摘要
针对运动载体的相对方位角误差问题,提出一种基于移动-分段执行的卡尔曼滤波算法,以及具有可变初始群值域的专门化遗传基因算法,提出的算法用来抑制信号源系统的有色噪声和测量系统的白色噪声对载体相对方位角的影响。该算法首先对利用判据解算出的相对方位角的近似解运行移动-分段执行的卡尔曼滤波算法,得出相对方位角的期望值,然后运行遗传算法得到相对方位角的最优估值。计算结果的精确度和执行过程的流畅性表明,该算法与天空偏振光传感器相配合,能够为当前迅速发展的自主定位技术提供一个可靠的实现手段。
Considering the relative azimuth error of the moving object,a Kalman filter algorithm based on moving block execution and a specialized genetic algorithm with variable initial group of domain were proposed. It is to restrain the influence brought by the colored noise of signal source system and the white noise of measurement system error. The expected value of the relative azimuth was calculated firstly by using Kalman filter algorithm based on moving block execution,and then the optimal estimation of the relative azimuth was got by running the genetic algorithm. The accuracy of the results and the smoothness of the execution show that the algorithm cooperating with the polarization instrument can provide a reliable realization means for the rapidly growing autonomous positioning technology.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2015年第3期404-408,共5页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(61174220)
北京市教委基金资助项目(KM201210028002)
关键词
相对方位角
卡尔曼滤波算法
遗传基因算法
最优估值
偏振光传感器
自主定位
relative azimuth
Kalman filter algorithm
genetic algorithm
optimal estimation
polarization instrument
autonomous positioning
