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Tuning the Attitude Filter: A Comparison of Intuitive and Adaptive Approaches

机译：调整姿态过滤器：直观和自适应方法的比较

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摘要

All attitude filter designers are familiar with the covariance matrix tuning process for an attitude filter to get an estimate close to the optimal (or sub-optimal)values as much as possible. This is a difficult and time-consuming task. Selected values for the measurement and process noise covariance matrices are decision makers for the filter's performance. Composing the measurement covariance matrix (R) is rather straightforward as we make use of the sensor specifications. Yet when there are issues such as measurement delay, the matrix components must be tuned for higher estimation accuracy and usually with an ad hoc approach. As to the process noise covariance matrix (Q), we have an analytical approximation, but most of the time it does not give the best result in practice. This paper first surveys researches on tuning the attitude filter and discuss the details of the problem. Then investigates the applicability of common adaptive methods for attitude filtering and provides a performance comparison in between intuitively and adaptively tuned attitude filters.
机译：所有的姿态滤波器设计人员都熟悉姿态滤波器的协方差矩阵调整过程，以使估算值尽可能接近最佳（或次优）值。这是一项困难且耗时的任务。测量值和过程噪声协方差矩阵的选定值是滤波器性能的决策者。当我们利用传感器规格时，组成测量协方差矩阵（R）非常简单。然而，当出现诸如测量延迟之类的问题时，必须对矩阵分量进行调整以获得更高的估计精度，并且通常采用临时方法。关于过程噪声协方差矩阵（Q），我们有一个解析近似值，但是在大多数情况下，它在实践中并未给出最佳结果。本文首先对姿态滤波器的调优研究进行了调查，并讨论了问题的细节。然后研究了常用的自适应方法对姿态过滤的适用性，并提供了直观和自适应调整的姿态过滤器之间的性能比较。

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