MeteorScan Overview and other Transient Detection Algorithms Pete Gural peter.s.gural@saic

1. MeteorScan Overview and other Transient Detection Algorithms Pete Gural peter.s.gural@saic.com Meteor Orbit Determination Workshop #3 April 17, 2010

2. Algorithmic Development Considerations • Imaging Modalities and Purpose • All sky – Fireball survey and meteorite recovery • Moderate FOV – Meteor flux, mass index, stream characterization • Telescopic – Ablation, orbits, spectroscopy, lunar impacts • Throughput - Real-time, Near-real-time, or Post-collection • Detection - Fast (high SNR) or robust (low SNR) algorithm • False alarms - Tolerance for and mitigation approach • Computing - Processing capacity, storage, interfaces • Analysis - Calibration, Cueing and/or Science exploitation

3. Detection Algorithm Choices • Streak Detection • Matched Filter– Hypothesize motion, shift and stack, then threshold • Best Pd, Pfa but large hypothesis count limits the application to meteors • Hough Transform– Threshold pixels, transform to Hough space, find peaks  feed MF • Good Pd, Pfa suitable for near real-time with short latency • Orientation Kernel– Convolve spatial kernel, merge detections via temporal propagation • Good Pd, Pfa suitable for near real-time with short latency • Cluster Tracking– Threshold pixels, locate clusters, motion consistency • Moderate Pd, Pfa suitable for real-time tracking needing rapid response • Spatial Change – Threshold pixels and match to spatial signature • Poor Pd, Pfa useful when the transient leaves no temporal response • Background Removal • Clutter Suppression – Use noise statistics to whiten the imagery • Meanor Median– Good for stationary background, lower noise threshold • Difference Frames – Good for slowly drifting background, fast processing

4. MeteorScan 3.20 Overview • Primarily for Meteor Detection in Video • Limited analysis capability since users wanted to “roll their own” • Operates at full resolution and near the recorded rate • Used by the North American Professional Meteor Community • Univ. of W. Ontario, NASA/MSFC, SETI • Originally Real-Time on a Mac circa 1997 • Migrated to Non-RT on a PC/Windows system ingesting AVIs • MeteorScan Capabilities • Masking and FOV Calibration • Detection via Hough Transform & MLE • User confirmation review and editing • Radiant association and statistics • Software library for detection-only processing in Windows and Linux

5. MeteorScan Detection Processing Noise Tracking Filters (in blue) Secondary Hough Space Primary Image Space Tertiary MLE Space <MLE> MLE Detect ? . . Max Likelihood Estimate . Frame Differencing PrimaryThresholding Hough Transform Hough Peaks Track Hypothesis

6. Streak Detection - Hough TransformMap spatial coordinate exceedance pixels into Hough space PCD • Traditional HT – hypothesis all lines that pass through each point • Pixel Pair HT - two points define line thus one point in Hough space. Localize pairs to reduce ops count. • Phase Coded Disk HT – convolve PCD kernel around each point to obtain orientation   y x MeteorScan SPFN - LFI Traditional HT 3 points on a line Line in Traditional HT (butterfly self-noise) Pixel pair HT N2 ops Phase coded disk HT N ops

7. Confirmation Mode Screen Shot

8. MTP Detector: Croatian Meteor Network • Video Compression via “SkyPatrol” • CONOPS • Save one RGB bit mapped file for every N seconds of video • For each pixel, keep the max value in time and associated frame# • Extending to temporal mean and std dev (excluding max) for flat fielding • Max Temporal Pixel (MTP) meteor detection software • Uses the MeteorScan detection modules, Post-processing by CMN Maximum Pixel Value Frame Number of Max Reconstructed Video

9. CAMS at the SETI Institute • All-sky coverage with high angular resolution • CONOPS • 5 DVRs monitors 20 CCD cameras for motion detection at 2 sites • Records all cameras via FTP compression (Flat-field Temporal Pixel) • Download only compressed video snippets containing detections • MeteorScan processed on DVR archive • Post-processing for triangulation and orbits by SETI DVR 4 channels DVR 4 channels Archived Detections via MeteorScan DVR 4 channels DVR 4 channels DVR 4 channels

10. MeteorScan for Telescopic Meteors • Fragmentation studies, Precise radiant positions • CONOPS / Issues • Very narrow FOV and large optics  deep stellar lm without intensifier ! • Meteor trailing losses still limits meteor lm  +6.5 • Small FOV lowers # meteors collected • Orion 80mm f/5 finder scope • 2x Focal reducer  2 degree FOV and stellar lm=+10.5 • MeteorScan has option for long streaks Scott Degenhardt’s “Mighty Mini” Orion 50 mm 5 km Short Baseline Meteor Triangulation

11. Transient Video Detection Applications • LFI Detector for the Spanish Fireball Network • Massive Compact Halo Object Detection • Lunar Meteoroid Impact Flash Detection • Meteor Tracking System • Meteor Simulation for ZHR

12. LFI Detector: Spanish Meteor Network • Large format CCD: 4K x 4K pixels • All sky coverage with 2.4 arc-minute resolution • Non-video system: stellar lm = +10, meteor lm = +2 • CONOPS • Slow read out CCD  1 snapshot every 90 seconds • Long Frame Integration (LFI) meteor detection • Differenced frames ( stars + and -, meteors + or - ), Hough Transform PCD • Post processing orbital reductions analysis by SPFN - = HT

13. Massive Compact Halo Object Detection • Jupiter sized objects wandering the galaxy • Stars briefly wink out from occultation • Find TNOs in the plane of the solar system • CONOPS • Collect pairs of dense star field video • Search for short timescale occultation • Use pair coincidence to rule out scintillation • 2 Telescopes with frame rate CCDs • Observation of an open cluster with good timing • MachoScan to identify occulted stars • Space-time coincidence of recorded AVIs • Post processing analysis by Mount Allison University Few meters

14. LunarScan: Lunar Impact Flash Detection • Boulder Sized Meteoroids Smashing into the Moon ! • Hypervelocity impact creates a momentary flash • Duration typically a few tens of milliseconds • One lasted ½ second ! • CONOPS • Monitor the dark face of the Moon • 3 days around first and last quarter • Minimum of two sites >20 km separation • LunarScan software to locate flashes • Register, Track mean and standard deviation • Threshold, Spatial cluster • Post-collection analysis by NASA/MSFC Camera Field of View

15. AIMIT Meteor Tracking System • Increase #s of meteors observed in narrow FOV instruments • Enables spectroscopy and high resolution triangulation/orbits • CONOPS • Wide field camera cues steering system for narrow field instrument • MeteorCue Detection Algorithm • Threshold, Fast clustering, Centroid, Track, Mirror Commands • Response time <100 msec (Galvo), <500 msec (Stepper) • Post-processing Univ of W. Ontario

16. MeteorSim Processing Radiant Particles assumed to have: Initial direction along radiant vector Random start position in cylinder Fixed begin and end heights Fixed magnitude Initial speed V∞ Fixed population index r Mag distribution = [-12,+6.5] Undergone zenith attraction Not decelerated Distance fading loss Atmospheric extinction loss . . . . . . . . . . . . . . . Specific to CCD vs. Human: Limiting magnitude FOV geometry FOV look direction Resolution Integration time Angular velocity loss Off-axis perception Earth Monte Carlo meteor influx simulation for video and visual observations/calibration Converts video counts  Spatial flux  ZHR

17. Algorithmic Backup Charts • MeteorCue • LunarScan • Streak Detection • Matched Filter • Orientation Kernel • Fast Clustering

18. MeteorCue Processing Mean, Threshold, & SNR Tracking Filters (Updated on a few rows per frame) <X> Full Frame Imagery 30 fps <X> + k1s <SNR> + k2sSNR Even Field Row, Col, SNR 2 x 16-bit Digital Signals Vx, Vy Alpha-Beta Tracker 30 Hz Odd Field Row, Col, SNR Repeat every 33 msec Tracker Association Update Fast Centroid Mirror Commands Threshold Each Frame Cluster Detection

19. LunarScan Processing Image Courtesy NASA/MSFC Sept 16, 2006 Optional register (PCM translation), Warp mean and s to current image Threshold Mean and standard deviation Triplet + Doublet cluster detector Update Exceedances

20. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Streak Detection – Matched FilterUses a “Track-before-Detect” approach • Remove Mean and Estimate 2nd Order Noise Statistics • Apply Covariance Inverse to Remove Clutter (Whitening) • Hypothesize Multiple Target Velocity Speeds and Directions • Shift Frames and Add for each hypothesis • Convolve with Smear Kernel Mean Removal Covariance Estimate Clutter Removal 1 Velocity Hypothesis Shift & Stack Threshold Detect Decluster / Culling . 2 . . . . . . 3 Multi-Frame Integration

21. Streak Detection – Orientation KernelSmall scale spatial-only convolution • Convolve 8 orientation kernels across focal plane • Detections are tested for temporal propagation • Shown are 5x5 binary kernels (MetRec) • Can be higher fidelity with width and fractional fill • Can use larger dimensions  more kernels • Can be formulated as a spatial matched filter

22. Streak Detection – Pixel ClusteringFind Groups of Pixels (Limited Spatial Extent, Track in Time) 1 0 1 1 Threshold Crossers Define Cell Size from Max Meteor Motion Per Frame Scale = 16 pixels / deg Max = 51 deg / sec 30 frames / sec Max  28 pixels / frame Cell = 32x32 pixels 3 1 3 0 1 S 1 2 1 0 1 2 5 1 1 0 Row Indices 1 4 8 1 3 Column Indices 1 2 1 1 1 Remove Singletons - Fill 32x32 Cells with Threshold Crossers Find Highest Peak Counts in 2 x 2 Cell Sums