This paper presents an indoor human localization system for the visually impaired. A prototype portable device has been implemented, consisting of a pedometer and a standard white cane, on which a laser range finder and a 3-axis gyroscope have been mounted. A novel pose estimation algorithm has been developed for robustly estimating the heading and position of a person navigating in a known building. The basis of our estimation scheme is a two-layered Extended Kaiman Filter (EKF) for attitude and position estimation. The first layer maintains an attitude estimate of the white cane, which is subsequently provided to the second layer where a position estimate of the user is generated. Experimental results are presented that demonstrate the reliability of the proposed method for accurate, real-time human localization.