We studied the problem of wireless indoor mobile robot localization and tracking using noise-free data and data with additive white Gaussian noise at three receiver positions. We proposed a new scanning method to overcome the drawbacks of fingerprint, which includes time-consuming construction of a database and its need for rebuilding every time a significant change in the environment occurs.