Abstract : In this paper, we develop the Kalman filter for the identification of bilinear forms. In this framework, the bilinear term is defined with respect to the impulse responses of a spatiotemporal model, which resembles a multiple-input/single-output system. Recently, the identification of such bilinear forms was addressed in terms of the Wiener filter and conventional adaptive algorithms, i.e., least-mean-square and recursive least-squares. In this work, apart from the derivation of the Kalman filter tailored for the identification of bilinear forms, a simplified (i.e., low complexity) version of the algorithm is also presented. Simulation results support the theoretical findings and indicate the good performance of the proposed solutions.