卡尔曼增益通过变遗忘因子进行改进，避免误差的累积。

Using improved Kalman filter to forecast and track. Kalman gain is improved through variable forgetting factor which will avoid the accumulation of errors.

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本文依据卡尔曼滤波器在使用最佳增益时，其余差序列互不相关的性质，开发了一种新的渐消滤波算法。

A new fading filtering algorithm is developed based on the property of Kalman filter that the sequence of residuals is uncorrelated when the optimal gain is used.

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介绍一种改进的固定增益卡尔曼滤波方法。

This thesis concentrates on the method of improved fixed-gain Kalman filter.

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