • ≤ θ ≤ 70 • ), ULA is considered, and for endfire angles, the angles which belong to (−90 • ≤ θ ≤ −70 • ) and (70 • ≤ θ ≤ 90 • ), SAA is considered. Simulation results of new proposed scenarios for DOA estimation of narrowband signals show the better performance with lower computational load.
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