Paper Details: Downloads: 548
Serial Number: P1180844451
Title: An FPGA-Based Design of Fixed-Point Kalman Filter
Authors: Sanjay Sharma and Ruchi Pasricha
Abstract: In this paper we study scaling rules and round-off noise variances in a fixed-point implementation of the Kalman filter for an ARMA time series observed noise free. The kalman filter is realized in a fast form that uses the so-called fast Kalman gain algorithm. The algorithm for the gain is fixed point. Scaling rules and expressions for rounding error variances are derived the numerical results show that the fixed-point realization performs very close to the floating point realization for relatively low-order ARMA time series that are not too narrow band. The floating-point model of the Kalman filter is simulated on matlab and then the design was translated into the fixed-point one using C language. The RTL version of the model was created in VHDL. Experimental results were obtained by running the fixed-point and floating-point filters on identical data sets and a close matching is found between them. RTL simulation is also done and the results obtained were similar to the fixed- as well as floating-point models.
Keywords: FPGA, Kalman, Fixed-point, DQPSK
Journal/Conference: International Journal of Digital Signal Processing
Volume: 9
Issue: 1
Submission Date: 10/29/2008 12:00:00 AM
Review Date: 11/12/2008 12:00:00 AM
Publishing Date: 1/2/2009 12:00:00 AM
Article Downloads: 548
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