In sensor networks, data collected by sensor nodes needs to be tagged with time and location information. Localization techniques are used to determine the location information by estimating location of a sensor node. It is well known that distance measurement errors affect the accuracy of estimated location. These errors may be due to methodical or environmental factors. In this paper, we propose AML (Adapted Multi-Lateration) by improving the existing multi-lateration technique. It is shown that the AML method is more robust to measurement errors; its mean localization error is lower than the multi-lateration technique for noisy measurements. Besides, the time complexity of the AML method is less than the multi-lateration technique since it does not require to solve the normal equation for the linear least squares problem as in the multi-lateration technique. Additionally, AML is advantageous for iterative localization where localized nodes become reference nodes and employed in the localization process. Incorporating these reference nodes in the AML equations is easier than multi-lateration technique.