CAJ | 학술논문

近年用于水下滑翔器的低成本导航系统成为研究热点，导航器件的成本与精度之间的折中问题仍然是目前的难题。针对因使用低成本的导航元件而造成低精度位姿估计的问题，提出用于位姿估计的改进高斯混合粒子滤波(IGMPF)方法。用高斯混合模型来估计非高斯噪声，改进的粒子滤波进一步提高位姿估计精度。为了验证其效果，该方法应用于自主设计的水下滑翔器导航系统中并做了车载实验，实验结果表明所提IGMPF方法在实际应用中比传统的EKF和UKF表现更优，姿态角和位移误差比EKF和UKF减小了至少30%。
근년용우수하활상기적저성본도항계통성위연구열점，도항기건적성본여정도지간적절중문제잉연시목전적난제。침대인사용저성본적도항원건이조성저정도위자고계적문제，제출용우위자고계적개진고사혼합입자려파(IGMPF)방법。용고사혼합모형래고계비고사조성，개진적입자려파진일보제고위자고계정도。위료험증기효과，해방법응용우자주설계적수하활상기도항계통중병주료차재실험，실험결과표명소제IGMPF방법재실제응용중비전통적EKF화UKF표현경우，자태각화위이오차비EKF화UKF감소료지소30%。
For the last few years, low cost navigation system applied to the underwater glider becomes a research hotspot, and the trade-off between accuracy and cost for navigation sensors is still a difficult problem currently. Aiming to the low accuracy of position and attitude estimation due to using low-cost navigation components, this paper proposes a novel improved Gaussian mixture particle filter (IGMPF) method for position and attitude estimation. By using the Gaussian mixture model to estimate the non-Gaussian noise, the improved particle filter further improves the position and attitude estimation accuracy. For verification, this method is implemented in the new underwater glider navigation system designed in our lab. A vehicle experiment is made to assess the performance of the proposed method. The results show that the proposed IGMPF method is better than the conventional EKF and UKF in the practical application with the attitude error and the position error reduced by≥30%compared with EKF and UKF.