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In order to solve the problems of target motion analysis convergence time too long and low accuracy for AUV bearings-only target tracking by model simplification、unknown noise statistical properties and target initial distance information inaccurate, an improved Strong Tracking Square Root Cubature Kalman Filter bearings only target motion analysis method is propoesd. With the STFSRCKF algorithm, the equation of state is predicted and updated with SRCKF, each cubature point of SRCKF is updated by strong tracking filter (STF), the effects of noises on system state estimation are suppressed by optimizing filter gains, and the system state estimation converges to real values quickly. At last, several algorithms of bearing target tracking algorithm under different initial condition and noise environmentare were compared in numerical simulation experiments. The experimental results show that the proposed strong tracking SRCKF filter has better performance on robustness and convergence.