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Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

机译:基于群体优化的个人手持设备磁力计校准

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摘要

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.
机译:惯性导航系统(INS)由加速度计,陀螺仪和处理器组成,该处理器通过整合特定的力和转速来生成位置和方向解。除加速度计和陀螺仪外,磁力计还可用于根据地球磁场得出用户航向。不幸的是,使用低成本传感器获得的磁场的测量结果通常会因一些错误而受损,包括制造缺陷和外部电磁场。因此,需要对磁力计进行适当的校准以实现高精度航向测量。在本文中,提出了一种基于粒子群优化(PSO)的校准算法来估计低成本磁力计的偏差和比例因子的值。该技术的主要优点是使用了人工智能,不需要任何误差建模或对非线性的了解。此外,当与惯性传感器和GPS / Wi-Fi结合用于室内导航和基于位置的服务(LBS)应用时,提出的算法可以帮助开发行人导航设备(PND)。

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