Considering the fact that the target tracking problems are always modeled by a linear system equation and a non-linear measurement equation we proposed a Reduced Square-root Cubature Kalman Filter (RSCKF) to improve the estimation accuracy and the real-time performance.The simplified algorithm utilizes state transition matrix to calculate one-step prediction value of state variable and covariance matrix in time update step which avoids the complex process of the original algorithm.According to theoretical derivation the value of time update step in the simplified SCKF is the same as that of the one-step prediction of the Kalman filter.Finally the two algorithms were used in bearing-only tracking experiment and the complexity was analyzed quantitatively.Simulation results show that the new algorithm can reduce the operation time effectively and improve the tracking accuracy.