摘要
对航天测控信号进行滤波处理将有利于提高系统的测量性能。针对连线干涉测量(connected elements interferometer,CEI)因以载波时延为测量量,使其测量精度与载波差分相位估计性能直接相关,且该性能主要受近载频噪声影响这一问题,提出了采用最小二乘法(least mean square,LMS)算法对测控信号进行滤波处理以提高载波差分相位估计精度的思路。首先给出了基于LMS算法的相位估计方案;然后分析了其可行性和存在的问题;最后将LMS算法应用于CEI测量仿真和同步卫星观测试验中。仿真和实测数据处理表明:LMS算法可提高CEI测量性能,在同样数据处理长度下,滤波处理后载波差分时延估计精度提高了大约1.42倍;或在同样数据情况下,滤波处理可以降低数据的信噪比为6dB。
Filter processing is beneficial to improve the measuring performance of TT&C system. As measuring parameter of connected elements interferometer (CEI), difference phase is directly related to the measuring accuracy of CEI and is mainly affected by noise near carrier frequency, so the idea that using least mean square (LMS) adaptive algorithm to filter TT^C signals to improve esti- mation performance of difference phase is proposed. First, the estimation scheme based on LMS algo- rithm is established and its feasibility and problems are analyzed. Then, the LMS algorithm is applied to CEI simulation and geostationary satellites (GEO) observation experiment. Simulation and actual measuring data manage show that the estimation accuracy of difference phase is improved by about 1.42 times or the data's SNR demand is reduced by about 6 dB.
出处
《装备学院学报》
2014年第6期79-83,共5页
Journal of Equipment Academy
基金
部委级资助项目
关键词
连线干涉测量
LMS算法
差分时延
蒙特卡罗仿真
观测试验
connected elements interferometer (CEI)
LMS algorithm
difference phase delay
Monte Carlo simulation
observation experiment