In order to solve the large pose estimation error of radiant field Visual SLAM algorithm and poor robustness in the process of fusion with inertial measurement unit, this paper proposes a radiance field visual inertial SLAM algorithm based on tightly coupled IMU. The algorithm uses an improved pre-integration module to implement a tightly coupled framework, the improved initialization strategy to deal with the robustness problem, combined with radiation field loss to optimize pose and bias. The proposed algorithm is applied to the positioning modules of NICE-SLAM and MonoGS, and is experimentally tested on the IMU-RGBD dataset OpenLORIS, and the tight-coupled module can improve the positioning accuracy by 34.3% and 14.8% respectively. Compared with MM3DGS, the proposed algorithm has higher robustness, which can effectively improve the positioning accuracy and has a good generalization ability to improve the SLAM performance of the radiance field.