摘要
为了更快速、准确地解算差分全球定位系统(DGPS)整周模糊度,把改进粒子群优化算法用于模糊度固定解搜索环节。在DGPS整周模糊度解算中,在DGPS载波相位观测方程的基础上,利用最小二乘估计模糊度浮点解和协方差矩阵;对模糊度浮点解作降相关处理;利用改进粒子群算法搜索模糊度固定解。实例结果表明:在和LAMBDA算法的1000个历元对比实验中,二者的解算成功率都在98%左右,相差不大,但改进粒子群算法搜索时间是12.472 s,比LAMBDA算法缩短2.008 s,搜索效率明显提高。
In order to solve the differential global positioning system(DGPS)integer ambiguity more quickly and accurately,the improved particle swarm optimization algorithm is applied to the ambiguity fixed solution search.In the DGPS integer ambiguity calculation,firstly,using the least squares estimation ambiguity floating point solution and covariance matrix,on the basis of DGPS carrier phase observation equation.And then reduce the correlation of ambiguity floating point solution.Finally,the improved particle swarm optimization algorithm is used to search for the ambiguity fixed solution.The example results show that in the 1000 epoch comparison experiment wiTHLAMBDA algorithm,the solution success rate of boTHis about 98%,which is not much difference,but search time of the improved particle swarm algorithm is 12.472 s,which is 2.008 s shorter than the LAMBDA algorithm,the search efficiency is significantly improved.
作者
张波
尚俊娜
ZHANG Bo;SHANG Junna(School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《传感器与微系统》
CSCD
2020年第1期129-131,135,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(11603041)
关键词
差分全球定位系统(DGPS)
整周模糊度
改进粒子群优化算法
最小二乘估计
降相关处理
differential global positioning system(DGPS)
integer ambiguity
improved particle swarm optimization(PSO)algorithm
least squares estimation
reduce correlation processing
作者简介
张波(1994-),男,硕士研究生,研究方向是卫星导航通信;通讯作者:尚俊娜(1979-),女,博士,副教授,主要从事卫星导航与室内导航定位的研究,E-mail:shangjn@hdu.edu.cn。
