空军工程大学学报（自然科学版）2013，Vol.14Issue(2)：66-70,5.DOI:10.3969/j.issn.1009-3516.2013.02.015
认知导航路径整合中方位及尺度参数求解方法
Method of Solving Parameters of Orientation and Scale for Cognitive Navigation's Path Integration
摘要
Abstract
In order to achieve relative orientation and scale values between environmental information and reference information for path integration of UCAV cognitive navigation, a method based on iterative least -squares is proposed to solve high-precision similarity transformation parameters. SURF algorithm is used to extract high robustness feature points, then ratio method is taken to purify the matching pairs to get a point-to-point set, the elements in the set are further transformed into vectors, similarity transformation parameters are gained by iterative least-squares algorithm, then the perceived image's orientation is rotated backward, and the scale is adjusted inversely according to the gained parameters, circulate the operations until relative orientation and scale value are finally obtained. The simulation results show that the use of the above method can get high-precision orientation and scale parameters and anti-noise performance is superior to the least squares algorithm.关键词
SURF/路径整合/迭代最小二乘法/相似变换参数Key words
SURF/ path integration/ iterative least-squares algorithm/ similarity transformation parameters分类
航空航天引用本文复制引用
周阳,吴德伟,邰能建,杜佳..认知导航路径整合中方位及尺度参数求解方法[J].空军工程大学学报（自然科学版）,2013,14(2):66-70,5.基金项目
国家自然科学基金资助项目(61273048) （61273048）
