基于粒子滤波的AUV组合导航方法

Particle Filter-Based AUV Integrated Navigation Methods

  • 摘要: 讨论了粒子滤波器和RB(Rao-Blackwellised)粒子滤波器两种滤波方法在组合导航中的应用,给出了组合导航算法用于自治水下航行器(AUV)的具体数学模型,并且与拓展卡尔曼滤波器的导航结果进行比较.利用AUV湖上试验验证了3种算法的导航性能,试验结果表明RBPF组合导航算法能够获得最好的导航精度;然而通过对算法进行分析,发现其计算复杂度高于其余两种滤波算法.

     

    Abstract: Applications of the particle filter(PF) and Rao-Blackwellised particle filter(RBPF) to AUV(autonomous underwater vehicle) integrated navigation are discussed.The specific mathematical model for implementation of the integrated navigation method on AUV is presented.And those methods are compared with the extended Kalman filter(EKF).The results of AUV navigation experiment at Qiandao Lake show that the method based on RBPF can provide the best navigation performance.However,algorithm analysis shows that this method requires more computational effort compared with the other two filter algorithms.

     

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