Barycenter Calibration of Spatial Spectra for Direction-of-Arrival Estimations Based on Capon/MUSIC Algorithms

Direction-of-arrival (DoA) estimation holds significant importance in both communication and sensing. Spectrum peak search in DoA estimation requires careful selection of the search step size. While a large step size can result in the loss of angular information, known as the fence effect; a very small step size can have a detrimental impact on real-time performance. Therefore, the peak search operation in DoA estimation entails a trade-off between real-time capability and estimation accuracy. In this letter, we propose a low-complexity barycenter calibration (BC) method to mitigate the loss of angular information caused by the fence effect in the discrete spatial spectrum. To evaluate the performance of our approach, we apply BC to the Capon and multiple signal classification (MUSIC) algorithms. Our simulation results demonstrate that the proposed BC-Capon/MUSIC algorithm significantly enhances estimation accuracy by up to tenfold while also saving space-time resources.