Copyright © 2003-2004 Vanderbilt University Dr. Akos Ledeczi Institute for Software Integrated Systems Vanderbilt University Network Embedded Systems Technology.

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Copyright © Vanderbilt University Dr. Akos Ledeczi Institute for Software Integrated Systems Vanderbilt University Network Embedded Systems Technology (NEST) Shooter Localization McKenna MOUT Site DBBL, Fort Benning Sep 4,

Copyright © Vanderbilt University 2 Outline  Overview  What You Will See Today  Technical Approach  Performance  Caveats/Future Plans

Copyright © Vanderbilt University 3 Overview  Ad-hoc wireless network of cheap acoustic sensors is used to accurately locate enemy shooters: Nodes detect shockwave and muzzle blast Nodes send back their data to the base station Base station determines shooter location  Performance: Average accuracy: 1 meter Latency: 2 seconds  Challenges overcome: 7-month research and development time Severely resource constrained cheap nodes Very limited communication bandwidth Bad multipath effects in urban environment  CONOPS support: Fast and accurate enemy shooter localization is key in reducing friendly casualties and neutralizing enemy combatants

Copyright © Vanderbilt University 4 What You Will See Today: 2D Display

Copyright © Vanderbilt University 5 What You Will See Today: 3D Display Red globe:  Shooter position Light blue sphere:  Sensor node (good measurement) Dark blue sphere:  Sensor node (no or unused measurement) Looking south down Main street

Copyright © Vanderbilt University 6 Additional Camera Angles Looking south at building B1Looking east at building B4

Copyright © Vanderbilt University 7  Detect TOA of acoustic shockwave and muzzle blast  MICA2 mote (UC Berkeley and Crossbow Inc.): Atmel 8MHz microcontroller 4KB data memory Chipcon radio  Acoustic sensor board (Vanderbilt): 3 acoustic channels High-speed AD converters FPGA for signal processing: shockwave and muzzle blast detection on board I2C interface to mote 2 AA batteries  Timestamp of shockwave and/or muzzle blast sent to mote  Motes send data to base station  Base station fuses data, estimates shooter position and displays result  Middleware services: Time synchronization Message routing Technical Approach

Copyright © Vanderbilt University 8 Time Synchronization  Requirements: Sound travels one foot per millisecond Time synch error in the whole network should be less than 1 msec  Algorithm: Each mote maintains a separate local and global time Simple integrated leader election Leader broadcasts its time and a sequence number Message is time stamped in the radio stack Receivers update their global time and rebroadcast it If message arrives with known sequence number, it is discarded Motes keep last ten local and global time pairs and perform linear regression If leader is lost, new leader is elected  Performance: +/- 60 microseconds error per hop One timesynch round per minute (i.e. one msg per min per mote)

Copyright © Vanderbilt University 9 Message Routing  Requirements: Acoustic event triggers many motes at once All need to get their data to base station with low latency Mote bandwidth: messages per second  Directed Flood Routing Framework Ad-hoc routing Automatic aggregation Implicit acknowledgments Configurable flooding policy: defines gradient controls retransmission Converge cast to root  Performance:  When max distance from root is 5, base station receives ~15 measurements in the first second

Copyright © Vanderbilt University 10 t 1 -vd 1 t 2 -vd 2 t 3 -vd 3 t 4 -vd 4 time f(x,y) = 1 / #datapoints in window t2t2 t1t1 t4t4 t3t3 ? d1d1 d2d2 d3d3 d4d4 f(x,y) Sensor fusion outlier

Copyright © Vanderbilt University 11 Sensor fusion  Muzzle blast: three dimensional utility function (x,y,z)  Shockwave adds three more (azimuth, elevation, bullet speed)  Multi-resolution search to find minimum  Utilizes all data, does it incrementally as data becomes available  Provides estimate, overall error and individual measurement error  Discards outliers  Multipath effect:  Direct line-of-sight motes get real data first  Attenuated signals not recognized as shockwave and/or muzzle blast  Sensor fusion discards outliers:  Simple geometric filtering  Utility function

Copyright © Vanderbilt University 12 Performance  Latency: 2 seconds  Accuracy in 2D: 0.64 meter  Results below based on 71 SRTA shots from 20 different positions error in meters number of shots Histogram of (x,y) error

Copyright © Vanderbilt University 13 Performance error in meters number of shots Histogram of (x,y,z) error  Accuracy in 3D: 1.5 meter  Results below based on 71 SRTA shots from 20 different positions

Copyright © Vanderbilt University 14 Caveats/Future Plans Caveats  #1 Multiple shots: currently 0.4 second separation is required between shots  #2 Deployment: current hardware is not weather-proof or shock-proof  #3 Silenced weapon or distant shooter: muzzle blast not detected  #4 Power usage: currently no power management  #5 Scalability: current system scales to ~200 nodes Future Plans  #1 Detection should discriminate between different weapons. More intelligent sensor fusion algorithm.  #2 New sensor board and packaging needed.  #3 Better shockwave detection and sensor fusion  #4 Power management is needed. Sentry service is needed.  #5 Hierarchical network arrangement is needed