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Transfer alignment filter is used to estimate the relative attitude error between a slave strapdown inertial navigation system (SINS) and a master INS, the two important targets of which are rapidness and veracity. Transfer alignment filters have typically relied on velocity measurements from the master SINS as the source of alignment information, but lever arm error must be compensated accurately while velocity information is utilized. Nearly all the quaternion based error models are nonlinear, so nonlinear filtering algorithms are needed, suffering from computational complex. A novel improved rapid transfer alignment algorithm formulation is presented, applying quaternion to built the process and measurement model, and the dimension of the state and the measurement vectors are all reduced to four, the improvement employs a special manipulation of the measurement equation resulting in a linear pseudo measurement equation, thus the classical linear Kalman filter is employed to estimate the state, avoiding lever arm error compensation, resulting in the reducing of computational burden. A transfer alignment simulation system is also developed for the evaluation and analysis of the presented algorithm, and results show that the new novel method presented can achieve the transfer alignment accuracy under 1 milliradian.