本文選題：UKF　切入點(diǎn)：CKF　出處：《電光與控制》2017年09期

【摘要】：扼要介紹了UKF和CKF濾波算法,分析總結(jié)了兩種濾波算法的異同,并基于蒙特卡羅仿真試驗(yàn),對(duì)大方位失準(zhǔn)角情形下UKF濾波算法和CKF濾波算法的應(yīng)用特性進(jìn)行了對(duì)比、分析和總結(jié),指出了UKF濾波算法對(duì)角運(yùn)動(dòng)和線運(yùn)動(dòng)均敏感,角運(yùn)動(dòng)和線運(yùn)動(dòng)方向的激勵(lì)均可以加速其收斂,而CKF濾波算法對(duì)角運(yùn)動(dòng)不敏感,但對(duì)線運(yùn)動(dòng)敏感,角運(yùn)動(dòng)方向的激勵(lì)無助于其對(duì)準(zhǔn)精度的提高,而線運(yùn)動(dòng)方向的激勵(lì)可加速其收斂,且收斂精度隨激勵(lì)效果的加強(qiáng)而提高的特性,為該種情形下對(duì)準(zhǔn)技術(shù)的工程化實(shí)現(xiàn)提供了針對(duì)性建議。
[Abstract]:This paper briefly introduces UKF and CKF filtering algorithms, analyzes and summarizes the similarities and differences of the two filtering algorithms, and compares the application characteristics of UKF filtering algorithm and CKF filtering algorithm in the case of large azimuth misalignment based on Monte Carlo simulation. It is pointed out that the UKF filtering algorithm is sensitive to the angular motion and the linear motion, and the excitation of the angular motion and the direction of the linear motion can accelerate its convergence, while the CKF filtering algorithm is not sensitive to the angular motion, but sensitive to the linear motion. The direction of angular motion does not help to improve the alignment accuracy, while the excitation of the direction of linear motion accelerates its convergence, and the convergence accuracy increases with the enhancement of the effect of excitation. Some suggestions are provided for the engineering realization of alignment technology in this case.
【作者單位】： 海軍航空大學(xué)青島校區(qū);中國人民解放軍92514部隊(duì);山東省產(chǎn)品質(zhì)量檢驗(yàn)研究院;
【分類號(hào)】：TN713
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本文編號(hào)：1678457