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首页> 外文期刊>Journal of guidance, control, and dynamics >Pipelined Particle Filter with Nonobservability Measure for Attitude and Velocity Estimation
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Pipelined Particle Filter with Nonobservability Measure for Attitude and Velocity Estimation

机译：具有不可观测性测度的管道式粒子过滤器，用于估计姿态和速度

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摘要

In this paper, a particle filter is proposed to estimate attitude and velocity onboard a small unmanned aerial system using GPS, gyro, and accelerometer measurements. For the proposed filter setup, attitude observability heavily depends on the vehicle trajectory. Therefore, a measure of nonobservability is introduced to track the uncertainty in the attitude estimate. For the nonlinear estimation problem at hand, the use of a particle filter instead of a classical extended Kalman filter has shown to be advantageous in terms of robustness. However, particle filters are computationally very demanding, and thus, are usually not applicable for navigation onboard small unmanned aerial systems. To overcome this problem, an onboard computer system has been developed, which comprises a field programmable gate array as coprocessor. To get a quantitative measure on the performance of the proposed algorithm, the field-programmable-gate-array-based onboard computer system running a pipelined particle filter for attitude and velocity estimation has been flight tested on a civil-aviation aircraft equipped with a high-precision attitude and heading reference system. Further tests have been carried out with a fixed-wing small unmanned aerial system, in which the pipelined particle filter has been used as attitude reference in a simple waypoint-navigation.
机译：在本文中，提出了一种粒子滤波器，用于使用GPS，陀螺仪和加速度计测量来估计小型无人机系统上的姿态和速度。对于建议的滤波器设置，姿态的可观察性在很大程度上取决于车辆的轨迹。因此，引入了不可观测性的度量以跟踪态度估计中的不确定性。对于当前的非线性估计问题，就鲁棒性而言，使用粒子滤波器代替经典的扩展​​卡尔曼滤波器已显示出优势。但是，粒子滤波器对计算的要求很高，因此通常不适用于小型无人航空系统的导航。为了克服这个问题，已经开发了一种车载计算机系统，其包括现场可编程门阵列作为协处理器。为了对所提出算法的性能进行定量评估，已经在配备了高空作业能力的民航飞机上对运行基于管道可编程粒子滤波器进行姿态和速度估计的基于现场可编程门阵列的机载计算机系统进行了飞行测试。精确的姿态和航向参考系统。已经对固定翼小型无人机系统进行了进一步的测试，在该系统中，流水线式粒子过滤器已在简单的航点导航中用作姿态参考。

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