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<p>Sensor networks are used throughout the government and industry for a wide variety of purposes. Mobile Sensor Platforms (MSPs), from surface combatant vessels to unmanned aerial vehicles, have been integrated into these sensor networks since their inception. Unmanned MSPs currently used in sensor networks have two major drawbacks: They are extremely expensive and they require the control of a human operator. Remote controlled unmanned systems currently do not eliminate risk to personnel entirely, because they are typically too expensive to be considered expendable. If these standard unmanned systems are downed in a hostile environment, their recovery is often attempted by personnel on the ground; thus, still risking human lives.  The military is exploring the use of low-cost unmanned MSPs to eliminate the need to risk personnel in their recovery. One of the greatest expenses in the life cycle of any system is operator cost. To reduce or eliminate operator cost, a platform must be autonomous. Though algorithms exist for adding autonomous capabilities to a mobile platform, such algorithms are typically designed for robust systems with a great deal of processing power. Low-cost systems are typically limited in capability by a low-processing power CPU. For this reason, small footprint alternatives to existing autonomous control algorithms must be developed to truly implement a low-cost MSP.  This thesis applies the systems engineering process to developing a generic system solution for the need of a low-cost MSP, with concept of operations, external systems diagram, generic requirements, functional architecture and decompositions developed. The proposed generic system solution is then further designed in a scoped environment and implemented as a proof of concept prototype.
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<br>Subjects: Systems engineering; Detectors</div>
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Tozzi, Michael Jay</div>
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