| 一种用于深空高动态微弱信号的频率估计算法 |
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| 引用本文： | 宋青平,刘荣科.一种用于深空高动态微弱信号的频率估计算法[J].宇航学报,2013,34(11):1496-1501. |
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| 作者姓名： | 宋青平 刘荣科 |
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| 作者单位： | 北京航空航天大学电子信息工程学院，北京 100191 |
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| 基金项目： | 新世纪优秀人才支持计划资助NCET-12-0030；国家863计划(2012AA7014065) |
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| 摘 要： | 研究了低载噪比与高动态环境下的深空测控系统频率估计算法，在分析已有方法不足的基础上，提出了一种基于无迹卡尔曼滤波(UKF)的闭环载波跟踪方法。此方法结合了锁频环鉴别器和UKF的优点，获得了宽的估计范围，高的估计精度和低的载噪比门限。在分析UKF模型的基础上，此方法还减少了原有UKF算法的运算量。仿真过程模拟了接收机的高动态运动轨迹，结果表明此法具有较好的动态适应能力、收敛性能和跟踪精度，能够有效地完成低载噪比与高动态环境下的频率估计。此法与基于扩展卡尔曼滤波(EKF)的频率估计算法相比，具有更低的频率估计误差，因此有着良好的应用前景。
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| 关 键 词： | 深空测控 频率估计 低载噪比 高动态 无迹卡尔曼滤波 |
| 收稿时间： | 2013-01-19 |
A Frequency Estimation Algorithm for High Dynamic and Weak Signalin Deep Space |
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| SONG Qing ping,LIU Rong ke.A Frequency Estimation Algorithm for High Dynamic and Weak Signalin Deep Space[J].Journal of Astronautics,2013,34(11):1496-1501. |
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| Authors: | SONG Qing ping LIU Rong ke |
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| Affiliation: | School of Electronic and Information Engineering, Beihang University, Beijing 100191, China |
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| Abstract: | A frequency estimation algorithm for the deep space telemetry, tracking and control (TT&C) system under low Carrier\|Noise Ratio (CNR) and high dynamic conditions is presented in this paper. Considering the drawbacks of the exist algorithms, an advanced closed loop carrier tracking algorithm based on the unscented Kalman filter (UKF) is proposed. This new algorithm combines the advantages of the discriminator of the frequency lock loop and UKF to obtain a wide estimation range, high estimation accuracy and low CNR threshold. In addition, it is found on the basis of the analysis of the two kinds of models that this new algorithm cost much less computational effort than the conventional UKF. The high dynamic trace of receiver is simulated in this paper. The results show that the proposed loop structure can apparently improve dynamic capability, convergence performance and tracking accuracy, thus effectively completing the task of frequency estimation under low CNR and high dynamic conditions. Compared with the frequency estimation algorithm based on extended Kalman filter (EKF), this new algorithm has a much smaller frequency estimation error so that it will have prospective application potential. |
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| Keywords: | Deep space TT& C Frequency estimation Low CNR High dynamic Unscented Kalman filter |
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