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Experimental validation of attitude and rate-sensor bias filter using range-difference measurements

机译:使用距离差测量的姿态和速率传感器偏置滤波器的实验验证

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摘要

This paper considers the problem of constructing a filter for estimating attitude and rate-sensor bias, that has both proven stability and close-to-optimal performance with respect to noise. The filter is based on measuring the difference in time of arrival for signals sent from three or more known, fixed positions to two or more receivers on the vehicle. An inertial measurement unit is also used, both rate-sensor and accelerometer measurements, and a position estimate is needed, generated from depth and time of arrival measurements. The vectors between receivers on the vehicle are assumed to be known in the body frame, and are calculated in the inertial frame through an algebraic transformation. These vectors are used as input for a non-linear observer along with rate-sensor and accelerometer data, estimating Euler angles and rate-sensor bias. These estimates are used as a linearization point for a Linearized Kalman Filter, taking the full non-linear system into account. Two experiments are run, and the filter is compared to an Extended Kalman Filter, and a non-implementable Linearized Kalman Filter using the true state as linearization point.
机译:本文考虑了构造一个用于估计姿态和速率传感器偏差的滤波器的问题,该滤波器已被证明具有稳定性,并且在噪声方面具有接近最佳的性能。滤波器基于测量从三个或更多已知的固定位置发送到车辆上两个或更多接收器的信号的到达时间差。还使用惯性测量单元,进行速率传感器和加速度计的测量,并且需要根据到达深度和时间的测量结果生成位置估计值。假设车辆的接收器之间的向量在车身框架中是已知的,并且在惯性框架中通过代数变换进行计算。这些向量与速率传感器和加速度计数据一起用作非线性观测器的输入,以估算欧拉角和速率传感器偏差。考虑到整个非线性系统,这些估计值用作线性化卡尔曼滤波器的线性化点。进行了两个实验,并将滤波器与扩展卡尔曼滤波器和使用真实状态作为线性化点的不可实现的线性化卡尔曼滤波器进行了比较。

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