Bento Box—Modular/Recoverable Stratospheric Balloon Capabilities to Support Distributed Maritime Operations

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Authors
Lan, Wenschel
Subjects
high-altitude balloons
near-space platforms
distributed maritime operations,
DMO
mosaic warfare
tactical maneuvers
contested environment
Advisors
Date of Issue
2022-10-19
Date
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
In investigating the use of a modular near-space system for Distributed Maritime Operations (DMO), a notional concept of operations (CONOP) was developed to demonstrate the feasibility of a future system that can be used by Naval Special Warfare (NSW) to maximize the breadth of its resources and provide cross-platform data. This CONOP focused on a satellite communications (SATCOM)-denied environment in the Arctic, which showed that it is feasible for a high-altitude balloon (HAB) system to provide persistent overwatch and electronic reconnaissance (POWER) capabilities when existing commercial stratospheric systems are leveraged and incorporated into the mission architecture. Additionally, the reliability and robustness of this system, named the Bento Box, survived environmental testing. An ADALM-Pluto software-defined radio (SDR) was integrated with the Bento Box for this portion of the study as a bounding case for commercial-offthe-shelf (COTS) equipment that can withstand the Arctic environment. End-to-end system testing between the integrated HAB system and two PRC-152 ground user radios in a simulated ground test environment serves as a proof of concept for mesh networks with low-cost COTS equipment that are expendable but easily sustainable within a DMO construct (Williams, 2022). Investigation of machine learning (ML) algorithms to improve overall geolocation accuracy revealed that math-based geolocation processing continues to be more accurate than ML-derived accuracy. Specifically, for maintaining positional accuracy for targets that are no longer emitting an RF signal, Kalman filtering with a chi-squared statistical anomaly detector can accurately estimate the target location. Future efforts may include exploring the use of ML during signal processing.
Type
Report
Description
NPS NRP Executive Summary
Department
Identifiers
NPS Report Number
Sponsors
Naval Special Warfare Command (NAVSPECWARCOM)
N7 - Warfighting Development
Funder
This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098).
Format
Citation
Distribution Statement
Approved for public release. Distribution is unlimited. 
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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