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为了解决更复杂的系统中自适应天线的研究,文献[1]提出了一种简化了的Kalman-type processing的自适应天线,它的讨论比较简单,因为它将Kalman滤波中动力学模型信息信号的状态转移矩阵认为已知,而且又略去了模型的噪声部分;对于观测方程,它将观测噪声的方差认为已知。这在自适应技术中,是不可能的,因此文献[1]不可能达到自适应的目的。本文利用了时间序列分析与辨识的方法,对Kalman-type processing的自适应天线的合理性,从原理上作了较详细地解释,通过我校M—340S计算机的模拟,结果是正确的,即被辨识的信息信号的参数和噪声的参数与真值之间非常吻合。
In order to solve the problem of adaptive antennas in more complicated systems, [1] proposed a simplified Kalman-type processing adaptive antenna which is simpler to discuss because it combines the kinetically model information signals The state transition matrix is considered as known, and the noise part of the model is omitted; for the observation equation it considers the variance of the observed noise as known. This is not possible in adaptive techniques, so it is impossible for literature [1] to achieve the goal of self-adaptation. In this paper, the method of time series analysis and identification is used. The rationality of Kalman-type processing adaptive antenna is explained in detail in principle. The result of M-340S computer simulation in our school is correct. That is, The parameters of the identified information signal and the parameters of the noise are in good agreement with the true value.