Research on the Down-rate Filtering Method for Observations of Precision Ranging System of Gravity Satellite
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摘要: 在卫星时频传递、矢量测量技术领域，有效观测数据的高精度滤波处理十分重要，其基本要求是在保留有效观测信息的同时能够降低噪声干扰，实现原始信息的高效、高精度传递。以中国地球重力场测量卫星高精度测距系统的工程研制为背景，为实现高频噪声抑制、保留低频重力场信息，基于对FIR滤波器结构的优化和窗函数的改进，提出了一种对10 Hz采样率的原始测距数据降速率、降噪滤波的算法。相比其他类似算法，所提方法同时具备降速滤波和差分运算两种功能，噪声抑制抑制度优于44%，且频率截止特性陡峭，第一旁瓣抑制度达到–94 dB。该算法在提高测距精度、充分保留重力场信息的同时，实现了地面数据后处理流程的简化，为微波测量系统、激光测量系统的数据处理提供了一种优选方案。Abstract: In the field of satellite time-frequency transfer and vector measurement technology, high-precision filtering of observations is very important. The basic requirement is to reduce noise interference while retaining effective observation information, and to achieve efficient and high-precision transmission of original information. In the development of high-precision ranging system for China’s earth gravity satellite, based on optimization of the FIR filter structure and improvement of the window function, a rate-down filtering algorithm for 10Hz raw ranging data is proposed in order to achieve high-frequency noise suppression and retain low-frequency gravity field information. CEDF for short, this algorithm has the operation efficiency of convolution, extraction and difference. Compared with other similar algorithms, the proposed method has the functions of both deceleration filtering and difference calculation, the noise suppression suppression degree is better than 44%, and the frequency cutoff characteristic is steep, and the suppression degree of the first side lobe reaches –94 dB. The algorithm not only improves the ranging accuracy and fully retains the information of gravity field, but also simplifies the post-processing process of ground data, and provides an optimal scheme for the data processing of microwave measurement system and laser measurement system. CEDF algorithm plays an important role in the engineering development of Earth gravity detection satellites in China and provides an effective means for the efficiency evaluation of loads.
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图 3 卷积7次的CEDF测距滤波器频域响应（a）及时域特性（b）
Figure 3. Frequency domain response (a) and time domain characteristics (b) of the CEDF ranging filter with 7 convolutions
图 4 KBR系统静态测试距离曲线（局部曲线呈现白噪声、闪烁噪声和随机游走噪声三种特征）
Figure 4. Static range curve of KBR system (local curve presents three characteristics: white noise, flicker noise and random walk noise)
图 5 滤波器降噪性能时域对比（静态数据）
Figure 5. Time-domain comparison of filter noise reduction performance (using static data)
图 6 滤波器降噪性能频域比对
Figure 6. Frequency domain comparison of filter noise reduction performance
图 7 滤波器降噪性能时域比对（动态数据）
Figure 7. Time-domain comparison of filter noise reduction performance (using dynamic data)
图 8 卷积7次的CEDF速度滤波器和加速度滤波器时域特性
Figure 8. Time-domain characteristics of CEDF velocity filter and acceleration filter with 7th convolution
图 9 CEDF滤波器提取距离、速度和加速度的观测量实例
Figure 9. Example of CEDF filter to extract range, velocity and acceleration observations
表 1 载荷数据生成参数
Table 1. Parameter configuration of payload test
卫星号 星间距离/
km载噪比/
（dB·Hz）测试时长/
h原数据速率/
HzKBR-A 220 80 7 10 KBR-B 220 80 7 10 
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表 2 参与对比的滤波器参数
Table 2. Filter parameters involved in the comparison
滤波器名称 阶数/抽取因子 截止带宽/Hz 第一旁瓣幅度衰减量/dB 噪声抑制度/(%) CIC滤波器 50（抽取因子） 0.1 –80 25.4 基于FIR半带滤波器 32阶 0.1 –85 33.0 基于FIR降速抽取滤波器 50（抽取因子） 0.1 –91 43.0 CEDF滤波器 7阶 0.1 –94 44.4 注 参考图3和4，噪声抑制度为 $\left[ {1 - { { { {({\rm{RMS} })}_{0.2\; {\rm{Hz} } } } } \mathord{\left/ {\vphantom { { { {({\rm{RMS} })}_{0.2\; {\rm{Hz} } } } } { { {({\rm{RMS} })}_{10\; {\rm{Hz} } } } } } } \right. } { { {({\rm{RMS} })}_{10\; {\rm{Hz} } } } } } } \right] \times 100\% 。$
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表 3 星间运动参数
Table 3. Inter-satellite motion parameters
运动工况 步进/mm 幅度/mm 速度/（mm·s–1） 加速度/（mm·s–2） 单向阶梯运动 0.1 0.9 0.01 0.001 双向往返运动 5 5 0.1 0.01
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