基于卡方檢驗(yàn)的抗差自適應(yīng)Kalman濾波在變形監(jiān)測中的應(yīng)用
發(fā)布時(shí)間:2019-04-02 14:32
【摘要】:在抗差Kalman濾波的基礎(chǔ)上引入雙自適應(yīng)因子,分別對(duì)動(dòng)態(tài)模型不準(zhǔn)確和觀測模型存在粗差進(jìn)行調(diào)節(jié),構(gòu)建雙自適應(yīng)因子濾波模型。針對(duì)抗差自適應(yīng)Kalman濾波效率較低的缺點(diǎn),通過構(gòu)建基于卡方檢驗(yàn)的抗差自適應(yīng)Kalman濾波,先用卡方檢驗(yàn)對(duì)粗差進(jìn)行檢驗(yàn),再調(diào)用抗差自適應(yīng)Kalman濾波進(jìn)行處理。工程實(shí)例表明,雙自適應(yīng)因子濾波模型可以很好地抵御粗差,并減弱模型不精確的影響。基于卡方檢驗(yàn)的抗差自適應(yīng)Kalman濾波不僅可以削弱粗差對(duì)濾波估值的影響,而且可以提高數(shù)據(jù)處理的效率。
[Abstract]:Based on the robust Kalman filter, two adaptive factors are introduced to adjust the inaccuracy of the dynamic model and the gross error of the observation model respectively, and the double adaptive factor filtering model is constructed. In view of the low efficiency of robust adaptive Kalman filtering, a robust adaptive Kalman filter based on Chi-square test is constructed. First, the gross error is tested by Chi-square test, and then the robust adaptive Kalman filter is used to deal with it. The engineering example shows that the double adaptive factor filtering model can resist the gross error well and weaken the imprecise influence of the model. The robust adaptive Kalman filter based on Chi-square test can not only weaken the influence of gross error on filtering estimation, but also improve the efficiency of data processing.
【作者單位】: 廣西空間信息與測繪重點(diǎn)實(shí)驗(yàn)室;桂林理工大學(xué)測繪地理信息學(xué)院;桂林理工大學(xué)廣西礦冶與環(huán)境科學(xué)實(shí)驗(yàn)中心;空軍大連通信士官學(xué)校;浙江省測繪大隊(duì);城市空間信息工程北京市重點(diǎn)實(shí)驗(yàn)室;
【基金】:國家自然科學(xué)基金(41461089) 廣西“八桂學(xué)者”崗位專項(xiàng) 廣西空間信息與測繪重點(diǎn)實(shí)驗(yàn)室研究基金(桂科能151400702,151400732,140452402) 廣西礦冶與環(huán)境科學(xué)實(shí)驗(yàn)中心課題(KH2012ZD004) 廣西自然科學(xué)基金(2014GXNSFAA118288) 城市空間信息工程北京市重點(diǎn)實(shí)驗(yàn)室項(xiàng)目(2016204)~~
【分類號(hào)】:P227;TU196.1
本文編號(hào):2452633
[Abstract]:Based on the robust Kalman filter, two adaptive factors are introduced to adjust the inaccuracy of the dynamic model and the gross error of the observation model respectively, and the double adaptive factor filtering model is constructed. In view of the low efficiency of robust adaptive Kalman filtering, a robust adaptive Kalman filter based on Chi-square test is constructed. First, the gross error is tested by Chi-square test, and then the robust adaptive Kalman filter is used to deal with it. The engineering example shows that the double adaptive factor filtering model can resist the gross error well and weaken the imprecise influence of the model. The robust adaptive Kalman filter based on Chi-square test can not only weaken the influence of gross error on filtering estimation, but also improve the efficiency of data processing.
【作者單位】: 廣西空間信息與測繪重點(diǎn)實(shí)驗(yàn)室;桂林理工大學(xué)測繪地理信息學(xué)院;桂林理工大學(xué)廣西礦冶與環(huán)境科學(xué)實(shí)驗(yàn)中心;空軍大連通信士官學(xué)校;浙江省測繪大隊(duì);城市空間信息工程北京市重點(diǎn)實(shí)驗(yàn)室;
【基金】:國家自然科學(xué)基金(41461089) 廣西“八桂學(xué)者”崗位專項(xiàng) 廣西空間信息與測繪重點(diǎn)實(shí)驗(yàn)室研究基金(桂科能151400702,151400732,140452402) 廣西礦冶與環(huán)境科學(xué)實(shí)驗(yàn)中心課題(KH2012ZD004) 廣西自然科學(xué)基金(2014GXNSFAA118288) 城市空間信息工程北京市重點(diǎn)實(shí)驗(yàn)室項(xiàng)目(2016204)~~
【分類號(hào)】:P227;TU196.1
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