Aiming at improving the low accuracy of the binocular vision sensor along the optical axis in target tracking, the correcting method by one-dimensional laser range sensor is proposed. Meanwhile, in order to take full advantage of the binocular vision sensor and the laser range sensor in target tracking, the information fusion is used to improve the measurement accuracy and data utilization. In the process of measurement, the frequency of the laser range sensor is affected by the mechanical property of two-dimensional turntable, which causes the data of laser range sensor time-delay. Utilizing the direct updated algorithm to estimate the one-step prediction data and make it into real-time data in follow-up algorithm. Then using federated Kalman filter to solve the dependence of the multi-sensor data. Simulation results show that the real-time performance of the time-delay information is enhanced by the direct updated algorithm. Meanwhile, experimental results show that the final information fusion algorithm improves the accuracy of target tracking and improves the sensor shortages of the accuracy and timing.