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相干通信中,由于目标的动态特性,使消息模型具有随机策动的性质。当此消息模型构成的角调信号通过随机时变信道后,形成复杂的非线性估计模型。本文采用对消息和信道过程进行联合估计的方法,以建立最佳非线性相位估计器。 文中首先应用扩大状态变量方法建立消息模型,然后讨论条件福克—普朗克方程,并由此导出估计方程和方差方程,构造条件均值滤波算法。应用这一算法以及推广卡尔曼滤波算法,导出了由白噪声策动的角调信号通过随机时变信道后的最佳非线性相位估计器。 最后,应用计算机给出的结果,得出了对消息和信道过程进行联合估计所获得的非线性相位估计器为最优的结论。
In the coherent communication, the message model has the nature of random action due to the dynamic characteristics of the target. When the angular signal formed by this message model passes through a random time-varying channel, a complex non-linear estimation model is formed. In this paper, the method of joint estimation of message and channel process is used to establish the best nonlinear phase estimator. In this paper, we first establish the message model by expanding the state variables, then discuss the conditional Fokker-Planck equation, and derive the estimation equation and variance equation to construct the conditional mean filter algorithm. Using this algorithm and the extended Kalman filter algorithm, the best nonlinear phase estimator after the white noise-driven angular signals pass through a random time-varying channel is derived. Finally, the conclusion given by the computer gives the conclusion that the nonlinear phase estimator obtained by joint estimation of message and channel process is the best.