基于改进PSO算法的传感器误差集成校正
Integrated Calibration of Sensor Errors with Improved PSO Algorithm
丁学振1
作者信息
- 1. 江苏自动化研究所,江苏 连云港 222061
- 折叠
摘要
为降低搭载于水下移动平台的三轴磁通门传感器受到的平台磁干扰和传感器自身误差(三轴非正交误差、三轴灵敏度不一致误差和零偏误差)的影响,提出了一种基于改进粒子群优化算法的集成校正方法.在分析误差来源的基础上建立了误差校正数学模型,并利用 2 个仿真算例对校正方法的有效性进行了验证.仿真试验结果表明:与传统粒子群优化算法相比,改进算法具有更高的抗噪能力和求解精度;经过校正之后,由传感器自身误差和平台磁干扰引起的测量误差得到了有效压制.
Abstract
To reduce the impact of platform magnetic interference and sensor errors(triaxial non-orthogonal errors,triaxial sensitivity inconsistency errors and zero bias errors)on the triaxial fluxgate sensor mounted on the underwater platform,an integrated calibration method based on improved particle swarm optimization algorithm is proposed in this paper.On the basis of analyzing the error source,a mathematical model for error calibration is established,and the validity of the calibration method is verified by two simulation examples.The simulation results show that compared with the traditional particle swarm optimization algorithm,the improved algorithm has higher robustness against noise and solution accuracy.After calibration,the measurement errors caused by the sensor errors and platform magnetic interference are effectively suppressed.
关键词
磁通门传感器/误差校正/改进粒子群优化算法Key words
fluxgate sensor/error calibration/improved particle swarm optimization algorithm引用本文复制引用
基金项目
国家重点研发计划(2022YFC2808302)
出版年
2024
国家科技期刊平台
NSTL
万方数据