摘要
针对利用CHAN算法进行TOA定位时,其定位的精度受环境条件的影响程度较大的问题,提出了一种利用粒子群与CHAN算法协同定位的方法。通过粒子群估算出移动终端的初始解,利用初始解构建残差方程,筛选出LOS环境下对应的基站,并用该基站结合CHAN定位模型对移动终端进行二次定位最终得到位置估计。由实验结果可知,基于融合算法的定位精度比单一算法的定位结果,其定位误差至少降低5 m。
In view of the TOA positioning using CHAN algorithm, the accuracy of the positioning is affected by the environmental conditions greatly. Based on this, a method of cooperative localization based on particle swarm op- timization and CHAN algorithm is proposed. Firstly, through particle swarm to estimate the mobile terminal using the initial solution, construction of initial solution residual equation, and screened under the environment of LOS corre- sponding to the base station, and the base station combined with CHAN positioning model was two times of mobile lo- cation final location estimation. The result showed that The positioning accuracy of the fusion algorithm based on the fusion algorithm is better than that of the single algorithm, and the positioning error is significantly reduced at least 5 meters.
出处
《电子科技》
2017年第8期1-5,共5页
Electronic Science and Technology
基金
国家自然科学基金(61272097)
上海市科委重点支撑项目(13510501400)
关键词
协同定位
CHAN算法
残差分析法
粒子群算法
location
CHAN algorithm
residual analysis method
particle swarm algorithm
