仿生偏振/MIMU/地磁组合导航抗干扰滤波方法研究

With multi-source disturbances, modeling of a bionic polarized lightintegrated navigation system and disturbance resistance filtering are proposed in this project. Firstly, based on the impact mechanism of the inner and outer disturbances of a bionic polarized light integrated navigation system, special information abstraction of multi-source disturbances, disturbance modeling and analysis are developed.In addition, bionic polarized light integrated navigation system modeling which contains multi-source information will be proposed. In case of an unmanned aerial vehicle system, based on the analysis of the platformvibration, inner light path and sensors noise,a composite layered disturbances resistancefiltering method aiming at special disturbances is proposed. Focusing on the conservation and lower convergence speed of traditional robust filtering methods, a recursive optimized robust filtering method is proposed to achieve real-time performance. Finally, a physical verification platform is built to analyze navigation precision and matching issues using components with different precisions in disturbance environments. In order to verify the effectiveness and practicability of the proposed disturbances resistance filtering method, a series of vehicle experiments are carried out. The research achievements will improve the performance and reliability of the bionic polarized light integrated navigation system and make the foundation of using in aircrafts, vehicles, ships and warships.

本项目研究多源干扰条件下仿生偏振/MIMU/地磁组合导航系统中的建模与抗干扰滤波问题。通过分析仿生偏振组合导航系统内、外部干扰等多源干扰的影响机理，开展多源干扰的特征信息提取、干扰建模及分析研究，建立含多源干扰信息的仿生偏振组合导航系统模型；以无人机为例，通过分析外部载体的扰动、振动以及内部光路、传感器噪声等多重干扰特性，提出基于特定干扰特性的复合分层抗干扰滤波方法；针对传统鲁棒滤波存在保守性大和收敛速度慢等问题，提出基于递推优化的鲁棒滤波方法以满足无人机实时性要求；最后，为解决不同干扰环境和器件精度下组合导航系统精度分析和匹配问题，搭建相应的物理验证平台，通过半物理仿真实验和车载实验验证和评估所提出抗干扰滤波算法的合理性及工程应用的实用性。研究成果将提升仿生偏振/MIMU/地磁组合导航系统的性能和可靠性，为仿生偏振组合导航系统在飞行器、地面车、舰船等载体的应用提供支撑。

本项目研究多源干扰条件下仿生偏振/MIMU/地磁组合导航系统中的建模与抗干扰滤波问题。通过分析仿生偏振组合导航系统内、外部干扰等多源干扰的影响机理，开展多源干扰的特征信息提取、干扰建模及分析研究，建立含多源干扰信息的仿生偏振组合导航系统模型；以无人机为例，通过分析外部载体的扰动、振动以及内部光路、传感器噪声等多重干扰特性，提出基于特定干扰特性的复合分层抗干扰滤波方法；针对传统鲁棒滤波存在保守性大和收敛速度慢等问题 ，提出基于递推优化的鲁棒滤波方法以满足无人机实时性要求；最后，为解决不同干扰环境和器件精度下组合导航系统精度分析和匹配问题，搭建相应的物理验证平台，通过半物理仿真实验和车载实验验证和评估所提出抗干扰滤波算法的合理性及工程应用的实用性。研究成果将提升仿生偏振/MIMU/地磁组合导航系统的性能和可靠性，为仿生偏振组合导航系统在飞行器、地面车、舰船等载体的应用提供支撑。