According to the data from the World Health Organization, 285 million people are estimated to be visually impaired worldwide, and 39 million are blind. It is very difficult for visually impaired people to perceive and avoid obstacles at a distance during their travelling. To address this problem, we propose a sensor fusion system, which combines the RGBDepth sensor and millimeter wave radar sensor, to detect the surrounding obstacles. The range and velocity of multiple obstacles are acquired by the millimeter wave radar based on the principle of frequency modulated continuous wave. The positions of the obstacles are verified by the RGB-Depth sensor based on the contour extraction and MeanShift algorithm. The data fusion algorithm based on particle filters obtains accurate state estimation by fusing RGB-Depth data with millimeter wave radar data. The experiment results show that multiple obstacles with different ranges and angles are successfully detected by the proposed system. The measurement uncertainties are reduced by the data fusion system, meanwhile the effective detectable range is expanded compared to the detection with only RGB-Depth sensor. Moreover, the measurement results are stable when the illumination varies. As a wearable prototype, the sensor fusion system has the characteristics of versatility, portability and cost-effectiveness, which is very suitable for blind navigation application.