Aimed at problems of extended Kalman filter (EKF) linearization exists nonlinear error and dependence on known noise distribution in realtime pose estimation, an adaptive linear Kalman filtering based on PnP for pose estimation was proposed. The PnP pose estimation solution strategy was introduced into the Kalman filter observation equation, and the Kalman filter recursive parameters were adaptively adjusted by realtime estimation of the statistical error parameters of the dynamic equation. The proposed algorithm had high accuracy, fixed the observation vector dimension of the observation equation, and improves the practicality of the algorithm. Through simulation experiments, the accuracy of pose estimation of this algorithm and EKF was compared. Through quantization error analysis, it was proved that this method can improve the precision of threedimensional motion pose estimation and verified the effectiveness of the method.