本文選題：控制科學(xué)與技術(shù) + 慣性導(dǎo)航系統(tǒng)��； 參考：《兵工學(xué)報(bào)》2016年07期

【摘要】：考慮到空天飛行器飛行環(huán)境和運(yùn)動(dòng)特性下導(dǎo)航傳感器誤差的噪聲統(tǒng)計(jì)特性不可能完全精確已知,若使用常規(guī)卡爾曼濾波進(jìn)行在線標(biāo)定,將會(huì)導(dǎo)致濾波精度下降甚至發(fā)散。設(shè)計(jì)一種基于新息自適應(yīng)濾波方法的慣性測量單元(IMU)誤差在線標(biāo)定方案和算法,克服常規(guī)卡爾曼濾波需預(yù)先知道噪聲統(tǒng)計(jì)特性的不足,設(shè)計(jì)包含IMU安裝誤差、刻度因子誤差和隨機(jī)常值誤差在內(nèi)的27維高階狀態(tài)變量的誤差標(biāo)定模型,分析提出可同時(shí)對(duì)系統(tǒng)噪聲和量測噪聲協(xié)方差矩陣進(jìn)行動(dòng)態(tài)調(diào)整的新息自適應(yīng)濾波在線標(biāo)定算法。仿真驗(yàn)證實(shí)驗(yàn)表明,相較于采用常規(guī)卡爾曼濾波以及Salychev O自適應(yīng)濾波算法進(jìn)行在線標(biāo)定,所設(shè)計(jì)的新息自適應(yīng)濾波在線標(biāo)定方法能更有效實(shí)現(xiàn)對(duì)IMU誤差的動(dòng)態(tài)標(biāo)定及補(bǔ)償,進(jìn)一步提高了慣性導(dǎo)航系統(tǒng)精度。實(shí)物驗(yàn)證實(shí)驗(yàn)表明,該方法可有效標(biāo)定IMU誤差殘差,提高導(dǎo)航精度,為工程應(yīng)用帶來較大便利。
[Abstract]:In view of the fact that the noise statistics of navigation sensor errors under the flight environment and motion characteristics of aircrafts can not be fully known, if the conventional Kalman filter is used for on-line calibration, the filtering accuracy will decrease or even diverge. An on line calibration scheme and algorithm for inertial measurement unit (IMU) errors based on innovative adaptive filtering method is designed. It overcomes the deficiency of conventional Kalman filter which needs to know the statistical characteristics of noise in advance. The design includes IMU installation error. The error calibration model of 27 dimensional high order state variables including calibration factor error and random constant error is analyzed and a novel adaptive filtering online calibration algorithm is proposed which can dynamically adjust the covariance matrix of system noise and measurement noise simultaneously. The simulation results show that compared with the conventional Kalman filter and Salychev O adaptive filtering algorithm, the proposed method can effectively calibrate and compensate the IMU error. The precision of inertial navigation system is further improved. The experimental results show that this method can effectively calibrate the error residuals of IMU, improve the navigation accuracy, and bring great convenience for engineering application.
【作者單位】： 南京航空航天大學(xué)導(dǎo)航研究中心;
【基金】：國家自然科學(xué)基金項(xiàng)目(61533008;61533009;61374115) 國家留學(xué)基金委資助項(xiàng)目(2012年) 江蘇省六大人才高峰資助項(xiàng)目(2013-JY-013) 江蘇省高校優(yōu)勢學(xué)科建設(shè)工程項(xiàng)目(2014年) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(NP2015406;NJ20150012;NP20152212;NS2014031) 南京航空航天大學(xué)研究生創(chuàng)新基地(實(shí)驗(yàn)室)開放基金項(xiàng)目(kfjj20150315)
【分類號(hào)】：V249.3

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本文編號(hào)：2032019