Under unknown environment, Simultaneous Localization, Mapping and Object Tracking (SLAMOT) based on monocular vision needs sufficient parallax to meet the observability condition of object tracking. Focused on the uncertainty of target motion and the unknown of the system on target motion mode, a multi-mode filtering target tracking algorithm based on monocular suboptimal parallax was proposed. Firstly, the direction in which the target uncertain ellipsoid projection area changed the most was selected as the suboptimal parallax direction and was used as the robot parallax control direction. Then, multi-mode filtering algorithm was used to calculate the probability of different motion modes of the target, estimating the target state of different motion modes. Finally, the target state was estimated according to the probabilistic weighting of each motion mode. The simulation results show that the residual error of suboptimal disparity algorithm is 0.16 m when the parallax velocity is 0.3 m/s, meanwhile the residual means of heuristic algorithm, multimode filtering algorithm, traditional Extended Kalman Filter (EKF) algorithm are 0.25 m, 0.06 m and 0.16 m respectively. Besides, when the parallax speed is small, the proposed algorithm also can satisfy the observability condition of target tracking, having important engineering application value.