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针对长航时无人机的长航时特性和组合导航系统固有的非线性特性,一种SINS/CNS组合导航系统的非线性模型被提出,该模型能够更加趋近于真实模型;模型建立之后详细分析了其可观测性,并根据可观测性分析的结果对该模型进行了降维设计,只对可观测性好的状态进行状态反馈;在滤波算法的选择中,精度更高的SCKF算法被应用,仿真结果表明,SCKF滤波算法精度更高,降维设计之后组合导航系统即能够保证导航精度又能够大大提高实时性。
Aiming at the long-haul characteristics of long-haul UAV and the inherent nonlinearity of integrated navigation system, a nonlinear model of SINS / CNS integrated navigation system is proposed, which can be closer to the real model. After the model is established The observability of the model is analyzed in detail. According to the results of observability analysis, the model is dimensionally reduced and the state feedback is only observed for the good observable state. Among the filtering algorithms, the more accurate SCKF algorithm Is applied. The simulation results show that the SCKF filtering algorithm has higher accuracy. The integrated navigation system after dimensionality reduction design can ensure the navigation accuracy and greatly enhance the real-time performance.