The problems of conventional Maximum Likelihood Estimation (MLE) algorithm are addressed for passive localization and an improved MLE passive localization algorithm is presented. Firstly, we estimate an initial target position using least square method. Moreover, in order to adapt the measurement error, the square root of the difference between the estimated position and the sensor’s position is used as the approximate covariance matrix for measurement error. Then, a weighted least square formula is employed to estimate a new position. Finally, we regard the estimation value as the necessary initial value, and employ the conventional MLE to calculate the final results. The improved algorithm have some advantages, i.e., it does not need to set an initial target position, its localization results do not diverge easily, its computational complexity is low, and it has the same level in accuracy as that of conventional MLE. Experimental results show that the proposed algorithm is effective.