GNSS/MEMS一体化自适应抗干扰技术研究

In recent years, precision strike based satellite navigation guidance technology has brought unprecedented effect. With the GPS modernization, Galileo system implemented, further improvement of Beidou system, the use of precision-guided weapons will be more prevalent in future, modern interference technology will continue improving, satellite navigation receiver is bound to face more complex confrontation environment. How to improve the reliability and anti-jamming capability of satellite navigation receiver effectivley is very worthy of study.. This project based on a high performance navigation terminal for application of the needs, carry out exploration adaptive antenna array satellite navigation and micro inertial device integrated anti-jamming navigation technology,in-depth analysis of adaptive beamforming, nonlinear super tight combination filtering system to solve key technical problems in the integration system, a class of nonlinear invasive weed algorithm to obtain the adaptive array antenna beam weights and The online adjustment UKF algorithm based on new measurement information is proposed, the integrated design of inertial navigation, adaptive array antenna, and satellite navigation receiver provides the technical basis for development of miniaturization receiver with high dynamic, anti-interference and multi-beam..

近年来，以卫星导航制导技术为基础的精确打击带来了前所未有的效果。随着GPS现代化改造，GALILEO系统付诸实施，北斗系统进一步完善，精确制导武器的使用将更为普遍，各种现代化的干扰技术将不断提高，卫星导航接收机必将面临更加复杂的对抗环境，因此如何有效提高卫星导航接收机的可靠性和抗干扰能力是非常值得研究的课题。. 本项目立足于高性能导航终端的应用需求，探索开展基于自适应阵列天线的卫星导航与微惯性器件一体化抗干扰导航技术研究，深入分析解决一体化系统中存在的自适应波束合成、非线性超紧组合滤波等关键技术问题，提出一种非线性入侵杂草算法获取自适应阵列天线波束权值和基于量测新息的在线调整UKF算法，实现惯导、自适应阵列天线、卫星导航接收机三者之间一体化设计，为未来高动态、抗干扰、多波束的小型化终端研制提供技术基础。

随着卫星导航应用电磁环境越来越复杂，基于阵列天线的组合导航抗干扰接收机成为未来高性能导航终端的必然发展方向。本项目立足于未来高性能导航终端的应用需求，探索开展基于GNSS/MEMS 惯导的自适应抗干扰接收机技术研究，实现惯导、自适应阵列天线、卫星导航接收机三者之间的一体化设计，为未来高动态、多波束、抗干扰的高性能终端研制提供技术基础。本项目提出了一种非线性入侵杂草算法的神经网络优化算法进行阵列天线自适应波束合成。建立了种子分发方差与植株自适应值的非线性函数关系，求取最优波束权值进行自适应波束合成，使均匀阵列天线辐射主瓣指向期望信号方向，在最大程度上将旁瓣值抑制到最低，并通过训练神经网络使算法快速收敛。提出了一种基于量测新息的自调整UKF算法，根据每一时刻的观测量确定出当前时刻最优的调节参数，以减小调节参数的选择对于模型直接的依赖性，提高了滤波的精度。. 依托项目共发表或论文6篇，授权专利5项，出版专著1部，申请专利多项。申请并获得中国博士后科学基金特别资助1项，黑龙江省自然科学基金1项，哈尔滨市科技创新人才研究专项资金项目1项。