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Chapter 47 Research on Ultra-Tight Integration Technology for GNSS/SINS Integrated Navigation Systems

机译:第47章GNSS / SINS组合导航系统超紧密集成技术研究

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GNSS/SINS deep integration relative to the tight integration can further improve navigation accuracy and noise immunity of high dynamic environment, and it is the future direction of development. A deep integrated navigation technology based on vector delay lock loop is researched. First, in the baseband signal preprocessing unit, Unscented Kalman Filter (UKF) is adopted to pre-filter the satellite signal, reduce the signal update rate, and the nonlinearity between I/Q signals and navigation state variables. By utilized base band signal pre-filter technology, the measurement equations of deeply integrated filter are simplified, and the calculation amount is also reduced significantly. For the heterogeneous sensor data fusion problem, in the deeply integrated filter design, an improved Unscented Particle Filter (UPF) algorithm based on the sequential importance sampling is proposed. The simulation studies show that the techniques researched here are effective. Comparing the tight integration technology, the position, velocity and attitude accuracy of navigation system are improved.
机译:相对于紧密集成,GNSS / SINS的深度集成可以进一步提高高动态环境下的导航精度和抗噪能力,这是未来的发展方向。研究了基于矢量延迟锁定环的深度集成导航技术。首先,在基带信号预处理单元中,采用无味卡尔曼滤波器(UKF)对卫星信号进行预滤波,降低信号更新率,以及I / Q信号与导航状态变量之间的非线性。利用基带信号预滤波器技术,简化了深度集成滤波器的测量方程,大大减少了计算量。针对异构传感器数据融合问题,在深度集成滤波器设计中,提出了一种基于顺序重要性抽样的改进的无味粒子滤波(UPF)算法。仿真研究表明,本文研究的技术是有效的。比较紧密集成技术,可以提高导航系统的位置,速度和姿态精度。

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