IEEE/CAA Journal of Automatica Sinica
Citation:  W. L. Zuo, J. M. Xin, C. N. Liu, N. N. Zheng, and A. Sano, “Improved Capon estimator for highresolution DOA estimation and its statistical analysis,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 8, pp. 1716–1729, Aug. 2023. doi: 10.1109/JAS.2023.123549 
Despite some efforts and attempts have been made to improve the directionofarrival (DOA) estimation performance of the standard Capon beamformer (SCB) in array processing, rigorous statistical performance analyses of these modified Capon estimators are still lacking. This paper studies an improved Capon estimator (ICE) for estimating the DOAs of multiple uncorrelated narrowband signals, where the higherorder inverse (sample) array covariance matrix is used in the Caponlike cost function. By establishing the relationship between this nonparametric estimator and the parametric and classic subspacebased MUSIC (multiple signal classification), it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE, the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signaltonoise ratio (SNR). Furthermore the statistical performance of the ICE is analyzed, and the largesample meansquarederror (MSE) expression of the estimated DOA is derived. Finally the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples, where the CramerRao lower bound (CRB) is used to evaluate the validity of the derived asymptotic MSE expression.
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