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该文论述将最佳滤波理论应用于相干通信中消息和信道过程的联合估计问题。首先根据消息过程和信道过程的随机特征,应用扩大状态变量的方法,建立相干通信中的联合非线性估计模型,然后应用推广卡尔曼滤波算法,寻求消息过程的最佳估值。计算机模拟结果表明,采用推广卡尔曼滤波改善了对消息过程的跟踪性能,使消息过程的估算具有更好的自适应性。
This paper discusses the application of the best filtering theory to the joint estimation of message and channel processes in coherent communication. Firstly, based on the random characteristics of message process and channel process, a method of expanding state variables is applied to establish a joint nonlinear estimation model in coherent communication. Then, a generalized Kalman filter algorithm is applied to find the best estimation of message process. Computer simulation results show that the improved Kalman filter can improve the tracking performance of the message process and make the estimation of the message process more adaptive.