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OPTIMIZING VLS FIRING POLICY: AN ENUMERATION OF HETEROGENEOUS SEQUENCES TO INFORM EXPENDITURE
- Publication Year :
- 2021
- Publisher :
- Monterey, CA; Naval Postgraduate School, 2021.
-
Abstract
- The U.S. Navy (USN) utilizes the Vertical Launch System (VLS) to store and launch both their offensive and defensive missiles. Since the number of VLS silos on a given ship is fixed, to maximize offensive capability the USN needs to minimize the number of interceptors required to combat incoming anti-surface missiles. Current firing policies may be overly conservative and expend too many interceptors per incoming threat, which results in a substantial fraction of VLS silos dedicated to defensive missiles. Decision makers need an analysis tool to explore the trade-off between missile consumption and probability of raid annihilation (PRA) for various firing policies and would also benefit from a prescriptive algorithm to help inform missile expenditure. This thesis provides a model to optimize VLS firing policy using a set of multiple interceptor types while accounting for range limitations, travel time, multi-interceptor salvos, battle damage assessment, and range dependent probability of kill. Additionally, the thesis derives analytical results for the optimal, lowest-cost allocation of interceptors in the single interceptor case, which, in turn, generates insight into how to structure sequential salvos. N81, Washington DC Ensign, United States Navy Approved for public release. Distribution is unlimited.
- Subjects :
- Vertical Launch System
pk
probability of raid annihilation
ship
SSLSS
probability of engagement kill
IAMD
integrated air and missile defense
VLS
BMD
SLS
ASCM
mix
distributed maritime operations
interceptor
DMO
loadout
salvo
battle damage assessment
expenditure
counterfire
low cost
PEK
PIP
missile
defense
probable impact point
BDA
PRA
anti-ship cruise missile
range
hard kill
SLSS
shoot look shoot
optimization
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.od......2778..d7ad39b081c44660f98ddd5644bc951d