高动态环境下的多普勒测速脉冲星导航方法研究

项目名称： 高动态环境下的多普勒测速脉冲星导航方法研究

项目编号： No.61501336

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 刘劲

作者单位： 武汉科技大学

项目金额： 22万元

中文摘要： 在深空探测捕获段这一高动态环境下，自主导航极为关键。在捕获段，航天器加速度变化快，轨道动力学模型呈强非线性、快时变等高动态特点。结合该模型计算出的速度误差较大，这将影响导航系统性能。除脉冲到达时间外，新兴的多普勒测速脉冲星导航还可直接提供多普勒速度这一观测量，适用于捕获段。本项目面向捕获段，从预测模型、观测量和滤波器等方面开展多普勒测速脉冲星导航研究：①由高动态轨道动力学模型积分而成的预测模型精度低。为解决该问题，拟通过高效的积分误差补偿方法构造实时高精度的预测模型。②脉冲星信号原始数据量大，与其成正比的多普勒测速计算量极大。为实时获取观测量，设计基于压缩感知的多普勒速度和脉冲到达时间联合估计方法。③由于预测模型强非线性，状态估计误差引起的非线性预测偏差较大，通过研究预测偏差与状态估计误差的耦合关系，提出二者相关条件下的高动态导航滤波器。以上成果将在捕获段为航天器提供实时高精度的自主导航。

中文关键词： 信号估计；脉冲星；深空探测；多普勒；导航

英文摘要： In the encounter period of deep space exploration which is a high dynamic environment, the autonomous navigation is the key to a successful mission. In the encounter period, as the acceleration of spacecraft varies fast, the orbit dynamic model has high dynamic characters including nonlinear and fast time-varying. The velocity error calculated by the orbit dynamic model is very large, which affects the whole navigation system performance. Besides the pulse time-of-arrival, the newly-developed Doppler velocimetry pulsar navigation method can also provide the Doppler velocity directly, and applies to the encounter period. We research the Doppler velocimetry pulsar navigation from the aspects of the prediction model, the observation information and the filter. .① The prediction model integrated by the high dynamic orbit dynamic model has low accuracy. To solve this problem, the efficient integral error compensation method is adopted to construct the real-time and highly precise prediction model. .②The raw data amount of pulsar signals is very large. The computational load of the Doppler velocimetry, which is proportional to the raw data amount, is very large. To obtain the observation real-time, the pulse time-of-arrival and Doppler velocity joint estimation method based on compressive sensing is proposed. .③Subjected to the nonlinear prediction model, the nonlinear prediction bias caused by the state estimation error is large. The relationship between the prediction bias and the state estimation error is analyzed. The high dynamic navigation filter with the relationship between the two is proposed. .The investigated achievements will provide the spacecraft with the time-real and accurate autonomous navigation information in the encounter period.

英文关键词： signal estimation;pulsar;deep space exploration;Doppler;navigation