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IMPLEMENTATION OF EXTENDED KALMAN FILTER ON FPGA

机译:扩展卡尔曼滤波器在FPGA上的实现

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The purpose of this paper is to explore the concepts and consequences of implementing the Extended Kalman Filter (EKF) on the FPGA. The methods of Runge-Kutta and Taylor-Heun are applied to approximate the continuous time update. The methods of Rugge-Kutta and Gauss-Legendre are used to solve the Riccati equation in order to update the discrete time measurement. The simulation on Matlab Simulink and implementation on the hardware in-loop are completed. Tradeoff between clock frequency, hardware resources and design accuracy are analyzed in the design. Recommended works describe the limitation of the design and give the suggestion on how to save the hardware resources and increase the accuracy.
机译:本文的目的是探讨在FPGA上实现扩展卡尔曼滤波器(EKF)的概念和结果。应用Runge-Kutta和Taylor-Heun的方法来近似连续时间更新。使用Rugge-Kutta和Gauss-Legendre方法求解Riccati方程,以更新离散时间测量。完成了在Matlab Simulink上的仿真和在硬件中的实现。在设计中分析了时钟频率,硬件资源和设计精度之间的折衷。推荐的作品描述了设计的局限性,并提出了如何节省硬件资源并提高精度的建议。

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