Integrating Developments from Industry for Robust Acoustic Intelligence
The MOC
By
LCDR John Falcone
November 21, 2023
Proper preparation for maritime conflict demands an intimate familiarity with the undersea environment and the assets an adversary may employ there. As such, the U.S. Navy prioritizes opportunities to collect underwater survey and acoustic data. In late 2016, the destroyer I served aboard received such prioritized tasking when satellite imagery revealed a high-interest submarine had left its homeport. This submarine’s acoustic properties were, to date, unrecorded. So, although we were more than a thousand miles away, we were tasked as the nearest asset equipped to find and track this submarine.
Given the mission’s significance, we embarked two Acoustic Intelligence specialists to support our sonar operators and provide immediate analytic expertise. Timely recognition and analysis would be critical. Once underway, our ship would have less than ten days – limited by our fuel supply – to intercept our target and collect data. The objective was to identify and record both discrete frequencies and bandwidths (characteristics of waterborne noise) generated by internal machinery, propellers, and sonar systems that would lead to acoustic intelligence (“ACINT”). This ACINT would enable detection and classification of similar submarines in the future.
This vignette highlights three present-day challenges to generating ACINT. First, a limited number of assets are relied upon to collect the raw acoustic data that becomes intelligence. Second, these platforms have shorter on-station times relative to the vessels they are assigned to track. And third, the lag between data collection and analysis undermines timely recognition of operationally significant information.
Today, the dual-use and defense technology sectors are combatting analogous challenges for the private sector. If properly applied to the naval context, these innovations have disruptive potential. First, solutions in industry are built to scale with demand. Second, much of the hardware employed are small, unmanned systems that have demonstrated high-endurance at sea. Finally, advancements in cloud computing and the application of machine learning systems have enabled real-time analysis and access to usable data. Integrating these features would improve the Navy’s ability to collect acoustic data in competition and conflict; however, responsible development requires pursuing these technologies through both traditional acquisition methods in addition to defense technology companies.
Improving the System of Systems to Capture Acoustic Data
Today, ACINT databases contain high quality acoustic data, but collection relied on exquisite systems onboard high-value assets. The Navy’s current inventory of ACINT assets includes seabed sensors, SURTASS ships, destroyers, maritime patrol craft, and attack submarines. This large-asset dependent model has a relatively fixed capacity. At the same time, our adversaries’ threat inventory is increasing in capability and quantity. Given these dynamics, the next evolution of ACINT capabilities must maintain widespread geographic coverage while remaining connected to the larger force to meet the rising challenge from submarine and autonomous underwater vehicle (“AUV”) proliferation.
Historically, the Navy has relied upon university-affiliated research centers (“UARCs”) to lead the development of next-generation ACINT capabilities. UARCs such as Johns Hopkins University Applied Physics Lab and Applied Research Laboratories, The University of Texas at Austin are leaders in this space. Unlike many other groups in the defense sphere, these centers have the agility and authority to implement solutions that address both demands and concerns from the fleet. Although the technical improvements from these centers are valuable, their impact is limited by the platforms they support. In other words, UARCs are, in general, condemned to trying to make a faster horse while defense tech ventures are building the car.
The growing blue economy (industries such as commercial shipping and offshore energy production) has created a demand for products and services that monitor disruptions at or below the ocean’s surface. To meet this opportunity, innovators have developed a variety of unmanned systems to collect and process raw data into valuable information for clients. By introducing collection capabilities that are low-cost and flexible, industry is producing the means to increase capacity, accelerate analysis, and provide real-time access to intelligence.
Features of Industry Solutions
Critically, the acoustic sensor systems that serve private industry can scale to meet dynamic end user requirements or changes in the operating environment. This scale is achieved by a variety of methods such as employing AUVs with onboard data processing, supporting diverse communication paths, or ensuring ease of deployment. In crisis or conflict, the Navy’s demand for acoustic data and intelligence will increase. Presently, however, if conflict operations demanded more ACINT, there would be a simultaneous drop in available assets as multi-mission platforms are likely tasked elsewhere. Even in peacetime, scalable solutions would offer greater coverage in a time when the Navy’s ship count remains nearly fixed while adversaries grow and increase the operational tempo of their submarine and AUV fleets. Scalable solutions, of which current ACINT capabilities lacks, offer the ability to increase capacity at a moment’s notice.
Second, industry solutions demand high endurance systems due to the high financial and environmental cost of manning vessels for work at-sea. Many of the unmanned systems available advertise at-sea endurance from multiple weeks to ninety days. These on-station times contribute to scalability while driving down the overall cost of data acquisition. In contrast, legacy naval platforms are limited by logistical constraints such as fuel and food. The takeaway is that for unmanned systems, the cost of each unit of coverage decreases as on-station time increases; meanwhile, the marginal cost of coverage increases with on-station time for legacy platforms. These economic burdens are in addition to the opportunity costs borne by employing a highly trained manned platform as a forward sensor.
Finally, whether in the commercial or naval application, acoustic data and intelligence is the product of laborious collection processes. From personal experience, collection of acoustic data onboard to receipt by competent analysts can take weeks with timelines hindered by simple logistics such as mailing off physical data records. These current processes cause time-delays. And while this is frustrating in today’s competitive environment, it can cost lives in conflict. Unmanned systems with the onboard capacity to run machine learning systems and communicate with cloud servers offer the potential for real-time analysis and dissemination to all network users. The result is that raw data transitions to intelligence in hours (or less), rather than weeks.
Need for Parallel Development
Although these features highlight the potential of industry solutions, solely relying upon these ventures to deliver the next-generation of ACINT technologies carries risks. Early stage start-ups face both technical and business challenges. While industry’s solutions demonstrate high-endurance and the ability to process ocean data in benign environments, ACINT systems will be required to perform in anti-access and communications denied environments. If procurement decisions overselect these emerging systems, the ACINT mission area could become exposed to concentration risk due to their unknown resiliency to physical and cyber threats.
From a business operations perspective, acoustic intelligence is likely not a sustainable, standalone business for an early-stage company. In economic downturns industry partners may be forced to close their secondary service lines (or the company altogether) if it is not financially viable. This could potentially leave the Navy without manufacturer parts or technical support.
Taken together, the technical and business risks associated with industry solutions indicate the need for traditional paths to continue to develop ACINT capabilities. Research centers, such as the UARCs, must still iterate and develop systems that enable legacy, manned platforms to increase the quality and quantity of data it collects. They must also work to improve data collection and analysis processes. Progress in these areas is independent of the platforms that these system suites serve and benefit all operators that collect and use ACINT.
Industry has demonstrated that scalability, endurance, and real-time data processing and dissemination must be bedrock characteristics of future ACINT system of systems. The outstanding challenge for the Navy is to identify and promote the right mix of legacy and industry development.
LCDR John Falcone is an active-duty Surface Warfare Officer, serving as Chief Engineer onboard a forward-deployed littoral combat ship. LCDR Falcone was awarded the 2022 Alfred Thayer Mahan Literary Award by the Navy League of the United States and is a graduate of the Princeton School of Public and International Affairs and Yale University.He can be found on LinkedIn.The author’s opinion is his own, and do not reflect the official stance of the Department of the Navy or Department of Defense.
The views expressed in this piece are the sole opinions of the author and do not necessarily reflect those of the Center for Maritime Strategy or other institutions listed.
Center for Maritime Strategy
By LCDR John Falcone
Proper preparation for maritime conflict demands an intimate familiarity with the undersea environment and the assets an adversary may employ there. As such, the U.S. Navy prioritizes opportunities to collect underwater survey and acoustic data. In late 2016, the destroyer I served aboard received such prioritized tasking when satellite imagery revealed a high-interest submarine had left its homeport. This submarine’s acoustic properties were, to date, unrecorded. So, although we were more than a thousand miles away, we were tasked as the nearest asset equipped to find and track this submarine.
Given the mission’s significance, we embarked two Acoustic Intelligence specialists to support our sonar operators and provide immediate analytic expertise. Timely recognition and analysis would be critical. Once underway, our ship would have less than ten days – limited by our fuel supply – to intercept our target and collect data. The objective was to identify and record both discrete frequencies and bandwidths (characteristics of waterborne noise) generated by internal machinery, propellers, and sonar systems that would lead to acoustic intelligence (“ACINT”). This ACINT would enable detection and classification of similar submarines in the future.
This vignette highlights three present-day challenges to generating ACINT. First, a limited number of assets are relied upon to collect the raw acoustic data that becomes intelligence. Second, these platforms have shorter on-station times relative to the vessels they are assigned to track. And third, the lag between data collection and analysis undermines timely recognition of operationally significant information.
Today, the dual-use and defense technology sectors are combatting analogous challenges for the private sector. If properly applied to the naval context, these innovations have disruptive potential. First, solutions in industry are built to scale with demand. Second, much of the hardware employed are small, unmanned systems that have demonstrated high-endurance at sea. Finally, advancements in cloud computing and the application of machine learning systems have enabled real-time analysis and access to usable data. Integrating these features would improve the Navy’s ability to collect acoustic data in competition and conflict; however, responsible development requires pursuing these technologies through both traditional acquisition methods in addition to defense technology companies.
Improving the System of Systems to Capture Acoustic Data
Today, ACINT databases contain high quality acoustic data, but collection relied on exquisite systems onboard high-value assets. The Navy’s current inventory of ACINT assets includes seabed sensors, SURTASS ships, destroyers, maritime patrol craft, and attack submarines. This large-asset dependent model has a relatively fixed capacity. At the same time, our adversaries’ threat inventory is increasing in capability and quantity. Given these dynamics, the next evolution of ACINT capabilities must maintain widespread geographic coverage while remaining connected to the larger force to meet the rising challenge from submarine and autonomous underwater vehicle (“AUV”) proliferation.
Historically, the Navy has relied upon university-affiliated research centers (“UARCs”) to lead the development of next-generation ACINT capabilities. UARCs such as Johns Hopkins University Applied Physics Lab and Applied Research Laboratories, The University of Texas at Austin are leaders in this space. Unlike many other groups in the defense sphere, these centers have the agility and authority to implement solutions that address both demands and concerns from the fleet. Although the technical improvements from these centers are valuable, their impact is limited by the platforms they support. In other words, UARCs are, in general, condemned to trying to make a faster horse while defense tech ventures are building the car.
The growing blue economy (industries such as commercial shipping and offshore energy production) has created a demand for products and services that monitor disruptions at or below the ocean’s surface. To meet this opportunity, innovators have developed a variety of unmanned systems to collect and process raw data into valuable information for clients. By introducing collection capabilities that are low-cost and flexible, industry is producing the means to increase capacity, accelerate analysis, and provide real-time access to intelligence.
Features of Industry Solutions
Critically, the acoustic sensor systems that serve private industry can scale to meet dynamic end user requirements or changes in the operating environment. This scale is achieved by a variety of methods such as employing AUVs with onboard data processing, supporting diverse communication paths, or ensuring ease of deployment. In crisis or conflict, the Navy’s demand for acoustic data and intelligence will increase. Presently, however, if conflict operations demanded more ACINT, there would be a simultaneous drop in available assets as multi-mission platforms are likely tasked elsewhere. Even in peacetime, scalable solutions would offer greater coverage in a time when the Navy’s ship count remains nearly fixed while adversaries grow and increase the operational tempo of their submarine and AUV fleets. Scalable solutions, of which current ACINT capabilities lacks, offer the ability to increase capacity at a moment’s notice.
Second, industry solutions demand high endurance systems due to the high financial and environmental cost of manning vessels for work at-sea. Many of the unmanned systems available advertise at-sea endurance from multiple weeks to ninety days. These on-station times contribute to scalability while driving down the overall cost of data acquisition. In contrast, legacy naval platforms are limited by logistical constraints such as fuel and food. The takeaway is that for unmanned systems, the cost of each unit of coverage decreases as on-station time increases; meanwhile, the marginal cost of coverage increases with on-station time for legacy platforms. These economic burdens are in addition to the opportunity costs borne by employing a highly trained manned platform as a forward sensor.
Finally, whether in the commercial or naval application, acoustic data and intelligence is the product of laborious collection processes. From personal experience, collection of acoustic data onboard to receipt by competent analysts can take weeks with timelines hindered by simple logistics such as mailing off physical data records. These current processes cause time-delays. And while this is frustrating in today’s competitive environment, it can cost lives in conflict. Unmanned systems with the onboard capacity to run machine learning systems and communicate with cloud servers offer the potential for real-time analysis and dissemination to all network users. The result is that raw data transitions to intelligence in hours (or less), rather than weeks.
Need for Parallel Development
Although these features highlight the potential of industry solutions, solely relying upon these ventures to deliver the next-generation of ACINT technologies carries risks. Early stage start-ups face both technical and business challenges. While industry’s solutions demonstrate high-endurance and the ability to process ocean data in benign environments, ACINT systems will be required to perform in anti-access and communications denied environments. If procurement decisions overselect these emerging systems, the ACINT mission area could become exposed to concentration risk due to their unknown resiliency to physical and cyber threats.
From a business operations perspective, acoustic intelligence is likely not a sustainable, standalone business for an early-stage company. In economic downturns industry partners may be forced to close their secondary service lines (or the company altogether) if it is not financially viable. This could potentially leave the Navy without manufacturer parts or technical support.
Taken together, the technical and business risks associated with industry solutions indicate the need for traditional paths to continue to develop ACINT capabilities. Research centers, such as the UARCs, must still iterate and develop systems that enable legacy, manned platforms to increase the quality and quantity of data it collects. They must also work to improve data collection and analysis processes. Progress in these areas is independent of the platforms that these system suites serve and benefit all operators that collect and use ACINT.
Industry has demonstrated that scalability, endurance, and real-time data processing and dissemination must be bedrock characteristics of future ACINT system of systems. The outstanding challenge for the Navy is to identify and promote the right mix of legacy and industry development.
LCDR John Falcone is an active-duty Surface Warfare Officer, serving as Chief Engineer onboard a forward-deployed littoral combat ship. LCDR Falcone was awarded the 2022 Alfred Thayer Mahan Literary Award by the Navy League of the United States and is a graduate of the Princeton School of Public and International Affairs and Yale University. He can be found on LinkedIn. The author’s opinion is his own, and do not reflect the official stance of the Department of the Navy or Department of Defense.
The views expressed in this piece are the sole opinions of the author and do not necessarily reflect those of the Center for Maritime Strategy or other institutions listed.