自適應加權質心算法在高精度星點定位中的應用
發(fā)布時間:2018-12-18 18:09
【摘要】:為實現(xiàn)空間飛行器在高目標星等、像移和光學系統(tǒng)像差等因素影響下的高精度星點定位,提出了一種自適應加權質心細分定位算法。基于最大似然估計推導、建立數(shù)學模型并進行仿真實驗。結果表明,與質心法、加權質心法及高斯擬合法等傳統(tǒng)星點定位算法相比,提出的算法定位精度提高了50%以上,且具有良好的收斂速度,經過5次迭代后,質心定位誤差相對較穩(wěn)定,可以滿足實際應用中對實時性的要求。
[Abstract]:An adaptive weighted centroid subdivision localization algorithm is proposed to achieve high precision star location under the influence of high target magnitude, image shift and optical system aberration. Based on the derivation of maximum likelihood estimation, the mathematical model is established and the simulation experiment is carried out. The results show that compared with the traditional star location algorithms such as centroid method, weighted centroid method and Gao Si fitting method, the proposed algorithm can improve the accuracy of star location by more than 50%, and has a good convergence rate. After five iterations, the proposed algorithm has a good convergence rate. The centroid positioning error is relatively stable, which can meet the real-time requirements in practical applications.
【作者單位】: 中國科學院長春光學精密機械與物理研究所;
【基金】:國家自然科學基金(61205143)
【分類號】:V448.2
,
本文編號:2386274
[Abstract]:An adaptive weighted centroid subdivision localization algorithm is proposed to achieve high precision star location under the influence of high target magnitude, image shift and optical system aberration. Based on the derivation of maximum likelihood estimation, the mathematical model is established and the simulation experiment is carried out. The results show that compared with the traditional star location algorithms such as centroid method, weighted centroid method and Gao Si fitting method, the proposed algorithm can improve the accuracy of star location by more than 50%, and has a good convergence rate. After five iterations, the proposed algorithm has a good convergence rate. The centroid positioning error is relatively stable, which can meet the real-time requirements in practical applications.
【作者單位】: 中國科學院長春光學精密機械與物理研究所;
【基金】:國家自然科學基金(61205143)
【分類號】:V448.2
,
本文編號:2386274
本文鏈接:http://sikaile.net/kejilunwen/hangkongsky/2386274.html