In view of the Non-Line-Of-Sight (NLOS) error of Ultra-WideBand (UWB) signal propagation in complex indoor environments, an adaptive UWB/DR co-localization approach based on Unscented Kalman Filter (UKF) is proposed. It combines the positioning information of UWB and Dead Reckoning (DR) by establishing an adaptive UKF filtering model. In this process, the principle of innovation and Gaussian distribution is used to detect whether the UWB positioning result contains NLOS error, and then the environmental adaptation coefficient, which is constructed by real-time estimation covariance and theoretical covariance of the innovation, dynamically correct the observed noise of UWB and make it adaptive to the real environment to reduce the impact of NLOS error on the positioning result to a greater extent. The experimental results show that the proposed approach can effectively reduce the NLOS error of UWB positioning, and because of the innovative introduction of environmental adaptation coefficient, it has higher positioning accuracy and stronger anti-NLOS error performance than UKF positioning and Particle Filtering (PF) positioning.