Solution method of DGPS integer ambiguity based on ICSO
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摘要: 针对差分全球定位系统(DGPS)模糊度解算过程中效率低,搜索慢的问题,对鸡群优化算法(CSO)进行适应性改进,并将改进后的鸡群优化算法(ICSO)应用到整周模糊度的快速解算中,利用卡尔曼滤波求出双差模糊度的浮点解和协方差矩阵,采用Lenstra-Lenstra-Lovasz (LLL)降相关算法对模糊度的浮点解和方差协方差矩阵进行降相关处理,以降低模糊度各分量之间的相关性,在基线长度固定的情况下,利用ICSO搜索整周模糊度的最优解. 采用经典算例进行仿真,仿真结果表明,与已有文献相比在整周模糊度的解算过程中改进的鸡群优化算法能有效提高搜索速度和求解成功率.Abstract: Aiming at the problem of low efficiency and slow search in the DGPS ambiguity resolution process, adaptively improve the chicken swarm optimization(CSO) and apply the improved chicken swarm optimization(ICSO) to the fast search of the integer ambiguity, a Kalman filter is used to obtain the float solution and its covariance matrix of the double-difference ambiguity. The Lenstra-Lenstra-Lovasz (LLL) decorrelation algorithm is adopted to decorrelate the float solution and its covariance matrix, thus, the correlation of each ambiguity float estimation can be eliminated. With a fixed baseline length, ICSO is used to search the optimal solution of the integer ambiguity. Simulations are performed using classic examples, the results show that compared with the literature [5], the improved chicken swarm optimization can effectively improve the search speed and the success rate of the solution.
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