In this paper, a streamlined MIMO Kalman equalizer architecture is proposed to extract the commonality in the data path by jointly considering the displacement structure of the transition matrix and the block-Toeplitz structure of the channel matrix. Finally, an iterative Conjugate-Gradient based algorithm is proposed to avoid the inverse of the Hermitian symmetric innovation correlation matrix in Kalman gain processor. The proposed architecture not only reduces the numerical complexity to O(F log F) per chip, but also facilitates the parallel and pipelined VLSI implementation in real-time processing.