基于差分进化算法的磁梯度张量系统误差校正

Calibration of magnetic gradient tensor system with differential evolution algorithm

针对磁梯度张量系统存在单传感器三轴非正交、三轴灵敏度不一致和零偏以及多传感器测量轴非对准误差等问题,本文提出了一种基于改进差分进化算法的误差校正方法.首先,详细描述上述误差并建立数学模型.然后,基于匀强磁场环境中磁梯度张量系统测得的总磁场为定值、同一方向测量轴输出一致、磁梯度张量分量与张量不变量等于零的特点,提出了基于改进差分进化算法的误差参数估计方法.不同于传统的磁梯度张量系统两步校正方法,该方法只需进行一步反演即可实现单传感器误差参数和多传感器非对准误差参数估计.仿真结果表明:与遗传算法和最小二乘拟合方法相比,本文方法具有较高的求解精度和搜索效率,且抗噪能力较强.实测数据校正结果表明,本文方法可以降低磁梯度张量系统误差引起的测量误差,测量精度得到明显改善.

For the non-orthogonality between axes,different scale factors and bias error of the single magnetic vector magnetometers and misalignment error of the magnetic gradient tensor system,we present a method for calibrating the magnetic gradient tensor system with improved differential evolution algorithm.Firstly,the above-mentioned errors are discussed in detail and the mathematical model is established.Then,the improved differential evolution algorithm is used to estimate the error parameters.The proposed method only needs to perform one-step inversion to realize the calibration of single-sensor system error and multi-sensor misalignment error.Two simulation examples are designed to verify the effectiveness of the proposed method.The simulation results show that,compared with the genetic algorithm and the least square fitting method,the proposed method has higher solution accuracy and search efficiency,and higher robustness against noise.The field test results show that after calibration,the measurement error caused by the system error can be reduced,and the measurement accuracy can be improved.