In many actual applications of the adaptive filtering, input signals as well as output signals often contain observation noises. Hence, it is necessary to develop an adaptive filtering algorithm to such an errors-in-variables (EIV) model. One solution for identifying the EIV model is a total least squares (TLS) algorithm based on a singular value decomposition of an off-line processing. However, it has not been considered to identify the EIV IIR system using an adaptive TLS algorithm of which stability has been guaranteed during adaptation process. Hence we propose a normalized lattice IIR adaptive filtering algorithm for the TLS parameter estimation. We also show the effectiveness of the proposed algorithm under noisy circumstances through simulations.