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High-precision initialization and acceleration of particle filter convergence to improve the accuracy and stability of terrain aided navigation
ISA Transactions ( IF 6.3 ) Pub Date : 2020-10-13 , DOI: 10.1016/j.isatra.2020.10.004
Wang Rupeng , Chen Yunsai , Li Ye , Xu Pengfei , Shen Peng

Initial positioning errors and the low adaptability of a priori digital elevation maps result in large positioning uncertainty intervals in the initial stage of terrain-aided navigation (TAN). This produces pseudo-peaks and mismatches in the initial position likelihood function and renders the convergence of the particle filter (PF) slow and unstable, while even causing divergence. Thus, the occurrence of the “kidnapped robot problem” is highly probable during the initial stage of TAN and is a scenario frequently faced by deep-sea and ultra-long-range underwater vehicles. In this study, a PF initialization method based on non-linear multi-terrain aided fusion position (NLMTP) is proposed to improve the stability and accuracy of TAN. NLMTP uses the terrain-aided position (TAP) information during the initial stage of TAN to estimate the high-precision probability distribution of the starting position via backward smoothing. Accordingly, a PF initialization method for non-Gaussian prior distribution probability is proposed to improve the convergence speed of the PF during the initial stage of underwater TAN. Finally, a performance comparison of PF initialized via the NLMTP, TAP confidence interval, and TERCOM methods was performed using the survey data obtained via onboard sensors. The experimental results show that NLMTP initialization improves the convergence speed and positioning accuracy of PF in the initial TAN phase; this improvement is clear in the low terrain-adaptability area.



中文翻译:

高精度初始化和加速粒子滤波收敛,以提高地形辅助导航的准确性和稳定性

初始定位错误和先验的低适应性在地形辅助导航(TAN)的初始阶段,数字高程图会导致较大的定位不确定性间隔。这会在初始位置似然函数中产生伪峰值和不匹配,并使粒子滤波器(PF)的收敛缓慢而不稳定,甚至会导致发散。因此,在TAN的初始阶段极有可能发生“绑架机器人问题”,这是深海和超远程水下航行器经常面临的情况。本文提出了一种基于非线性多地形辅助融合位置(NLMTP)的PF初始化方法,以提高TAN的稳定性和准确性。NLMTP在TAN的初始阶段使用地形辅助位置(TAP)信息通过后向平滑来估计起始位置的高精度概率分布。因此,提出了一种针对非高斯先验分布概率的PF初始化方法,以提高水下TAN初始阶段PF的收敛速度。最后,使用通过机载传感器获得的调查数据,对通过NLMTP,TAP置信区间和TERCOM方法初始化的PF的性能进行了比较。实验结果表明,NLMTP初始化提高了TAN初始阶段PF的收敛速度和定位精度。在低地形适应性地区,这种改进是显而易见的。提出了一种非高斯先验分布概率的PF初始化方法,以提高水下TAN初始阶段PF的收敛速度。最后,使用通过机载传感器获得的调查数据,对通过NLMTP,TAP置信区间和TERCOM方法初始化的PF的性能进行了比较。实验结果表明,NLMTP初始化提高了TAN初始阶段PF的收敛速度和定位精度。这种改进在低地形适应性地区很明显。提出了一种非高斯先验分布概率的PF初始化方法,以提高水下TAN初始阶段PF的收敛速度。最后,使用通过机载传感器获得的调查数据,对通过NLMTP,TAP置信区间和TERCOM方法初始化的PF的性能进行了比较。实验结果表明,NLMTP初始化提高了TAN初始阶段PF的收敛速度和定位精度。这种改进在低地形适应性地区很明显。实验结果表明,NLMTP初始化提高了TAN初始阶段PF的收敛速度和定位精度。这种改进在低地形适应性地区很明显。实验结果表明,NLMTP初始化提高了TAN初始阶段PF的收敛速度和定位精度。这种改进在低地形适应性地区很明显。

更新日期:2020-10-13
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