This paper proposes a distributed localization algorithm based on Received Signal Strength (RSS) that consists of two phases, distance estimation phase and coordinate estimation phase. In distance estimation phase the distance of the unknown node is computed based on the RSS measurements using log normal shadowing path loss model and ITU indoor attenuation model. The distance error is minimized by one-dimensional Kalman filter and the number of iterations of the filter is limited using Cramer Rao Bound value. In the second phase, the coordinates of the unknown node is estimated by lateration technique whose accuracy is improved by min-max algorithm. The RSS value is experimentally obtained in real-time indoor environment using zigbee series 1 RF module. The proposed algorithm is simulated and analyzed in MATLAB version 7. From the simulation results it is found that the proposed localization algorithm performs more efficient in terms of computational cost and accuracy. © 2010 Springer-Verlag Berlin Heidelberg.