A Protocol for Tracking Mobile Targets using Sensor Networks H. Yang and B. Sikdar Department of Electrical, Computer and Systems Engineering Rensselaer.

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A Protocol for Tracking Mobile Targets using Sensor Networks H. Yang and B. Sikdar Department of Electrical, Computer and Systems Engineering Rensselaer Polytechnic Institute Troy, NY Sensor Network Protocols and Applications, 2003

Outline INTRODUCTION A DISTRIBUTED ALGORITHM FOR PREDICTIVE TRACKING Assumptions of the DPT Algorithm The Distributed Prediction Tracking Algorithm SIMULATION CONCLUSION

INTRODUCTION Scalable coordination and operation of a large scale sensor network Designed to track mobile targets a architecture for managing coordinating a sensor network Propose a distributed and scalable prediction based algorithm The Distributed Predictive Tracking algorithm

INTRODUCTION (CHALLENG) Scalable Coordination Tracking Accuracy Ad Hoc Deployability Computation and Communication Costs Power Constraints

A DISTRIBUTED ALGORITHM FOR PREDICTIVE TRACKING A cluster based architecture for the sensor network Ensure the sensor network's scalability and energy efficiency

Assumptions of the DPT Algorithm Cluster Head (CH) Sensor identity Location Energy level Each sensor has two sensing radii, normal beam r and high beam R Least 3 sensors to sense the target Targets originate outside the sensing region and then move inside

The Distributed Prediction Tracking Algorithm Cluster head 1 Cluster head 2 L1 (x i-1,Y i-1 ) L1 (x i, Y i ) L1 (x i+1, Y i+1 ) S1 S2 S3 Target’s Actual location Target’s track Predicted Track speed direction

The Distributed Prediction Tracking Algorithm Cluster head 1 Cluster head 2 L1 (x i-1,Y i-1 ) L1 (x i, Y i ) L1 (x i+1, Y i+1 ) S1 S2 S3 Target’s track Predicted Track r R

The Distributed Prediction Tracking Algorithm Cluster head 1 Cluster head 2 L1 (x i-1,Y i-1 ) L1 (x i, Y i ) L1 (x i+1, Y i+1 ) S1 S2 S3 Target’s track Predicted Track r Cluster head 3

The Distributed Prediction Tracking Algorithm Failure Recovery Doesn’t get any confirmation from the downstream cluster head after a given period of time predicted location error

Recovery level First level of recovery L1 (x i+1, Y i+1 ) S1 S2 S3 r R Cluster head Target’s Actual location

12 Recovery level Second Level S1 S2 S3 r All sensor activated in this circular area

Recovery level N th level S1 S2 S3 r

The Distributed Prediction Tracking Algorithm Energy Considerations Prediction Normal beam and higher beam

SIMULATION the target’s speed is 15m/s the normal/high sensing beam is 35/55m

SIMULATION

CONCLUSION We proposed a feasible solution for distributed tracking of mobile targets using sensor networks Essential idea is to predict the target's future location possible direction of work multiple targets simultaneously accommodate mobile sensors