期刊文献+

面向FPGA的惯性导航算法的研究与实现 被引量:1

Research and Implementation of Inertial Navigation Algorithm for FPGA
下载PDF
导出
摘要 针对当前飞控系统中传感器多、运算量庞大,传统微处理器已难以满足其日益增长的性能需求,本文提出了一种面向FPGA的并行化惯性导航算法.本算法采用扩展卡尔曼滤波对结果做最优估计,四阶龙格库塔算法进行积分估计,同时将惯性导航算法进行模块化分割,采用流水线并行处理,提高解算速度.利用FPGA开发板驱动传感器,并在该FPGA上实现对数据的解算,解算结果由接口传输给微处理器,降低了对微处理器接口和性能的要求.最后仿真结果表明,本算法在速度和精度上均有良好的表现,验证了该算法在FPGA上实现的可行性. Aiming at the problem that the sensor in the current flight control system is to many and the computational complexity is large, the traditional microprocessor has been difficult to meet its growing performance requirements. This paper presents a parallel adaptive inertial navigation algorithm for FPGA. In this algorithm, the extended Kalman filter is used to estimate the result. The fourth-order Runge-Kutta algorithm is used to estimate the integral. At the same time, the inertial navigation algorithm is modularized and the parallel processing is used to improve the solution speed. The FPGA development board is used to drive the sensor, and the data is solved on the FPGA. The result of the solution is transmitted from the interface to the microprocessor to reduce the interface and performance requirements of the microprocessor. Finally, the simulation results show that the proposed algorithm has good performance in terms of speed and accuracy, and verifies the feasibility of the algorithm on FPGA.
作者 刘强军 张岩 LIU Qiang-jun;ZHANG Yan(Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China)
出处 《微电子学与计算机》 CSCD 北大核心 2018年第7期58-61,66,共5页 Microelectronics & Computer
基金 广东省科技计划项目(2016B090918047)
关键词 惯性导航算法 FPGA开发板 扩展卡尔曼滤波 龙格库塔算法 INS FPGA Extended Kalman Filter(EKF) Runge-Kutta algorithm
  • 相关文献

参考文献5

二级参考文献32

共引文献83

同被引文献12

引证文献1

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部