發(fā)布時間：2018-07-13 22:00

【摘要】：針對GPS/INS組合導航中因觀測異常導致系統(tǒng)狀態(tài)先驗信息矩陣失去對稱正定性,及傳統(tǒng)等價權函數(shù)抗差算法易遇到病態(tài)矩陣,引起濾波性能下降的問題,提出一種基于奇異值分解的改進抗差UKF算法.該算法克服了先驗協(xié)方差矩陣負定性變化,通過判斷矩陣病態(tài)性實現(xiàn)智能選取抗差策略.最后利用車載實測數(shù)據(jù)進行驗證,所得結果表明,SVD-UKF導航解精度稍優(yōu)于EKF算法,改進的抗差策略能夠極大減弱單獨、連續(xù)以及混合的觀測異常對導航解的影響,提高了導航解精度和可靠性.
[Abstract]:In view of the loss of symmetric positive definiteness of system state priori information matrix due to abnormal observation in GPS / ins integrated navigation system, the traditional equivalent weight function robust algorithm is prone to encounter ill-conditioned matrix, which leads to the degradation of filtering performance. An improved robust UKF algorithm based on singular value decomposition (SVD) is proposed. The algorithm overcomes the negative qualitative change of the priori covariance matrix and intelligently selects the robust strategy through the ill-condition of the judgment matrix. Finally, the experimental data are used to verify that the accuracy of SVD-UKF navigation solution is slightly better than that of EKF algorithm, and the improved robust strategy can greatly reduce the influence of single, continuous and mixed observation anomalies on the navigation solution. The accuracy and reliability of navigation solution are improved.
【作者單位】： 中國礦業(yè)大學國土環(huán)境與災害監(jiān)測國家測繪局重點實驗室;中國礦業(yè)大學環(huán)境與測繪學院;
【基金】：新世紀優(yōu)秀人才支持計劃項目(NCET-13-1019) 江蘇省高校優(yōu)勢學科建設工程項目(SZBF 2011-6-B35) 江蘇省普通高校研究生科研創(chuàng)新計劃項目(CXLX13 944)
【分類號】：TN96.2

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