CAJ | 학술논문

利用单频 GPS 载波相位差分技术进行动态精密测量时，由于观测历元少，经典 LAMBDA 算法会出现法矩阵病态导致整周模糊度无法求解。针对这一问题研究了基于 TIKHONOV 正则化原理的改进 LAMBDA 算法。通过对双差观测方程系数矩阵进行奇异值分解选取正则化矩阵，改善了法矩阵的病态性，获得了更高精度的浮点解。利用均方误差矩阵替代协方差阵进行 LAMBDA 求解，提高了模糊度求解的速度和成功率。对连续100组5个历元实测数据计算表明：与原算法相比，改进 LAMBDA算法求得的浮点模糊度偏差从36.48周减小到4.08周，搜索效率和成功率分别改进97.74%和100%。
이용단빈 GPS 재파상위차분기술진행동태정밀측량시，유우관측역원소，경전 LAMBDA 산법회출현법구진병태도치정주모호도무법구해。침대저일문제연구료기우 TIKHONOV 정칙화원리적개진 LAMBDA 산법。통과대쌍차관측방정계수구진진행기이치분해선취정칙화구진，개선료법구진적병태성，획득료경고정도적부점해。이용균방오차구진체대협방차진진행 LAMBDA 구해，제고료모호도구해적속도화성공솔。대련속100조5개역원실측수거계산표명：여원산법상비，개진 LAMBDA산법구득적부점모호도편차종36.48주감소도4.08주，수색효솔화성공솔분별개진97.74%화100%。
When single-frequency GPS carrier phase differential technology is used in dynamic and precise measurement, the normal matrix becomes ill-condition and LAMBDA algorithm can’t work due to less observable epochs. In this paper, an improved LAMBDA algorithm based on regularization decomposing was studied in order to solve the problem. The regularization matrix, which was acquired by singular value decomposition of coefficient matrix, was used to improve the ill-condition of normal matrix and the precision of float solution. LAMBDA algorithm, by using mean square error matrix instead of covariance matrix, can improve the speed and success ratio of the integer ambiguity resolution. The continuous 100 calculation of five epochs’ experiment data show that, compared with the old LAMBDA algorithm, the improved algorithm has reduced the bias of float ambiguity to 4.08 cycles from the original 36.48 cycles, and has improved the efficiency and success ratio of search to 97.74% and 100% respectively.