Direct MLE of Position for Ground-Based Vehicles Using PSO

• 作 者: Zhang Hongyang Xu Luping Luo Liyan Gao Na
• 机 构: School of Aerospace Science and Technology, Xidian University, Xi'an, China ,710126
• 出 处: 第七届中国卫星导航学术年会
• 发表日期: 2016年5期
• 关键词: GNSS Maximum likelihood estimation Direct position estimation Particle swarm opt

　　In this paper,a maximum-likelihood estimation of position and velocity in GNSS is derived,called direct position estimation (DPE).In this method,the navigation solution is obtained directly by maximizing the cost function which is derived as a function with respect to the parameters of all satellite signals such as code delay,carrier phase and Doppler frequency.Because the parameters of all satellites are used collectively,this method is optimal in theory.But one of the main drawbacks of this approach is the lack of a computationally efficient optimization algorithm due to the high dimensionality and nonlinearity of the cost function.This paper researches the two-dimensional position search of ground-based vehicles.An effective search method using the particle swarm optimization (PSO) is proposed.PSO is a low-complexity optimization algorithm which doesnt need to compute the gradient.Some simulations have been done to compare this method with grid search method for different SNRs.The computational cost is also analyzed and compared.