Nautilus Automates, You Analyze Reproducible Analysis of Sensor Data - - PowerPoint PPT Presentation

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Nautilus Automates, You Analyze Reproducible Analysis of Sensor Data - - PowerPoint PPT Presentation

Nautilus Automates, You Analyze Reproducible Analysis of Sensor Data in R Dr. Benjamin Ashwell Dr. Kevin Kirshenbaum 21 March, 2018 We need to know how well sensors that provide positional data work 1 We need to know how well sensors that


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Nautilus Automates, You Analyze

Reproducible Analysis of Sensor Data in R

  • Dr. Benjamin Ashwell
  • Dr. Kevin Kirshenbaum

21 March, 2018

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We need to know how well sensors that provide positional data work

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We need to know how well sensors that provide positional data work This apparently simple goal is actually very complicated

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Track-to-truth assignment is often tedious and ambiguous

Latitude Longitude

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Who is this track tracking? How should we evaluate its track accuracy?

Track-to-truth assignment is often tedious and ambiguous

Latitude Longitude

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Track-to-truth assignment is often tedious and ambiguous

When was this target detected? Latitude Longitude

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The things that matter for sensor performance change with the mission

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Surveillance radars Fire control radars

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Target A Target B Track 1 Track 2 Target C Track 3 Target D

Nautilus takes tracks and truth…

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… and assigns tracks to the most likely targets

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Target A Target B Track 2 Target C Target D Track 3 Track 1

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With track-to-truth assignments, we can start answering questions

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Target Name Detection Range (km) Detection Time Avg Position Error (m) F-18 2.16 1/1/2015 0:15 46.36 EA-18G 1.58 1/1/2015 0:22 45.6 P-8A 2.58 1/1/2015 0:07 40.54 LCS 4 4.2 1/1/2015 1:13 31.46

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With track-to-truth assignments, we can start answering questions

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USS Good Guy

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Nautilus produces a number of different plots

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Our approach, Nautilus, compares sensor reports to reality

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Nautilus is designed for operational testing, so we’re interested in the correctness of actionable information provided by the sensor Nautilus is system agnostic

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What you need to use Nautilus

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  • A basic understanding of R
  • Truth data for ownship (the sensor) and targets: time,

latitude, longitude, altitude

  • The sensor tracks: time, latitude, longitude, altitude, track

ID

  • Only 2 (or 3) user inputs to assign tracks to targets
  • Patience and a willingness to experiment
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Which target is each track following?

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Target A Target B Track 1 Track 2 Target C Track 3 Target D

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Step 1: Nautilus assigns each sensor point to the closest target

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

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Applies a cutoff distance: any sensor point ‘wronger’ than δ is a false track

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Target A Track 2 Target C Track 3 Target D Track 1

δ

Target B

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Step 2: Removes points for which we have no nearby truth data

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

δ

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A small cutoff may unfairly reduce error estimates…

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

δ

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But a large cutoff may include additional false track points

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

δ

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Changing the method to a window method will smooth the target assignment

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Target A Target B Track 1 Track 2 Target C Track 3 Target D t = τ t = τ - α t = τ + α

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Target A Target B Track 1 Track 2 Target C Track 3 Target D

Changing the method to a window method will smooth the target assignment

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Target A Target B Track 1 Track 2 Target C Track 3 Target D

Changing the method to a window method will smooth the target assignment

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Adjusting window size may change results

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

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Adjusting window size may change results

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

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Adjusting window size may change results

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Target A Track 2 Target C Track 3 Target D Track 1 Target B

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How do we know our assignments are right?

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Because it is sensor system agnostic, Nautilus cannot judge the reasonability of its answers

Nautilus automates, you analyze

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R Demonstration

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Our code is modular – use the pieces that you find useful

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  • Automatically calculate values like relative bearing,

target aspect, and slant range between targets

  • Useful interactive figures for event reconstruction
  • Import and export data from/to SIMDIS
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Backup

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What do we even mean by performance?

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What do we even mean by performance?

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Nautilus tries to do what your eyes do automatically

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1. Calculate the distance from each track to each target (User specifies assignment method and cutoff distance)

  • 2. Assign track to closest target (caution: reasonable

assumption)

  • 3. Flag false tracks (distance > δ)
  • 4. Generate figures and diagnostics