Maximum likelihood estimation of navigation parameters from downlink telemetry

V. Vilnrotter, K. Andrews, J. Hamkins, A. Tkacenko
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引用次数: 5

Abstract

Deep-space navigation uses estimates of range and Doppler to update and improve spacecraft trajectory solutions.1,2 Operationally, Doppler is generally extracted directly from the ground receiver's carrier tracking loop, and range is determined primarily by the use of specially designed “ranging tones,” or more recently (e.g., on New Horizons), Pseudo-Noise (PN) sequences. Transmission of tones or PN sequences drain power and bandwidth that could be better used for transmitting additional science data from the spacecraft. Here we describe and evaluate a novel technique that extracts range and Doppler estimates directly from the decoded data, thus enabling data-transmission at the maximum rate consistent with spacecraft range, antenna gain and available signal power. In this paper, the structure of the maximum likelihood estimator for range and Doppler is derived, and its performance determined relative to Cramér-Rao bounds via simulation and analysis. Performance of conventional Doppler and delay estimators based on carrier tracking loops is also derived, and contrasted with the performance of the optimum Doppler-delay estimator over a range of symbol SNR typically encountered in deep-space applications.
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下行遥测导航参数的最大似然估计
深空导航使用距离估计和多普勒来更新和改进航天器的轨道解决方案。在操作上,多普勒通常是直接从地面接收机的载波跟踪环路中提取的,距离主要是通过使用专门设计的“测距音调”来确定的,或者最近(例如,在新视野上),伪噪声(PN)序列。音调或PN序列的传输会消耗能量和带宽,这些能量和带宽本可以更好地用于从航天器传输额外的科学数据。在这里,我们描述并评估了一种新技术,该技术直接从解码数据中提取距离和多普勒估计,从而使数据以与航天器距离、天线增益和可用信号功率一致的最大速率传输。本文推导了距离和多普勒最大似然估计器的结构,并通过仿真和分析确定了其相对于cram r- rao界的性能。推导了基于载波跟踪环路的传统多普勒和时延估计器的性能,并与深空应用中典型的符号信噪比范围内的最佳多普勒时延估计器的性能进行了对比。
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