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UNIVERSAL ALGORITHM OF ADAPTIVE OPTIMAL-INVARIANT SIGNAL FILTERING

机译:自适应最优不变信号滤波的通用算法

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The algorithm of optimal-invariant adaptive signal filtering for models of interferences of measurement in the form of Markovian processes of kth order by an example of an complex system with the filter of a difference signal is offered. Demanded level of a priori determinancy concerning noise of measurement includes knowledge of approximate duration of intervals of a quasistationarity noise of measurement, sort of linear model of measurement, a variance of high-frequency noise and presence of a mutual noncorrelated of a signal and noise. The algorithm in the course of operation, besides optimal filtering of signals, evaluates quality of handling of signals and defines adapting time. In the presence of the information on correlative functions noise of measurement the algorithm ensures optimally-invariant filtering of Kalman 's signals without necessity of solution of the equation of Rikkati.
机译:以带有差分信号滤波器的复杂系统为例,提出了以k阶马尔可夫过程形式的测量干扰模型的最优不变自适应信号滤波算法。关于测量噪声的先验确定性的要求水平包括以下知识:近似平稳的测量噪声的间隔的持续时间的知识,测量的线性模型的种类,高频噪声的方差以及信号和噪声的相互不相关的存在。该操作过程中的算法除了对信号进行最佳滤波之外,还评估了信号处理的质量并定义了适应时间。在存在相关函数测量噪声的信息的情况下,该算法可确保卡尔曼信号的最佳不变滤波,而无需解算Rikkati方程。

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