發(fā)布時(shí)間：2018-09-10 18:51

【摘要】：在動(dòng)態(tài)環(huán)境下導(dǎo)航定位受到很多因素影響,且異常噪聲會(huì)嚴(yán)重影響導(dǎo)航濾波結(jié)果。通過研究Bayes濾波的抗差方法,在導(dǎo)航觀測(cè)方程中采用高斯混合模型,對(duì)混合模型不確定度參數(shù)采用層次模型實(shí)時(shí)估計(jì)。借助指示變量進(jìn)行模型變換,削弱導(dǎo)航過程中異常噪聲的影響。并采用Rao-Blcakwellized粒子采樣方法,求取復(fù)雜、非標(biāo)準(zhǔn)形式的狀態(tài)后驗(yàn)分布。最后通過衛(wèi)星導(dǎo)航以及組合導(dǎo)航實(shí)驗(yàn)算例,分析驗(yàn)證了基于高斯混合模型的Bayes濾波在動(dòng)態(tài)導(dǎo)航定位中的抗差性能。
[Abstract]:In dynamic environment, navigation location is affected by many factors, and abnormal noise will seriously affect the navigation filtering results. By studying the robust method of Bayes filtering, Gao Si mixed model is used in navigation observation equation, and real-time hierarchical model is used to estimate the uncertainty of mixed model. The influence of abnormal noise in navigation process is weakened by using indicator variable to transform the model. The complex, non-standard state posterior distribution is obtained by Rao-Blcakwellized particle sampling method. Finally, the robust performance of Bayes filter based on Gao Si hybrid model in dynamic navigation and positioning is analyzed and verified by the experimental examples of satellite navigation and integrated navigation.
【作者單位】： 信息工程大學(xué);
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(41274016;40974010) 地理信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室重點(diǎn)基金項(xiàng)目(SKLGIE2014-Z-2-1) 信息工程大學(xué)地理空間信息學(xué)院創(chuàng)優(yōu)基金(XS201504)
【分類號(hào)】：P228.4

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