Efficient implementation of the 2-D Capon spectral estimator

We present a computationally efficient algorithm for computing the 2-D Capon spectral estimator. The implementation is based on the fact that the 2-D data covariance matrix will have a Toeplitz-Block-Toeplitz structure, with the result that the inverse covariance matrix can be expressed in closed form by using a special case of the Gohberg-Heinig formula that is a function of strictly the forward 2-D prediction matrix polynomials. Numerical simulations illustrate the clear computational gain in comparison to both the well-known classical implementation and the method recently published by Liu et al. (see IEEE Trans. Aerosp. Electron. Syst., vol.34, no.4, p.1314-19, October 1998).