To deal with the uncertain statistics of measurement noise in maneuvering target tracking, a Fuzzy Adaptive Cubature Kalman Filter（FACKF） is proposed based on fuzzy inference system.By on-line judging the degree of compatibility between actual residual and theoretical residual, the measurement noise covariance of cubature Kalman filtering is adjusted in real time by using the fuzzy inference system to make it closer to the real measurement covariance gradually.Accordingly, the adaptability of the tracking algorithm is improved.Simulations using bearing-only tracking and active radar tracking model demonstrate that, compared with regular cubature Kalman filter and unscented Kalman filter, the proposed algorithm provides better filtering accuracy and stability when the observation noise is abnormal.