Unmanned Aerial Systems (UAS) Payloads

Abstract

The Unmanned Aircraft Systems (UAS) Sensor Payload program provides the capability to develop, integrate, field, and sustain Intelligence, Surveillance, and Reconnaissance (ISR) and non-ISR payloads for the USMC Family of UAS. These payloads will alleviate Marine Corps ISR capability gaps caused by changes in mission, threats, and technologies and will increase the versatility of UAS in support of MAGTF mission accomplishment. In support of Force Design 2030 initiative, tactical UAS Reconnaissance, Survivability, and Target Acquisition (RSTA) is primarily focused on Marine Littoral Regiments (MLR) and on Marine Expeditionary Units (MEU) to enhance their ability to operate within an operating environment characterized by Great Power Competition. In support of the Commandant of the Marine Corps Planning Guidance and Force Design 2030 requirements, UAS sensor payloads provide modular, low-cost, aerial sensing technologies to achieve the Maritime Domain Awareness required by MLRs and MEUs in support of the Joint Forces Maritime Component Command (JFMCC). Within the context of Maritime Domain Operations, Marine forces executing Expeditionary Advanced Base Operations (EABO) require the organic capability to establish and maintain awareness of adversaries and potential adversary activities in communications and navigation degraded or denied environments. UAS Payloads enable sensing of threat indicators across the electromagnetic spectrum, gravimetric, chemical, nuclear, and acoustic spectrums and within the visual and physical domain and radar spectrum, with reduced signature, and minimized risk to personnel. The incorporation of advanced technology enablers such as artificial intelligence/machine learning (AI/ML) and precision geolocation provide automated recognition, identification, tracking, advanced networks, advanced communications, and cross-cueing in support of accelerated battlespace awareness and targeting. As an essential element of the kill chain, UAS payloads are critical to the JFMCC targeting process to find, fix, track, target, engage, and assess the effects of lethal and non-lethal fires. Employment of UAS payloads on platforms distributed across the MLRs and MEUs during EABO allows for greater distribution of forces while maintaining persistent awareness, enhances the security of tactical units and personnel moving across the battlespace, and enables the rapid transition between positions necessary for force survivability.

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Document Details

Document Type
R2 Budgetary Justification
Publication Date
Oct 01, 2024
Source ID
0305242M_7_1319_PB_2024
Change Summary Explanation
The increase of $3.225M from FY 2023 to FY 2024 is for efforts within the schedule associated with the Signals Intelligence (SIGINT)/Electronic Warfare Support (ES), Synthetic Aperture Radar (SAR)/Moving Target Indicator (MTI), Artificial Intelligence (AI)/Machine Learning (ML), Wide Area Maritime Target Detection and Classification (WAMTDC), SUAS Reusable Architecture (SRA)/Common Sensor Workstation (CSW), Acoustic Battlefield capabilities, and Government Engineering. There will be an increase in deficiency corrections and enhancements for the SIGINT/ES, SAR/MTI, AI/ML, and WAMTDC capabilities. SRA implementation will be conducted in 2 phases: payload capabilities vendor integration and platform integration.
Service Agency Name
Navy

Entities

Organizations

  • United States Navy

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Additive Manufacturing
  • Artificial Intelligence
  • Cross Domain
  • Data Management
  • Detection
  • Fabrication
  • Full Motion Video
  • Military Research
  • Navigation
  • Product Development
  • Signals Intelligence
  • Synthetic Aperture Radar
  • Systems Engineering
  • Target Detection
  • Test And Evaluation
  • Unmanned Aerial Systems
  • Unmanned Aerial Vehicles

Readers

  • Maritime Combat Support and Expeditionary Logistics.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - UAVs

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