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An Empirical Study of Collaborative Acoustic Source Localization

An Empirical Study of Collaborative Acoustic Source Localization Andreas M. Ali Kung Yao EE, UCLA Travis Collier Charles E. Taylor Daniel T. Blumstein Ecol. and Evolutionary Biology, UCLA Lewis Girod CSAIL MIT Contribution

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An Empirical Study of Collaborative Acoustic Source Localization

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  1. An Empirical Study of Collaborative Acoustic Source Localization Andreas M. Ali Kung Yao EE, UCLA Travis Collier Charles E. Taylor Daniel T. Blumstein Ecol. and Evolutionary Biology, UCLA Lewis Girod CSAIL MIT

  2. Contribution • Online marmot detector based on Constant False Alarm Rate (CFAR) • A centralized marmot call localization system based on Approximate-ML (AML) bearing likelihood estimation • A field study on real animals in natural habitat Yellow Bellied Marmot Rocky Mountain Biological Lab (RMBL)

  3. Outline • Motivation to study Marmot alarm calls • Acoustic ENS Box Platform and Methods • Analysis and Results • Summary

  4. Motivation for Using Marmot Alarm Calls Rocky Mountain Colorado Lab (RMBL) • Biologically important • Infrequent • Difficult to observe • 30% identified by observation Marmot at RMBL

  5. Acoustic ENS Box Platform Acoustic ENSBox V1 (2004-2005) • Wireless distributed system • Self-contained • Self-managing • Self-localization • Processors • Microphone array • Omni directional speaker V2 (2007)

  6. DOA Based Localization System CFAR • Constant False Alarm Rate (CFAR) based event detection • Combine AML Direction of Arrival (DOA) likelihood estimate to produce the source location estimate J1 JN J2

  7. Satellite Picture of Wide Deployment • Rocky Mountain Biological Laboratory (RMBL), Colorado • 6 Sub-arrays • Burrow near Spruce • Wide deployment • Max range ~ 140 m • Compaq deployment • Max range ~ 50 m

  8. CFAR Detector Performance

  9. Source Directionality Test

  10. Aligning Node Position with GPS Coordinate • Compact Deployment • GPS (red) • Self-Loc (blue)

  11. Pseudo Log-likelihood Map • Compaq deployment • location estimate • spruce location • Normalized beam pattern • Collective result mitigate individual sub-array ambiguities • Marmot observed near Spruce

  12. Aligning Node Position with GPS Coordinate • Wide Deployment • GPS (red) • Self-Loc (blue)

  13. Location Estimates Scatter Plot for Wide Deployment Meter Meter Meter Meter 6 sub-arrays 4 sub-arrays

  14. Summary • Non-intrusive acoustic source localization is practical and tractable • Self-localization and synchronization feature of Acoustic ENS Box is essential for practical field deployment • Combining multiple AML based DOA likelihoods from multiple nodes effectively overcomes ambiguity individual node suffers • Redundancy can be used to identify and exclude sub-arrays which have especially poor data due to reverberations, multi-path, or other practically unavoidable problems.

  15. Yellow Bellied Marmot Thank you!

  16. Generate Pseudo Log-likelihood Map from AML Meters Meters • From a position, sum all the log-likelihood values of the bearing estimates • Beam crossing

  17. Deployment & Collection Method Node n Self-loc • Self-localization stage • Acoustic ENS Box • Detection/recording stage • Each node: • Runs CFAR event detector • Silent recording • Each node estimate bearing via AML (can be run in fusion center) • Fusion center:Generate a Pseudo Likelihood map to estimate source location • Deployment size (Compaq or Wide) Store Event? CFAR event detector AML Yes No Fusion center Pseudo Log-likelihood Estimate

  18. Performance Impact on Sub-array Size

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