基于PC104的低成本惯性/GPS组合导航平台设计与实验

Di Li, R. Landry, P. Lavoie
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引用次数: 3

摘要

全球定位系统(GPS)/惯性导航系统(INS)的集成在各种导航应用中已经变得非常重要。近十年来,随着微机电传感器(MEMS)的快速发展,低成本的GPS/INS集成应用引起了人们的极大兴趣。提出了一种基于PC104的低成本GPS/INS组合导航平台。平台硬件由低成本惯性传感器和各种PC104兼容外设组件组成,如数据采集卡、GPS接收器、以太网卡、主板、显卡等。利用Simulink实现了包括惯性/GPS数据采集、惯性导航计算和GPS/INS集成卡尔曼滤波在内的平台软件,并借助Matlab实时工场(RTW)实用程序直接加载到PC104母板上进行处理。该平台是完全自嵌入的,可以独立应用,也可以作为系统的一部分。仿真和实际数据实验验证和评估了所提出的设计。实验采用了一种成本极低的MEMS惯性传感器。参考是由战术级惯性测量单元(IMU)导出的导航解决方案。测试结果表明,PC104导航平台提供的综合导航解决方案可与传统笔记本电脑计算的参考解决方案相媲美,但功耗更低,系统体积/复杂性更小,总体成本更低。通过在系统软件中配置相关参数,平台硬件可以兼容不同等级的各种惯性传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PC104 Based Low-cost Inertial/GPS Integrated Navigation Platform: Design and Experiments
The integration of Global Positioning System (GPS)/Inertial Navigation System (INS) has become very important in various navigation applications. In the last decade, with the rapid development of Micro Electro Mechanical Sensors (MEMS), great interest has been generated in low cost integrated GPS/INS applications. This paper presents a PC104 based low cost GPS/INS integrated navigation platform. The platform hardware consists of low cost inertial sensors and an assembly of various PC104 compatible peripherals, such as data acquisition card, GPS receiver, Ethernet card, mother board, graphic card, etc. The platform software including inertial/GPS data acquisition, inertial navigation calculation and integrated GPS/INS Kalman filter is implemented with Simulink, which can be directly loaded and processed in the PC104 mother board with the aid of Matlab Real-Time Workshop (RTW) utility. This platform is totally self-embedded and can be applied independently or as part of a system. Simulation and real data experiments have been performed to validate and evaluate the proposed design. A very low cost MEMS inertial sensor was utilized in the experiments. The reference is the navigation solution derived from a tactic grade Inertial Measurement Unit (IMU). Test results show that PC104 navigation platform delivers the integrated navigation solutions comparable to the reference solutions, which were calculated with a conventional laptop computer, however with less power consumptions, less system volume/complexity and much lower over-all costs. Moreover the platform hardware is compatible to various inertial sensors of different grades by configuring the related parameters in the system software.
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