發(fā)布時間：2019-03-04 13:35

【摘要】：針對光學線陣遙感影像幾何定位中,系統誤差改正參數對應系數矩陣存在誤差的問題,提出了一種基于正則化總體最小二乘的光學線陣遙感影像定位方法。首先依據有理函數模型的定義,構建共線條件方程,利用線性化構建光學線陣影像定位方法和系統誤差改正方法,然后依據EIV模型的定義和性質構建相應的優(yōu)化目標函數,并引入正則化項,依據Lagrange條件極值原理推導基于正則化總體最小二乘的系統誤差參數迭代估計方法。實驗結果表明:與經典的最小二乘平差算法相比,該方法的總體定位精度提高了11.61%,且比Tikhonov正則化法的定位精度平均提高了6.06%。本文提出方法在不增加任何額外控制信息的情況下,是提高光學線陣影像定位精度的有效途徑。
[Abstract]:Aiming at the error of the coefficient matrix corresponding to the system error correction parameters in the geometric positioning of optical linear remote sensing images, an optical linear array remote sensing image localization method based on the regularization population least squares is proposed in this paper. Firstly, according to the definition of rational function model, the collinear conditional equation is constructed, and the linear array image localization method and the system error correction method are constructed. Then, according to the definition and properties of the EIV model, the corresponding optimization objective function is constructed. The regularization term is introduced and the iterative estimation method of system error parameters based on regularization population least squares is derived based on the Lagrange conditional extremum principle. The experimental results show that, compared with the classical least square adjustment algorithm, the overall positioning accuracy of this method is increased by 11.61% and 6.06% higher than that of the Tikhonov regularization method on average. The method proposed in this paper is an effective way to improve the positioning accuracy of optical linear array images without adding any additional control information.
【作者單位】： 信息工程大學地理空間信息學院;地理信息工程國家重點實驗室;
【基金】：國家自然科學基金資助項目(No.41471387;No.41301526) 地理信息工程國家重點實驗室開放基金資助項目(No.SKLGIE2015-M-3-1)
【分類號】：TP751

【相似文獻】

相關碩士學位論文 前2條

1 張亮;高密度電阻率正則化反演及應用研究[D];東華理工大學;2015年

2 林文東;基于統一框架結構的正則化地球物理反演研究[D];東華理工大學;2014年

，

本文編號：2434305