摘要
针对车载GPS定位算法中卡尔曼滤波对异常的观测噪声非常敏感,严重影响车载GPS定位的精度问题,应用Bayes定理,给出观测噪声服从污染正态分布的Bayes滤波算法。研究结果表明:该滤波算法能够有效地抑制异常噪声对车载GPS定位算法的影响;实例解算结果验证了该算法的有效性和可靠性。
Based on the fact that the precision of location of vehicular GPS is significantly affected by the gross errors since Kalman filtering is very sensitive to them,a robust Bayesian estimator for the state parameters of one kind of dynamic models was given based on Bayesian theory with non-Gaussian noises.The results show that this Bayes filter algorithm can resist efficiently affection of abnormal noises.Example proves that the modified Kalman filter is effective and reliable.
出处
《中南大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2010年第4期1462-1466,共5页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(40874005)
国家教育部博士点基金资助项目(200805331086)
国家教育部博士后基金资助项目(20090451489)