DEALING WITH MEASUREMENT NOISE

(A gentle introduction to noise filtering)

CONTENTS

INTRODUCTION

When measurements are corrupted by random variations, they are said to be affected by noise. Since the standard deviation is a measure of spread in a data distribution, these random variations can be characterised by the standard deviation of the measured signal. That is, the larger the standard deviation, the noisier is the measurement. The procedure of reducing or attenuating the noise components of a measured signal is commonly known as filtering.

There are many different ways to design filters, but the most common ones have their roots in simple averaging.

The purpose of this set of notes is to

• introduce some of the terminology used in the area of signal processing
• show why signal averaging can reduce the effects of noise
• introduce some filtering algorithms that are based on averaging
• show that the low-pass filter that is commonly used in industry is equivalent to one form of averaging filter

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