# Estimating GPS Positional Error

Bill Witte
,
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#### Summary

Very simply and directly determine the x, y, z accuracy of the various GPS receivers using a simple method that doesn't use a lot of quantitative statistics and yields a gut-level sense of the accuracy of different systems.

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## Context

#### Audience

We primarily use this exercise in an introductory field geophysics class for majors.
Designed for an introductory geology course

#### Skills and concepts that students must have mastered

Basic equipment skills: students must be able to reproducibly acquire positions with various GPS receivers at a known mark, digitally record the positions, and download to a pooled class spreadsheet in a consistent UTM format. Students must understand the UTM coordinate system and basic good GPS practice. Generally we do this project in MS Excel and it serves as an Excel warm-up or refresher exercise.

#### How the activity is situated in the course

Typically we use this very early in the syllabus.

## Goals

#### Content/concepts goals for this activity

Students will acquire GPS positions and plot scatterplots the XY errors and histograms of the vertical errors. Students will tabulate the radial error from the pooled data and will determine the confidence interval for an individual measurement in XY and Z. Typically each student will acquire a 20 positions over a week, with a class size of ~15.

#### Higher order thinking skills goals for this activity

How to make reproducible measurements. Analyzing sources of error. What does a "confidence interval" mean?

## Description of the activity/assignment

After instructing students on basic receiver operation, each student will make many (10-20) position estimates of 3 benchmarks over a week. The different benchmarks will have different views of the skies or vegetation cover. Each student will download their data into a spreadsheet and calculate horizontal and vertical errors which are collated into a class spreadsheet. The positions are sorted by error and plotted in a cumulative frequency plot. The students are encouraged to discuss the distribution, sources of error, and estimate confidence intervals. This exercise gives the students a gut feeling for confidence intervals and the accuracy of data. Students are asked to compare results from different types of data and benchmarks with different views of the sky.

Uses online and/or real-time data
Has minimal/no quantitative component <BR> Addresses student fear of quantitative aspect and/or inadequate quantitative skills