Rank-deficient robust Capon filter bank approach to complex spectral estimation

We consider nonparametric complex spectral estimation using an adaptive filtering-based approach where the finite-impulse response (FIR) filter bank is obtained via a rank-deficient robust Capon beamformer. We show that, by allowing the sample covariance matrix to be rank deficient, we can achieve much higher resolution than existing approaches, which is useful in many applications, including radar target detection and feature extraction. Numerical examples are provided to demonstrate the performance of the new approach as compared to the existing data-adaptive and data-independent FIR filtering-based spectral estimation methods.