Adaptive Kalman Filter Enhanced With Spectrum Analysis for Wide-Bandwidth Angular Velocity Estimation Fusion

Adaptive Kalman Filter Enhanced With Spectrum Analysis for Wide-Bandwidth Angular Velocity Estimation Fusion
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通过频谱分析增强自适应卡尔曼滤波器,实现宽带角速度估计融合

DOI:
10.1109/jsen.2020.2997780
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发表时间:
2020-10
影响因子:
4.3
通讯作者:
Li Jinyi
Li Jinyi
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Ji Yue;Du Yun;Yan Guozhong;Li Xingfei;Wu Jun;Tuo Weixiao;Li Jinyi

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光电惯性稳定平台广泛应用于天文观测、监测搜索、量子通信等领域,这些领域都需要较强的振动抑制和跟踪能力。为了实现惯性稳定平台全带宽的高精度角度测量,研究了磁流体动力(MHD)和微机电(MEMS)陀螺仪信号融合的融合算法。基本的自适应卡尔曼滤波器由于测量传递矩阵偏差而存在信噪比和融合频率抖动问题,使其不适合快速动态系统。本文提出了一种通过将测量协方差与信号频率联系起来来增强频谱分析的自适应卡尔曼滤波器。该方法根据频域特性将修正测量协方差的迹分为三部分。根据频率分析,滤波器的输出在低频时主要取决于MEMS陀螺仪、中频域中两个陀螺仪的融合结果以及高频时的MHD陀螺仪。该理论在扫频实验和对比实验中得到了验证,包括与梳状滤波器和闭环滤波器进行多谐波正弦和阶跃响应测试。测试结果表明,融合信号在整个测量带宽内与实际信号一致,融合信噪比得到提高。融合算法的频率特性和噪声水平满足光电惯性稳定振动测量的要求。
The optoelectronic inertial stabilization platform is widely used in the fields of astronomical observation, monitoring and search, quantum communication and other fields, which all need strong vibration suppression and tracking capability. To realize high-precision angular measurement throughout the wide bandwidth for inertial stabilization platform, the fusion algorithm is studied to fuse the signals of magnetohydrodynamic (MHD) and microelectromechanical (MEMS) gyroscope. The basic adaptive Kalman filter experiences signal-to-noise ratio and fusion-frequency jitter problems because of the measurement transfer matrix deviation, making it unsuitable for quick dynamic systems. This paper proposes an adaptive Kalman filter enhanced with spectrum analysis by connecting the measurement covariance with the signal frequencies. This method divides the trace of the modified measurement covariance into three parts according to frequency domain characteristics. Based on the frequency analysis, the filter output mainly depended on the MEMS gyroscope at low frequencies, fusion results of the two gyroscopes in the intermediate frequency-domain, and the MHD gyroscope at high frequencies. This theory is verified in the swept frequency experiment and comparative experiments, including multi-harmonic sinusoidal and step response tests compared with combing filter and closed-loop filter. The tests results show that the fusion signal is identical with the actual signal throughout the measurement bandwidth, and the fusion signal-to-noise ratio is improved. The frequency characteristics and noise level of the fusion algorithm satisfy the requirements of optoelectronic inertial stabilization vibration measurement.
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