基于自适应卡尔曼滤波的捷联去耦算法

The Decoupling Algorithm Based on Adaptive Kalman Filter

  • 摘要: 针对捷联相控阵雷达导引头中弹体姿态干扰弹目视线角速率提取的问题,提出了基于自适应卡尔曼滤波去耦算法,引入合适的遗忘因子优化了滤波的性能,建立了噪声特性递推和预测的数学模型,联立滤波方程和噪声估计方程解决了弹目视线角速率去耦的问题,在误差的允许的范围内提取了弹目视线角速率。最后通过仿真实验表明所提算法在捷联去耦上的有效性以及相对于标准卡尔曼滤波去耦的优良性,提高了提取弹目视线角速率的精度,优化了导弹制导性能,具有较高的工程运用价值。

     

    Abstract: Aiming at the problem of the extraction of line of sight interfered by missile attitude of phased array radar seeker. A decoupling algorithm based on adaptive Kalman filter is proposed, which introduces a suitable forgetting factor to optimize the performance of the filter. The mathematical model of recursiving and predicting noise characteristics is established and filtering equations and noise estimation equations are combined to solve the problem of decoupling of line of sight angular rate, so the angular rate of the line of sight is extracted within the allowing scope of the error. Finally, simulation results show that the proposed algorithm is effective in the problem of strapdown decoupling and is more accurate than the standard Kalman filter algorithm, which improved the accuracy of line of sight rate extraction, optimize missile guidance performance, and have high engineering application value.

     

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