Nonlinear Kalman filter with self-organizing model

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Abstract

To improve the accuracy of the aircraft navigation system error correction in the output signal is used. The errors of the navigation complex are estimated by using a nonlinear Kalman filter. It is proposed to use a nonlinear model constructed by the method of self-organization as a model of the process being evaluated. The effectiveness of the self-organization algorithm in comparison with the genetic algorithm and the neural network is confirmed by the results of mathematical modeling. Keywords aircraft; inertial navigation system; error model; self-organization algorithm
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自组织模型非线性卡尔曼滤波
为了提高飞机导航系统的精度,对输出信号进行了误差校正。利用非线性卡尔曼滤波对导航复合体的误差进行估计。提出了用自组织方法构造的非线性模型作为评价过程的模型。数学建模结果验证了自组织算法与遗传算法和神经网络的有效性。关键词:飞机;惯性导航系统;误差模型;自组织算法
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