GPS position solution algorithm based on the optimization theory
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摘要: 针对传统定位解算方法存在的问题,基于优化理论的思想提出了一种新的定位解算方法——基于优化理论的最大后验估计算法.介绍了该方法的基本原理,详细给出了算法的推导过程,该方法用优化理论的思路求解系统状态量的最大后验概率估计值.它是从系统状态量、观测量的联合概率密度函数出发,将估计问题转化成优化问题,用优化问题的解法对系统的状态进行估计.在此基础上,用仿真实验验证了该方法进行定位解算的有效性.实验结果表明该方法完全解决了定位解算中的非线性问题,并拥有较高的定位精度.Abstract: In order to solve the problems of the traditional positioning solution methods, a new position solution method which was maximum a posteriori estimation based on the optimization theory was put forward. The basic principle of the method was introduced, and the derivation of the algorithm was detailed. The algorithm was from the joint probability density function of the system state variables, observation variables, and then transformed the estimation problem into optimization problem, using the solution of the optimization problem to estimate the state variables of the system. On this basis, simulation experiments had been used to show the effectiveness of the method. The experimental results show that the method can completely solve the nonlinear problem of the position solution, and have a high positioning accuracy.
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