Approved for public release; distribution is unlimited. / The U.S. Army's Future Force is being developed as a faster, lighter, more rapidly deployable alternative to the current force structure. The Future Force will feature a smaller in-theater footprint and require the ability to cover a larger area of the battle space with intelligence-gathering assets. To support this development the Naval Postgraduate School and TRAC Monterey began to conduct research in the area of allocation of Future Force sensor platforms. A previous thesis developed the Sensor Allocation Model (SAM) for finding an appropriate mix and allocation strategy for organic Unit of Action sensors in a given threat scenario. The mix suggested by the model is robust to uncertainties in sensor performance and target quantity and location. SAM shows great promise for use as a screening tool in support of analysis of alternatives studies as well as in support of Army and Joint war fighting experimentation. It also has potential for use as an operational decision support tool for unit commanders. This thesis discusses three improvements to SAM. First, SAM has been translated into a programming language that easily can be implemented into any simulation environment. Second, it now contains more realistic constraints on sensor platform employment duration and distance. Third, the model estimates of sensor performance have been improved with a Probability Line of Sight model. Together, these improvements have greatly improved SAM's usability. / Captain, German Army
| Identifer | oai:union.ndltd.org:nps.edu/oai:calhoun.nps.edu:10945/1163 |
| Date | 06 1900 |
| Creators | Doll, Thomas M. |
| Contributors | Carlyle, Matthew, Phillips, Donovan, Naval Postgraduate School (U.S.)., Operations Research |
| Publisher | Monterey, California. Naval Postgraduate School |
| Source Sets | Naval Postgraduate School |
| Detected Language | English |
| Type | Thesis |
| Format | xvi, 71 p. : col. maps ;, application/pdf |
| Rights | Copyright is reserved by the copyright owner. |
Page generated in 0.0024 seconds