A New Method Implementation of Kalman Filter Based on FPGA

Xin Li; Cong Wang; Qing Zhen Zhang; Xiao Fu Zou

doi:10.4028/www.scientific.net/AMR.945-949.1725

Paper Titles

Establishment and Analysis of Mathematical Model of the Accuracy Identification of Five-Axis CNC Machine Tools
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Graphical Fault Diagnosis Expert System of CNC Machine Tool Based on B/S
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Design on the New Composite Rail of Beam in CNC Gantry Machine Tool
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The Data Acquisition and Processing of Cutting Parameter Database
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A New Method Implementation of Kalman Filter Based on FPGA
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Design and Implementation of Federal Kalman Filter Based on FPGA
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User Interface Design of 1090ES Mode Embedded Ground-Based Transceiver System
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Design of Real-Time Large Field Video Display System Based on FPGA
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Design of the Wireless Data Acquisition System for Experimental Rabbit Rectal Temperature Based on Bluetooth and ARM Technologies
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949A New Method Implementation of Kalman Filter Based...

A New Method Implementation of Kalman Filter Based on FPGA

Abstract:

Kalman filter is one of the most essential and important computing methods in the fields of control, signal processing and communication. In the past, mostly Kalman filter is implemented by DSP, but the operating speed could not meet the requirement. Therefore, the study will research the implement methods of Kalman filter based on FPGA. MicroBlaze soft core and VHDL (Hardware Description Language) are used to implement Kalman filter. The operating results will be analyzed and compared with each other.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

1725-1728

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.945-949.1725

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Online since:

June 2014

Authors:

Xin Li, Cong Wang*, Qing Zhen Zhang, Xiao Fu Zou

Keywords:

FPGA, Implementation Methods, Kalman Filter

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* - Corresponding Author

References

[1] Bing D, Tao T, Junmin P. DSP based sensorless control for induction motor using extended Kalman filter[C]. Electronics, Circuits and Systems, 2000 ICECS 2000 The 7th IEEE International Conference on; 2000: IEEE; 2000. pp.390-3.

DOI: 10.1109/icecs.2000.911563

Google Scholar

[2] Liu Y, Bouganis C-S, Cheung PY. Efficient mapping of a Kalman filter into an FPGA using Taylor expansion[C]. Field Programmable Logic and Applications, 2007 FPL 2007 International Conference on; 2007: IEEE; 2007. pp.345-50.

DOI: 10.1109/fpl.2007.4380670

Google Scholar

[3] Houtekamer P, He B, Mitchell HL. Parallel Implementation of an Ensemble Kalman Filter[J]. Monthly Weather Review. (2013).

DOI: 10.1175/mwr-d-13-00011.1

Google Scholar

[4] Zhang X, Kang C. Study on Kalman filtering for noise filtration in INS[C]. System Simulation and Scientific Computing, 2008 ICSC 2008 Asia Simulation Conference-7th International Conference on; 2008: IEEE; 2008. pp.827-30.

DOI: 10.1109/asc-icsc.2008.4675476

Google Scholar

[5] Jin Q. A Modified Federal Kalman Filter Algorithm and its Application at Integrated Navigation System [J]. Fire Control and Command Control. 2009; 7: 041.

Google Scholar

[6] Bonato V, Marques E, Constantinides GA. A floating-point extended kalman filter implementation for autonomous mobile robots[J]. Journal of Signal Processing Systems. 2009; 56(1): 41-50.

DOI: 10.1007/s11265-008-0257-8

Google Scholar