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RJMCMC粒子滤波方法在月球探测器自主天文导航中的应用
An Autonomous Celestial Navigation Method for Lunar Probe Based on RJMCMC Algorithm Paticle Filter
【摘要】 天文导航系统是典型的非线性和噪声非高斯分布的系统。针对传统的扩展卡尔曼滤波不适于非线性和噪声非高斯分布的系统,和一般粒子滤波存在的粒子退化等问题,提出了一种将RJMCMC(可逆跳转马尔可夫链蒙特卡罗)算法应用于月球探测器自主天文导航粒子滤波器中的新方法。计算机仿真结果显示了该方法在加快收敛速度、提高导航定位精度和自适应调整粒子个数方面的有效性和可行性。
【Abstract】 Autonomous celestial navigation system is a typical nonlinear,non-Gaussian dynamic system.Because the extended kalman filter method is not good at dealing with nonlinear and/or non-Gaussian problems and the conventional particle filter method exists particle degeneration problem.A new autonomous celestial navigation method for lunar probe based on RJMCMC(Reversible-Jump Markov Chain Monte Carlo)method is presented in this paper.A simulation result demonstrated the validity and feasibility of this new method in quickening up the speed of convergence,increasing the precision of position determination and adjusting the sample size automatically.
【Key words】 Lunar probe; Autonomous celestial navigation; Particle filter; RJMCMC;
- 【文献出处】 宇航学报 ,Journal of Astronautics , 编辑部邮箱 ,2005年S1期
- 【分类号】V448
- 【被引频次】13
- 【下载频次】520