A wireless sensor network (WSN) consists of spatially distributed sensors connected via a wireless link. Sensors may be designed for pressure, temperature, sound, vibration, motion... This paper considers the problem of target tracking in a WSN. This problem is especially challenging in presence of measurements which are outliers. Two algorithms for target tracking robust to outliers are proposed. They only assume that the maximum number of outliers is known. Based on interval analysis, these algorithms perform a set-membership estimation using either SIVIA or a combinatorial technique. In both cases, sets of boxes guaranteed to contain the actual target location are provided.