借助于Bancroft方法快速决定全球定位系统中接收机的大概位置,可作为观测方程线性化的初值.采用最小二乘法来求解方程时,观测数据存在较大误差(即出现粗差)的情况下,最小二乘解会出现小稳定性,即削题呈不适定性.为了克服解的不适定性,引入了正则化方法,采用正则化方法及正则化参数最优选择来提高抗粗差能力.实验结果表明,利用这种定位方法的抗粗差能力有一定的改进,这对实时、快速定位有重要意义.
To determine the approximate position of a global positioning system receiver, the Bancroft method can provide the initial value for linearization of the observation equation, which can then be solved by the least-square (LS) method. Because the solution of IS method is not unique and the observation data have noise, the solution is ill-posed. In order to solve the problem, we introduce the regularization method combined with the optimum choice of regularization parameter. The experimental result indicates that it can enhance the resistance to bad errors, which has significance in real-time fast positioning.