The use of seismic waves to detect subsurface targets such aslandmines is a very promising technology compared to existingmethods like Ground Penetrating Radar (GPR) and ElectromagneticInduction (EMI) sensing. The fact that seismic waves induceresonance in man-made targets, and hence more scattering, gives thismethod a natural ability to discriminate landmines from common typesof clutter like rocks, wood, etc. Reflection and resonance from thetargets can be used in imaging to detect the location of targets.However, existing methods require a large number of measurements forimaging and detection, which are expensive and time consuming. Toreduce the number of measurements and enable faster detections, anew sensing strategy is proposed based on optimally maneuveringsensors. The system would operate in two main modes. In search mode,the goal would be to move on top of a target using the minimumnumber of measurements. Once the target is found, the system wouldswitch to a detection mode to make its final decision. The seismicsensor system is an active system, where a seismic source generatesthe probing pulse. The waves reflected from buried targets arecollected by an array of sensors placed on the surface, and then animaging algorithm is used to estimate the target position. Theperformance bounds for this position estimate are derived in termsof the Fisher information matrix (FIM). This matrix gives thedependence of the target position estimate on the array position.Based on the FIM, the next optimal array position is determined byusing the theory of optimal experiments. The next array positionwill be the one that reduces the uncertainty of the target positionestimate the most. The whole array is moved to this new position,where the same steps are repeated. In this way, the target can belocalized in a few iterations.
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Localization of Subsurface Targets using Optimal Maneuvers of Seismic Sensors
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