提出了具有一般相关量测噪声的线性系统的平滑估计算法 ,该算法是在系统正向和逆向滤波估计结果的基础上 ,利用线性无偏最小方差估计获得的 .由于量测噪声的相关性 ,使得其后验均值不一定等于其先验均值 ,而它的后验均值又无法通过计算得到 ,因而提出的算法是一个次优算法 .在正、逆向滤波结果已知时 ,所提出的算法计算量小 ,易于实现 .仿真实例说明 ,该算法的估计结果要优于正、逆向滤波估计结果 ,以及量测噪声不相关的Kalman平滑估计结果 . A smoothing estimation algorithm for linear systems with general correlated measurement noise is proposed, which is based on the results of systematic forward and backward filtering estimation and obtained by using linear unbiased minimum variance estimation. Due to the correlation of measurement noise, So that its posterior mean does not necessarily equal its prior mean, and its posterior mean can not be calculated, so the proposed algorithm is a suboptimal algorithm.When the forward and backward filter results are known, the proposed algorithm Which is small and easy to implement.The simulation results show that the proposed algorithm is superior to the Kalman smoothing estimation based on the results of positive and negative filter estimation and the uncorrelated measurement noise.