This paper presents an adaptive fault tolerant distributed target tracking algorithm for wireless sensor networks with intermittent observation based on the multi-model method and consensus information filtering. The loss and arrival of the observation are modeled as a Markov process. The posterior probabilities of intermittent observation loss and arrival are estimated in the framework of Cubature information filtering. The information contributions of each local sensor are calculated via the combination of measurement model probability. The fault tolerance to intermittent observations is obtained based on multi-model estimation. Simulation results show the effectiveness and fault tolerance of the proposed algorithm.