基于改进粒子群优化算法的传感器误差集成校正

Integrated calibration of sensor error with improved particle swarm optimization algorithm

摘要:

针对三轴磁通门传感器存在三轴非正交、三轴灵敏度不一致和零偏误差以及水下移动平台磁干扰等问题,本文提出了一种基于改进粒子群优化算法的集成校正方法。首先,详细描述上述误差并建立了数学模型。然后,基于匀强磁场环境中磁场传感器测得的总磁场为定值等特点,提出了基于改进粒子群优化算法的误差参数估计方法。仿真结果表明：提出的集成校正方法能够有效压制由传感器自身误差和平台磁干扰引起的测量误差,传感器测量精度得到明显改善；与传统粒子群优化算法相比,改进方法具有较高的求解精度和抗噪能力。

Abstract:

For the non-orthogonality between axes, different scale factors and bias error of the fluxgate sensor and platform magnetic interference, this study present an integrated calibration method with improved particle swarm optimization algorithm. Firstly, the above-mentioned errors are discussed in detail and the mathematical model is established. Then, the improved particle swarm optimization algorithm is used to estimate the error parameters. Two simulation examples are designed to verify the effectiveness of the proposed method. The simulation results show that after calibration, the measurement error caused by the system error and platform magnetic interference can be reduced, and the measurement accuracy has been improved. Compared with the traditional particle swarm optimization algorithm, the proposed method has higher solution accuracy and higher robustness against noise.