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Sniper Localization System Marko Gasic Sandeep Brar Ehsan Dallalzadeh Balraj Mattu

Sniper Localization System Marko Gasic Sandeep Brar Ehsan Dallalzadeh Balraj Mattu. Overview. Introduction Vision System Description Test Results Obstacles Encountered Project Finances Production Cost Conclusion Questions?. Introduction.

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Sniper Localization System Marko Gasic Sandeep Brar Ehsan Dallalzadeh Balraj Mattu

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  1. Sniper Localization System Marko Gasic Sandeep Brar Ehsan Dallalzadeh Balraj Mattu

  2. Overview • Introduction • Vision • System Description • Test Results • Obstacles Encountered • Project Finances • Production Cost • Conclusion • Questions?

  3. Introduction • Snipers are a serious threat in urban warfare environment. • Civilian threat in cases such as Washington DC sniper. • Snipers are very effective at harassing and impeding military operations. • AcousticShieldDesigns system enables identification of direction of origin of a sniper shot within seconds of the event.

  4. System Overview

  5. Vision • Existing Products • Above $15,000 US • Available only to elite military divisions and not standard equipment to regular units or police forces • Acoustic Shield System • System cost around $2000 • Low cost enables local police departments and regular military units to purchase system

  6. System Description • Functional Breakdown • Signal Acquisition • Gunshot Recognition • Delay Detection • 3-D Triangulation • Human-Machine Interface (H.M.I) • Principle of Operation • Sound waves reach 4 speakers at different times • Using these delays we can calculate the origin of sound

  7. Sound Acquisition • PC Hardware • M-Audio Delta 44 PCI audio card • 4/4 mono analog input/output channels • 24bit, 8kHz – 96kHz independent channel sampling • Winsound interface drivers

  8. Sound Acquisition • Microphones • Electret Omni-directional condenser microphones. • -45dB sensitivity • 20Hz – 16kHz Frequency Response • 60 dB S/N ratio

  9. Sound Acquisition • Microphone Preamplifier • Supplies minimum voltage required for microphone operation • Amplifies signal to 500mV swing, compatible for PC soundcard input.

  10. Sound Acquisition • Software Sample at 44kHz Continuously sample microphone inputs When sample exceeds 0.2V, record next 1.0 seconds and place in memory

  11. Time Domain Representation Recognition Algorithm • Understanding the characteristic of a gun shot

  12. Recognition Algorithm Frequency Domain Representation

  13. Average Power Bin1 average power Bin2 average power 11 Average Power 228 Hz (±150 Hz) 1 kHz – 1.5 kHz Recognition Algorithm • Algorithm is based on comparison of average power between two bins:

  14. Back Microphone Sound Wave Distortion in frequency spectrum is introduced Recognition Algorithm • Refinement after experimentation • Needed to consider all 4 input at the same time

  15. Recognition Algorithm • Simple Solution • Analyze all four microphones • Accuracy is demonstrated in Test Results section

  16. Δt Extraction • 4 similar signals, out of phase • Use Cross Correlation to determine phase difference Δt14 Δt13 Δt12

  17. 3-D Triangulation • Extrapolate origin of sound using the 3 Δt’s and speed of sound as input • Use Gauss-Newton method to solve 4 non linear equations • Recover the X Y and Z coordinates of signal origin • Normalize vector to give azimuth and elevation angles

  18. User Interface • Easy to Use/Navigate • Targeted towards Army Personnel • Displays Azimuth and Elevation • No installation Required

  19. Testing • The testing was done in 2 phases: • Testing for the detection in 2-D (X,Y) • Testing for detection of the elevation • Procedure A: • The system was setup • The software was running • Located the tripod at the center of a large circle • Drew a 2-D coordinate system about the center of the tripod • Marked the imaginary circle around the center of the tripod with points each about 30 degrees apart • Ran the sound sample of the gunshot twice at each point

  20. Testing • Recorded the Average, Trigger, X and Y values • Took a string from the sound source(speaker) to the center of the tripod • Chose a point on the string and recorded its X and Y components. • At the end, had pairs of vectors in 2-D • Comparison Stage…… • Wrote a C++ code to input each pair of vectors to calculate the angle between the actual vector and the result vector from the system in Degrees

  21. Observations • On average, the angle difference was about 2.78 Degrees • The accuracy was almost the same for all the points in the surrounding

  22. Testing cntd. • Procedure B (Elevation): • The system was setup • The software was running • Located the tripod at the center of a large circle • From points 90 Degrees apart, got samples • At each point, tried 3 different elevations: 1) above the center plane 2) at the same plane 3) below the center plane • Recorded the elevation that the program gave for each trial • For each point, measured the elevation angle compared to the center of the tripod (+ if above the center, (-) if below the center)

  23. Observations • On average, elevation difference was 3.15 Degrees • Functional Specifications stated maximum allowable error of 10 degrees

  24. Obstacles Encountered • Initially used Texas Instruments DSP • Insufficient inputs: unable to sample both stereo codecs simultaneously • Insufficient resolution: TMSC320 C6711 main audio codec samples at only 11kHz, we need a minimum of 44kHz • Extremely poor user interface and non-existent (yet advertised) compatibility with MATLAB

  25. Input Signal Power Spectrum of t2 – t3 Power Spectrum of t0 – t1 Obstacles Encountered • Initial Algorithm • Divide sampled input into smaller intervals • Analyze smaller intervals in frequency domain

  26. Known Spectrum Power Spectrum of t0 – t1 Obstacles Encounterd • Initial Algorithm • Determine if it’s gun shot or not by comparing with known spectrum Positive Match

  27. Recognition Subsystem 1 Main Recognition Block Obstacles Encountered • Algorithm was implemented in Matlab and Simulink

  28. Obstacle Encountered • Problems • Unable to achieve desired speed • Didn’t do well when tried with real input (instead of a wave file)

  29. Financial Aspects • Prototype Development Cost: • TMSC320 Daughter Board $120.00 • MATLAB RTW Documentation $ 35.00 • Microphones and Pre-Amps $ 60.00 • Miscellaneous Audio Cables $ 30.00 • M-Audio Delta44 $220.00 • Other $ 25.00 • TOTAL $490.00

  30. Budget Estimate • Initial cost estimate $2260.00 • Actual cost $490.00 • Significantly lower cost due to change in platform • Savings with no loss in performance • We were able to borrow the tripod, saving ~$100

  31. Manufacturing Costs • Assuming 50 units/month • Based on Digi-Key bulk pricing where available ITEM COST Microphone $ 1.20 Pre-Amp $ 6.00 Tripod $ 80.00 M-Audio Card $ 130.00 Cables $ 20.00 PC $ 600.00 Total $ 837.20

  32. Conclusion • Successfully Demonstrated Functional Concept • Demonstrated market value and ability to produce at reduced cost • Encountered problems and chose alternate solutions • Stayed within budget and timeline considerations

  33. Thank You Questions?

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