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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Noise covariances estimation for systems with bias states
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Noise covariances estimation for systems with bias states

机译：具有偏置状态的系统的噪声协方差估计

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摘要

This paper presents a new approach to noise covariances estimation for a linear, time-invariant, stochastic system with constant but unknown bias states. The system is supposed to satisfy controllable/observable conditions without bias states. Based on a restructured data representation, the covariance of a new variable that consists of measurement vectors is expressed as a linear combination of unknown parameters. Noise covariances are then estimated by employing a recursive least-squares algorithm. The proposed method requires no a priori estimates of noise covariances, provides consistent estimates, and can also be applied when the relationship between bias states and other states is unknown. The method has been applied to strapdown inertial navigation system initial alignment. Simulation results indicate a satisfactory performance of the proposed method
机译：本文提出了一种具有恒定但未知偏置状态的线性，时不变，随机系统的噪声协方差估计的新方法。该系统应该满足可控/可观察的条件，而不会出现偏置状态。基于重组的数据表示，由测量向量组成的新变量的协方差表示为未知参数的线性组合。然后，通过采用递归最小二乘算法估计噪声协方差。所提出的方法不需要噪声协方差的先验估计，提供一致的估计，并且当偏置状态与其他状态之间的关系未知时也可以应用。该方法已应用于捷联惯性导航系统的初始对准。仿真结果表明该方法具有令人满意的性能。

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