基于加權(quán)自適應(yīng)平方根容積卡爾曼濾波的GPS/INS組合導(dǎo)航方法
doi: 10.11999/JEIT170597
基金項(xiàng)目:
國家自然科學(xué)基金(61301094, 61473308, 61501430)
A GPS/INS Integrated Navigation Method Based on Weighting Adaptive Square-root Cubature Kalman Filter
Funds:
The National Natural Science Foundation of China (61301094, 61473308, 61501430)
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摘要: 針對GPS/INS組合導(dǎo)航系統(tǒng)中,由于量測噪聲統(tǒng)計(jì)的不確定性導(dǎo)致平方根容積卡爾曼濾波器(SCKF)濾波精度下降甚至發(fā)散的問題,該文提出一種基于加權(quán)的自適應(yīng)SCKF(WASCKF)方法。該方法首先利用移動(dòng)開窗理論對SCKF新息的協(xié)方差陣進(jìn)行最大似然估計(jì),實(shí)現(xiàn)對測量噪聲統(tǒng)計(jì)特性的在線調(diào)整;然后,利用加權(quán)理論,依據(jù)窗口內(nèi)不同時(shí)刻信息的有用程度的不同而設(shè)置相應(yīng)的權(quán)值,增強(qiáng)對窗口內(nèi)有用信息的利用。最后,將WASCKF方法應(yīng)用于GPS/INS組合導(dǎo)航系統(tǒng)中進(jìn)行仿真驗(yàn)證,并與SCKF和ASCKF方法進(jìn)行比較,結(jié)果表明,在測量噪聲統(tǒng)計(jì)存在不確定情況下,該文所提出方法的速度誤差和位置誤差的均方根均小于SCKF和ASCKF方法,能夠有效地提高GPS/INS組合導(dǎo)航系統(tǒng)對量測噪聲統(tǒng)計(jì)不確定的自適應(yīng)能力與導(dǎo)航性能。Abstract: In the GPS/INS integrated navigation system, the filtering precision of Square-root Cubature Kalman Filter (SCKF) will decrease or even diverge resulting from the uncertainty of the measured noise statistics, therefore, a Weighting Aaptive Square-root Cubature Kalman Filter (WASCKF) method is proposed in this paper. Firstly, the moving window method is employed to conduct the maximum likelihood estimation of the covariance matrix of SCKF, in order to realize the on-line adjustment of the statistical characteristics of the measured noise. Then, the weighting theory is utilized to set the corresponding weights according to the usefulness of the information at different times in the window, thus it takes great use of effective information in the window. Finally, the WASCKF is applied to the GPS/INS integrated navigation system for simulation and verification, and comparing with the SCKF and ASCKF methods. The results indicate that the mean square root of velocity errors and position errors of the proposed method are less than SCKF and ASCKF, and it can effectively improve the adaptive capability and navigation performance of GPS/INS integrated navigation system with the measured noise uncertainty.
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Key words:
- Integrated navigation /
- Measured noise /
- Cubature Kalman Filter (CKF) /
- Weighting
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