1. 1 Copyright © 2004 Vanderbilt University Sensor Network-Based Countersniper System Akos Ledeczi Senior Research Scientist Institute for Software Integrated Systems Vanderbilt University G. Simon, M. Maroti, A. Ledeczi, G. Balogh, B. Kusy, A. Nadas, G. Pap, J. Sallai, K. Frampton

2. 2 Copyright © 2004 Vanderbilt University Overview Ad-hoc wireless network of cheap acoustic sensors is used to accurately locate enemy shooters in urban terrain Performance: – Average 3D accuracy: ~1 meter – Latency: <2 seconds – Multipath elimination – Multiple simultaneous shot resolution Challenges: – Severely resource constrained nodes – Very limited communication bandwidth – Significant multipath effects in urban environment Funded by DARPA through the IXO NEST program

3. 3 Copyright © 2004 Vanderbilt University Technical Overview Muzzleblast Supersonic projectile Shockwave Base Station

4. 4 Copyright © 2004 Vanderbilt University Detect TOA of acoustic shockwave and muzzle blast MICA2 mote Proprietary acoustic sensor board: –3 acoustic channels (only a single channel is used in final system) –High-speed AD converters –FPGA for signal processing: shockwave and muzzle blast detection on board Timestamp of shockwave and/or muzzle blast sent to mote Motes send TOA data to base station Base station fuses data, estimates shooter position and displays result Middleware services: –Time synchronization –Message routing –Remote control Technical Approach

5. 5 Copyright © 2004 Vanderbilt University Software Architecture Sensorboard Time Sync Muzzle Blast & Shockwave Detector Remote Control Sensorboard Interface Sensorboard Config/ Monitor Stack Monitor Data Recorder Download Manager Acoustic Event Encoder Time Sync Message Routing User Interface Message Center Sensor Fusion Plotter Logger Sensor Location Remote Controller I2CI2CUART SENSORBOARD MICA2 MOTEBASE STATION

6. 6 Copyright © 2004 Vanderbilt University ZC coder τ 2 = n/a Mm 2 = 0 τ1τ1 L1L1 τ3τ3 Mm 1 L2L2 L3L3 Mm 3 T2T2 T1T1 T3T3 ADCZC Coder Shock wave detector Muzzle blast detector Board Clock I 2 C Interface time ZC Filter Detection

7. 7 Copyright © 2004 Vanderbilt University Flooding Time Synchronization Protocol (FTSP) Sender-receiver multi-hop time synchronization Integrated leader election, global time is synchronized to the local time of the leader End-to-end accuracy: average 1.6 μs per hop, maximum 6.1 μs per hop (experiment included simulated root failure) Constant network load: 1 msg per 30 seconds per mote Start up time: network diameter times 60 seconds Uses the Time Stamping module Topology change tolerant: motes can move at speeds less than 1 hop per 30 seconds. Available from the TinyOS CVS.

8. 8 Copyright © 2004 Vanderbilt University Directed Flood-Routing Framework (DFRF) app id “rank” packet 1packet 2packet n msg format: 3 bytes Flood Routing Engine: –Ad-hoc routing –Automatic aggregation –Implicit acknowledgments –Table/cache management –Very low overhead Flooding Policy: –Defines the meaning of “rank” –Controls the flooding and retransmission Application: –Can change the packet on the way –Can drop the packet on the way Data packet: –Fixed size length –Must contain unique part

9. 9 Copyright © 2004 Vanderbilt University RITS: Routing Integrated Time Synch Combination of Time Synchronization and Message Routing No extra messages Stealth operation Uses the Time Stamping module that has 1.4 μs average precision per hop No clock skew estimation Precision depends on the hop count of the route and on the total routing time Plug-in replacement for the Directed Flood Routing Framework (DFRF) node1 time node2 time node3 time root time T event Δt1Δt1 Δt2Δt2 Δt 1 + Δt 2 + Δt 3 T root T event = T root - Δt 1 - Δt 2 - Δt 3 Δt3Δt3

10. 10 Copyright © 2004 Vanderbilt University RITS Experimental Evaluation 50 Mica2 motes 10 x 5 grid, neighbor to neighbor comm is enforced in software Five simulated shots separated by 10 msec For each shot 13 motes send simultaneous detection events to root –simulates a shot event –triggered by a radio message in experiment Root at the edge of the network Experiment #1: normal routing: –1.5 hours long (2 tests/min) 4.4 μs average error 19.2 μs average maximum error 74 μs peak maximum error Experiment #2: data is delayed by 5 seconds at each hop: –8 hours long (2 tests/min) 28.5 μs average error 107.6 μs average maximum error 265 μs peak maximum error

11. 11 Copyright © 2004 Vanderbilt University time t2t2 t1t1 t4t4 t3t3 d1d1 f(x,y)f(x,y) ? d3d3 d4d4 d2d2 t 2 – d 2 /v t 3 – d 3 /v t 1 – d 1 /v t 4 – d 4 /v Shot #1 @ (x 1,y 1,T 1 ) Shot #2 @ (x 2,y 2,T 2 ) Echo #1 @ (x 3,y 3,T 1 ) f(x,y) = [max number of ticks in window] = 3 Shot time estimate T 3 0 1 sliding window Sensor Fusion

12. 12 Copyright © 2004 Vanderbilt University Sensor fusion cont’d. Advantages: –Groups together consistent sensor readings –Only uses correct detections for localization: high accuracy –Enables multiple simultaneous shot resolution Search algorithm: – Loop { Multiresolution search locates maximum If absolute time is close to a previously found peak, it is classified as an echo, otherwise a shot Contributing sensor readings are removed – } Continue Remarks: –Size of sliding window is determined by the estimated detection error due to, for example, sensor localization error –Only uses muzzleblast at this point. Shockwave is utilized after localization for trajectory estimation. –Performance is remarkable: separates simultaneous shots, differentiates between shooters in close proximity, can handle 10 shots per second or more (bottleneck is network bandwidth)

13. 13 Copyright © 2004 Vanderbilt University Experiments at McKenna MOUT site at Ft. Benning NORTH B1 Church  Sep 2003: Baseline system  Apr 2004: Multishot resolution  60 motes covered a 100x40m area  Network diameter: ~7 hops  Used blanks and Short Range Training Ammunition (SRTA)  Hundreds of shots fired from ~40 different locations  Single shooter, operating in semiautomatic and burst mode in 2003  Up to four shooters and up to 10 shots per second in 2004  M-16, M-4, no sniper rifle  Variety of shooter locations (bell tower, inside buildings/windows, behind mailbox, behind car, …) chosen to absorb acoustic energy, have limited line of sight on sensor networks  Hand placed motes on surveyed points (sensor localization accuracy: ~ 0.3m)

14. 14 Copyright © 2004 Vanderbilt University Results Based on 40 blank and SRTA shots from surveyed points Average 2D error: 0.57m Average 3D error: 0.98m

15. 15 Copyright © 2004 Vanderbilt University 2.5D Display, Single shot

16. 16 Copyright © 2004 Vanderbilt University 2.5D Display, Multiple Shots Red circle:  Shooter position White dot:  Sensor node Small blue dot:  Sensor Node that detected current shot Cyan circle:  Sensor Node whose data was used in localization Yellow Area:  Uncertainty

17. 17 Copyright © 2004 Vanderbilt University Future work http://www.isis.vanderbilt.edu/projects/nest New sensor fusion utilizing both muzzle blast and shockwave: –Increased range and accuracy –Silenced weapons New sensor board: –Low-power DSP –More sophisticated detection: increased range –Power saving modes Sensor self localization: –< 0.5m 3D accuracy needed Scaling up: –Hierarchical network architecture –Distributed sensor fusion