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Nonlinear Attitude and Bias Observer Design with a Gibbs-Inspired Cost Function Using Direct Vector Measurements

机译:非线性姿态和偏见观测器设计,使用直矢量测量与GIBBS启动的成本函数

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This paper considers the problem of rigid-body attitude and rate-gyro bias estimation. Available measurements include a biased rate-gyro measurement and two or more linearly independent vector measurements. The gradient-based observer design methodology for Lie groups is employed to derive a provably convergent attitude observer. The observer propagates the state estimate along the gradient descent direction of a proposed attitude error function. The use of the proposed attitude error function, which is inspired by previous cost functions using the Gibbs parameterization, results in an innovation term that aggressively drives the attitude error to zero, leading to fast convergence of the observer. The innovation term can be constructed directly from the vector measurements. Numerical results are included that demonstrate the desirable convergence properties of the observer compared to previous results.
机译:本文考虑了刚体态度和速率 - 陀螺偏见估计的问题。可用测量包括偏置速率-Gyro测量和两个或更多个线性独立的矢量测量。使用基于梯度的观察者设计方法,用于派对派对的趋势态度观察者。观察者沿着所提出的姿态误差函数的梯度下降方向传播状态估计。使用拟议的姿态误差函数,它是通过使用GIBBS参数化的先前成本函数的启发,导致创新术语激发态度误差为零,导致观察者的快速收敛。创新项可以直接从矢量测量中构建。包括数值结果,其证明与先前的结果相比观察者的理想收敛性。

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