NDLI: Resolution improvement of measurement systems through optimal filtering techniques-Implementation issues on discrete signal processors

Content Provider	IEEE Xplore Digital Library
Author	Demoment, G. Reynaud, R.
Copyright Year	1993
Description	Author affiliation: Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France (Demoment, G.)
Abstract	In many measurement problems, it is found that the lack of resolution of the measuring device is the consequence of some blurring of the measured signal. Under linearity and shift-invariance assumptions, the signal restoration can be performed by a linear filtering of the data implementing some minimum mean square error (MSE) deconvolution. One possible solution to the problem involves the use of a Kalman filter. If all the processes are stationary and the measurement noise is white, the steady-state Kalman filter and the infinite impulse response (IIR) Wiener filter are identical. The recursiveness of the Kalman filter algorithm is very amenable to VLSI implementation. The aim is to discuss the problems inherent in the implementation of a Kalman filter structure on specialized VLSI devices such as discrete signal processors (DSP). To this end, the basic algorithm is split into elementary operations involving functional units with a high degree of internal parallelism such as a multiplier-accumulator unit. Due to the real-time processing constraint, special attention is paid to rounding effects, and a comparison is made between fixed point and floating point arithmetics.
Starting Page	391
Ending Page	396
File Size	685969
Page Count	6
File Format	PDF
ISBN	0780312295
DOI	10.1109/IMTC.1993.382611
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-05-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal resolution Signal processing algorithms Very large scale integration Linearity Signal restoration Maximum likelihood detection Mean square error methods Deconvolution Noise measurement White noise
Content Type	Text
Resource Type	Article

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