R/I-Capon for Low-Complexity Direction of Arrival Estimation with Real-Valued Computation

Abstract

The problem of low-complexity direction-of-arrival (DOA) estimation without knowing sources number is addressed. Real/imaginary-part of array covariance matrix (ACM) can be remodeled as a whole ACM of signal received by virtual array aimed at fast DOA estimate. Based on such a virtual signal model, a novel real/imaginary-part Capon (R/I-Capon) involving the inverse of only the real/imaginary-part of the estimated ACM (EACM) is derived. In-depth insights are provided to prove that the rank of real/imaginary-part of EACM is always equal or greater than that of whole EACM, which indicates that R/I-Capon exceeds conventional Capon under the circumstance with small numbers of snapshots. Further discussion indicates that R/I-Capon is also capable of decreasing about \(75\%\) complexity with any array structures, which shows an enforcement advantage over state-of-the-art prototype methods. Simulations are finally conducted to verify theoretical analysis and to show practicability of proposed algorithm.