摘要
在航天摄影测量卫星线阵CCD影像的外方位元素解算中,经常产生严重的病态性问题,如果采用最小二乘原理解算,其解明显偏离真值,甚至无法求得外方位元素,在分析以往解决办法的基础上,引入主成分估计来解算,并根据外方位元素解算问题的实际,提出了确定主成分估计中偏参数的3种方法,实验证明该方法稳定、有效。
The ill\|conditioning often occur on computing the exterior orientation elements of satellite one\|line scanner imagery in space photogrammetry or satellite photogrammetry. If least squares estimation method is used, the true values of the exterior orientation elements of satellite one\|line scanner imagery might not be gotten. In fact, the ill\|conditioning does have an unusually large effect on the LS estimation and can deteriorate results completely. In such a case, we need to further improve the calculation procedures on computing the exterior orientation elements of satellite one\|line scanner imagery by using the recently developed biased estimation theory in modern statistics. To overcome the difficulties caused by ill\|conditioning, first, this paper analyses previous methods of solving this problem. Then, the principal component estimator method is introduced to directly combat ill\|conditioning in computing the exterior orientation elements of satellite one\|line scanner imagery. According to practical situations, the three methods of choosing the biased parameter contained in the principal component estimator is also provided in this paper. Experimental results show that in some cases, the proposed principal component estimator can overcome ill\|conditioning effectively and this method is very steady and effective.
出处
《遥感技术与应用》
CSCD
2003年第1期14-18,共5页
Remote Sensing Technology and Application
基金
国家杰出青年科学基金项目(49825107
40125013)
国家自然科学基金项目(40074006)
河南省自然科学基金项目(004051300)。