Abstarct: The area of sea and oceans is much more than land in the earth. This is the reason for importance of object detection and tracking under water in the commercial, leisure and defense field. Under water passive tracking is the subject of the thesis. It is investigated that the Fuzzy extended Kalman has better performance, in compare with other kind of the Kalman filter. The covariance matrix of the noise measurements in the Kalman filter is adjusted by using fuzzy method. The system consists of state equations describing the position and velocity of moving target in different directions. It is assumed the velocity is constant. The vector measurement model is studied in two cases: first, time differences between reflected signal from the surface and sea floor to the sensor is measured, in the second case, the vector measurement model is only the angle of the target. Finally, the fuzzy extended Kalman filter is tested for tracking. The results are compared with extended Kalman filter, tradition and Unscented Kalman filters. The results indicate that fuzzy extended Kalman filter show better estimate and less RMSE.