Multi-Axis Protection of Surface Ships
Abstract
The anti-ship cruise missile (ASCM) is a growing asymmetric threat to U.S. naval combatants, force projection, and defense of the sea lanes of communications missions. Threat ASCM capabilities and lethality are rapidly improving with extended range, higher speeds, and advancing sophistication in navigation and targeting subsystems. In addition, these weapon systems are being proliferated in greater numbers to adversarial nations with options for submarine deployment. Submarine-launched ASCMs pose an even greater challenge to our Anti-Submarine Warfare (ASW) systems as they expand search area requirement proportional to the square of the cruise missile range. The Multi-Axis Protection of Surface Ships program intends to reverse the asymmetric advantage of these threats through the development of advanced offboard sensing from unmanned systems. These multi-spectral mobile and autonomous sensor systems will operate at significant offboard ranges from maritime battle groups to provide tactically significant early warning of cruise missile attacks. The effort is focused on achieving new detection modalities with sufficient low power, weight, and size (SWaP), to enable unmanned vessel implementations. Initial efforts will focus on identifying the best detection methods and sensor modalities leveraged from state-of-the-art sensors and new physical and operational insights. Provided compelling detection capability is achievable, prototype systems will evolve through at-sea testing and sensor integration. The program seeks to further explore ASW and networked maritime system concepts explored within PE 0603766E, Project NET-02, and PE 0602702E, Project TT-03, to develop breakthrough technology for long-range detection and classification, communications, energy management, sensor and platform integration, and robust autonomous processing and control for distributed sensing platforms. This program will transition to the Navy.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2016
- Source ID
- b766d862f691046f44a89128fd29ffad