In this paper we present a novel indoor localization approach based on measuring the time of flight (TOF) of ultrasound signal reflections in human bodies and walls. This is a stand off detection approach, it does not require the user to carry any wireless device. Only a static co-located speaker and microphone pair is used. The speaker sends a chirp, which is reflected to the environment. Then, the microphone receives the chirp and the reflections, measuring the reception times. Subsequently, the position of the target is estimated by the line of sight signal and the second reflections from 2 walls. Fast normalized correlation is used to estimate the timestamps of the received signals. The human being reflections are detected by subtracting the correlated signal in consecutive intervals, exploiting the fact that even a static human being moves slightly due to his breathing. Besides, we use a polynomial approximation of the reflections to increase the accuracy of this process. The choice among the remaining peaks is done by minimizing the error of the geometrical equations involved. When the target is moving continuously, an unscented Kalman filter is used to predict the most reliable peaks and estimate the position of the target. Real measurements show the capability of the proposed approach of localizing a person standing still with a median error of 0.15m and a moving human being with a median error of 0.08m and a standard deviation of 0.13 m.