基于简化UKF的捷联惯导系统摇摆基座对准大误差模糊推理研究

Weiwei Yang, Lingjuan Miao, Ze Guo
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引用次数: 2

摘要

基于欧拉平台误差角的概念,针对惯导系统中对准角较大导致的非线性问题,建立了精确的惯导系统误差模型。为了减少捷联惯导系统初始对准的计算量,由于其状态方程是非线性的,而测量方程是线性的,因此可以采用简化UKF (SUKF)。提出了一种基于SUKF的模糊推理系统(FIS)与系统噪声在线估计相结合的新方法,以调整系统噪声协方差,在线提高捷联惯导系统初始对准性能。在大不对准角的捷联惯导系统对准仿真条件下,与传统的UKF相比,经FIS的SUKF具有更高的对准精度、更好的稳定性和更好的实时性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of Fuzzy Inference based on Simplified UKF for large alignment errors in SINS alignment on a swaying base
In the condition of large alignment angles which brought about nonlinear problem in SINS, a precise SINS error model was established on the concept of Euler platform error angles. To reduce the computation of initial alignment in SINS, a Simplified UKF (SUKF) could be used since its state equation was nonlinear while the measurement equation was linear. A novel method combined Fuzzy Inference System (FIS) and system noise's online estimation together on the basis of SUKF was proposed to adjust the system noise covariance, and online improve the performance of the SINS initial alignment. In the SINS alignment for large misalignment angles simulation conditions, the SUKF via FIS showed higher accuracy, better stability and also better real-time performance compared with conventional UKF.
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