Distributed localization in sensor networks with communication and measurement noises

The localization problem for sensor networks with communication and measurement noises is studied in this paper. A robust distributed iterative algorithm called ECHO-CMN is presented based on the signed barycentric coordinate representation, which can be calculated only by relative distance measurements. In the algorithm, a dither is added to the sensor states before quantization to randomize the quantization error. To attenuate the communication noise, a gain parameter which decays to zero is used. An unbiased distance estimator is constructed, and nodes can take advantage of the estimator to update the distance estimation before each localization iteration. It can be proved that ECHO-CMN converges to the exact location of each sensor almost surely under some mild assumptions on the noise. Numerical studies illustrate the proposed localization algorithm.