A new 2-D spectrum estimate using multichannel AR approach of 2-D fast RLS algorithms

In the framework of high resolution 2-D spectrum analysis, a new multichannel approach called harmonic mean horizontal vertical (HMHV) is proposed. It is based on 2-D fast recursive least squares (2-D FRLS) algorithms and their use for the computation of causal 2-D autoregressive (AR) parameters. This HMHV spectrum presents the following three main advantages on the 2-D spectrum estimated by the harmonic mean (HM) of the 2-D AR first and second quarter plane supports (QP1 and QP2) spectrum estimates: first, it presents the same biases and variances of estimation for the horizontal and vertical frequency components and improves in many cases the variances obtained with the HM method. Secondly, the single peak area (SPA) of the HMHV estimate is quite circular although the HM one looks like a skewed square indicating the existence of a best direction for the separation of two sinusoids. Thirdly, the new estimate presents less spurious peaks. This paper sums up the calculation of the different spectrum estimates and the experiments which lead to the conclusions.