This article proposes an analytical inverse kinematics solution method based on parallel joint axis vector optimization to solve the inverse kinematics problem of SSRMS type 7-DOF redundant space manipulators. Firstly, based on the characteristics of the 7-DOF redundant space manipulators, parallel joint axis vectors are introduced. Using these vectors, all joint positions and joint axis vectors orientation are derived, and all joint angles are solved. Then, the joint limit avoidance, singularity avoidance and motion continuity of the manipulator are used as constraints to establish the optimization model. Finally, based on the particle swarm optimization (PSO) algorithm, a 7-DOF manipulators inverse kinematics optimization algorithm is designed to find the optimal parallel joint axis vector. A kinematic simulation experiment is conducted using a self-developed SSRMS type 7-DOF redundant manipulators as an example. The effectiveness of the algorithm is verified through kinematic simulation experiments, and the results reflects that the algorithm performs well in terms of accuracy and stability.