This PDF file contains the front matter associated with SPIE Proceedings Volume 11015, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

Ionospheric conditions are variable in nature and can cause destructive interference to transmissions made in the High Frequency (HF) band, which ranges from 3-30 MHz. This poses a problem as the HF band is a critical fre- quency range for various applications (i.e. emergency, military). To manage these dynamic conditions, intelligent techniques should be implemented at the transmitter and receiver to properly maintain reliable communications. In this paper, we present work deriving components of a cognitive HF transceiver with agents called cognitive engines (CEs) operating at the transmitter and receiver. At the transmitter, cognition is employed to determine the combination of modulation and coding techniques that maximize throughput. At the receiver, cognition is implemented to derive the best parameters for equalization (i.e. tap length, step size, filter type, etc.) Results are presented showing that the individual components are able to satisfy their objectives. A discussion is also provided surveying recent research efforts pertaining to the development of cognitive methods for the Automatic Link Establishment (ALE) protocol, a common networking methodology for HF stations.

Nowadays, ever larger amounts of data are being generated, processed and linked. This enables to share data with other people or communities and to work collaboratively and evaluate data. Depending on the use case, environment and domain there are different aspects to consider regarding data security, availability, data protection etc. In the military environment, a concept and derived specifications for data distribution were standardized as STANAG 4559 and are already used operationally. The advantages of such a solution can also be of interest for other domains with similar needs. A possible use case is in the context of research data. Especially in areas where huge amounts of data with specific features are needed, it is often difficult to access (enough) research data and as a result, the outcome of the research is of limited quality. As every research institution creates its own data it would be helpful to have a possibility to share data and information amongst each other in a standardized way. The possibility of the aggregation from individual authorities results in a joint data pool. The research based on such a data pool can be more (cost) efficient, the quality increases due to the broader data sets and aspects like anomaly detection could be enforced. We present an idea of a concept to use a military data distribution standard for civil applications by defining data model extensions and considering security aspects and obstacles that may occur from various aspects such as the military characteristic and inflexibility of the standard and the data model.

This paper describes an architecture intended to support all-optical signaling and routing to and through spacecraft. The approach is based on a dense wavelength division multiplexing (DWDM) router, transceivers, and internal optoelectronic translators that support the interface of high-performance sensors and processing arrays. Key to this approach is the novelty of an optical middle box (OMB) scheme. Each OMB contains a number of optical ports, electrical ports, and reconfigurable optical transmitter and receiver elements. Laser communications transceivers interface to the optical router and support dynamic reconfiguration. A basic interoperability protocol (BIP) defines a type of "optical dial tone" through which metadata is relayed to provide communications management cues to a control processor that manages the entire payload enclave (router and several OMB-based devices, with a spacecraft host interface). This paper describes details of the optical router, OMB, reconfigurable transceivers and supporting protocols.

This paper describes a modular strategy for communications in which each platform (being a satellite, airplane, missile/munition, even soldiers) carries a hub-and-spoke internal network integrating a variety of modems and other information devices. These embedded networks, referred to as “global network access terminals” (GNATs), are in fact information convergence devices that seek connection with other peers (subject to constraints, such as energy and security) to form basic “substrate networks” (a type of mobile ad hoc networks). Overlays are formed on top of these oftenunreliable substrates, permitting the virtualization of networks that can appear to be more reliable, hence a type of softwaredefined network (SDN). The concepts for this type of SDN is drawn from the rich base of SDN and network functional virtualization (NFV) concepts used in cloud computing , except that they are must be optimized for the heterogeneous and rapidly changing nature of the basic substrate network formed opportunistically by GNATs.

The development and implementation of the next generation wireless technology has been a key industrial goal over the last decade where many pieces of infrastructure are being incrementally built and deployed. The dream of automated homes, driverless vehicles, automated air traffic control, and intelligent cybermedicine can all be implemented with 5G and Artificial Intelligence/Machine Learning (AI/ML). Once you add AI/ML to the proposed high bandwidth, high speed, low latency network, with ubiquitous connectivity, we get a platform that can enable many safety-critical automated functions. 5G can also provide connectivity to every potential device to ensure owner knowledge of status and alerts for potential malfunctions. All this data can become weaponized in the wrong hands, so as we create more data to make life better and safer, we create vulnerabilities that can leverage the speed, and capacity of the communication system to harm users. This paper addresses the potential vulnerabilities and mitigations of ubiquitously implementing 5G to ensure secure communications and data protection.

Recent advances in commercial-level virtual-reality (VR) systems have reduced the barriers to entry into the use of virtual-reality products in both financial and technical terms. With lower costs, less obtrusive hardware, and greater adoption amongst the wider technology fields, VR systems are attracting new interest in industries that have previously not leveraged VR for enhanced data interaction. Three-dimensional data-sets have traditionally been reviewed in two-dimensions by slicing the three-dimensional data, or animating a fly-through on a flat screen. While this mode of review does offer one method for data interaction, the extension into a third-dimension via VR offers new data immersion at a previously unseen scale. L3 Unmanned Maritime Systems is exploring new data interaction tools that leverage VR to immerse operators and users in three-dimensional water quality, optical reconstructions, bathymetry scenes to make post-mission analysis more efficient and effective. This paper will discuss the use of virtual-reality for AUV post-mission analysis along with in-software metrics for quantifying the benefits of VR use. We will discuss early L3 Unmanned Maritime Systems VR training efforts and current efforts building more involved analysis tools.

In April of 2017 NATO recognized a new standard called JANUS (ANEP-87) that enabled open-access underwater communications to support interoperation of acoustic modems from various manufacturers. The standard was developed over several years primarily at the Centre for Maritime Research and Experimentation (CMRE) in La Spezia, Italy. The key feature of JANUS is the modulation method used in the physical layer communication protocol, employing a form of “frequency hopping” (FH) which sequentially assigns each individual symbol out of the encoder precisely one position in time and frequency.

As high-density power supplies extend mission runtimes from hours to days, the use of heterogeneous UUVs to perform coordinated missions is growing quickly. Two decades ago, a single unmanned underwater vehicle (UUV) might be deployed to conduct a survey, and recovered several hours later with or without data and be deemed a mostly successful day. As technology has advanced, though, what constitutes a successful day has changed dramatically. Man-portable UUVs are demonstrating runtimes in terms of days, while new sensor packages are recording environmental data in unprecedented fidelity. This paper explores the use of acoustic communications to increase operational efficiency in a variety of situations. Specifically, we discuss acoustic network applications in the form of the ability to perform message forwarding, vehicle-determined acoustic retasking, and the use of acoustic mid-mission updates sent to third-party listening stations for near-real-time review.

Here we discuss an open software architecture to develop, test, and evaluate machine learning algorithms for target detection and classification. This architecture, known as the Modular Algorithm Testbed Suite (MATS), aids developers by defining interfaces for various portions of the automatic target detection processing chain. There are several key advantages to this approach. First, with “plug and play” modules for detection, feature extraction, and classification, developers can mix and match different approaches and focus on particular portions of the processing chain that yield the most performance benefit. Second, since some portions of the processing chain may be more agnostic to the sensor data type than others, e.g. target features may change but the pattern classification approach is the same, MATS enables quick ATR development for similar data types. Finally, since developers can insert "black boxes" into the ATR processing chain, MATS allows for independent blind testing of algorithms without compromising intellectual property. In this paper, we will discuss the MATS architecture and review several case studies where MATS enabled rapid demonstration and transition of ATR algorithms to Navy mine countermeasure (MCM) post-mission analysis software.

Interoperability between systems is normally created through highly coupled interfaces and exchanges hardcoded into multiple systems' core software. Open architecture standards attempt to solve interoperability by a common programming interface but these open architectures suffer from the same manual programming need when interfacing with systems outside of the same open architecture standard and often between different versions of the same standard. The drive to a common standard can work for stable technology but military systems are constantly upgrading to new global and regional threats and are continually diverging away from standard practices. The STITCHES toolchain provides two overarching and automatically generated functions: translation of messages and control of data flow. STITCHES' translation function is created by a novel use of graph and category theory via a graph-based data base where messages are transformed to other semantically equivalent messages and the STITCHES compiler translates between two system messages by traversing the graph then optimizing the final transform. Data flow control is achieved by implementing routing functions, data synchronization, source and destination isolation, and several other types of data control via both stateless and statefull transports. Both of these STITCHES functions are implemented by a custom domain specific language tailored to interoperability. The result is large and small system of systems implemented on the scale of minutes to hours vs months to years which has been routinely demonstrated within the DARPA SoSITE program.

Warfighter mission scenarios have evolved, and show a greater need to cover more diverse sets of targets from a single platform, and require a number of different sensor packages. Increases in computing speed and global connectivity have expanded the rate of technological advances. This has evened the global playing field, and many have taken advantage of the situation, shrinking the significant advantage that the United States once held over its peers. Traditional acquisition processes and stove-piped proprietary weapon and sensor systems no longer suffice. Unique integrations, vendor-lock-in, and data rights issues have been shown to stifle competition, limit innovation, eliminate missionized capabilities, and drive life-cycle program costs. To maintain dominance in this environment, the DoD must create agile systems that are flexible, modular, rapidly reconfigurable, and adaptable to shifting priorities. The Air Force Research Laboratory (AFRL) is responding by developing technologies for Agile Intelligence, Surveillance and Reconnaissance (ISR), or simply AgileISR. The AgileISR mission is to support rapid and affordable integration of emerging capabilities, delivering advanced sensing and communications capabilities to legacy aircraft and enables higher mission readiness and adaptability to the future needs of the Air Force. A key component of AgileISR is the Open Adaptable Architecture (OA2), which enables rapid integration of sensor systems built on open architecture standards and a Government-owned physical pod interface for developing and acquiring missionized solutions.

Open Architectures (OAs) play a key role in the design of sensor systems in the government and commercial world of today. The attraction of OAs is their ability to enable interoperability and reduce the cost of sensor systems. The Sensor Open Sensor Architecture (SOSA) Consortium is a consensus based community of government and industry partners working together to develop the next generation of sensors that have a well-defined set of interfaces for software, hardware, and electrical/mechanical components. In total, the SOSA Technical Standard is applicable to any one of the five sensor types (or combination): radar (RADAR), electro-optical and infrared (EO/IR), signal intelligence (SIGINT), communications (COMMS), and electronic warfare (EW). The ability of the SOSA Technical Standard to be a pointer to five different sensor types is what sets it apart from other standards available today. Many standards suffer from being application/platform specific, relevant to only one sensor type, and locked to a particular vendor. The SOSA Consortium combats this problem by focusing on being platform, vendor, and sensor agnostic. This paper provides use cases to demonstrate the efficacy of the SOSATM Technical Standard for different sensor types. The use cases demonstrate how the electro-mechanical, hardware, architecture, software, and business concepts of the SOSA Technical Standard will be advantageous to the design and procurement of the next generation of sensors.

Pervasive and ubiquitous computing is now universal. We now have intelligent and interconnected kitchens. Cars are interconnected networks on wheels. Smart highways will be here before the flying car. In the near future, the Internet-of- Things (IoT) will provide inter-connectivity for all things electronic. In 1971, the first 4 bit microprocessor was introduced. Nearly 50 years later, the microprocessor is driving global, world-wide connectivity to everything. More fundamental than pervasive and ubiquitous computing is the underlying technology of digital communications. Shannon proved in 1948, that digital communications provide for an arbitrarily small number of errors regardless of the distance between sender and receiver. Once data is in a digital form, it can be transmitted or copied an arbitrarily large number of times without error. Digital is a universal language which can transmit and store information for millennia to come. Digital is defined as quantized, discrete time. In this paper, we review sampling theory to convert analog to discrete time and discrete time to digital. We will illustrate the importance of understanding analog-to-digital conversion for model based engineering.

Planning future Multi-Domain Battle (MDB) missions requires extensive, complex, and real-time collaboration and coordination between many Warfighting Functions and Domains such as Electronic Warfare (EW), Positioning, Navigation and Timing (PNT), Network Operations, and Cyber Operations. This collaboration and coordination requires synchronization of the associated domain processes and activities. Large Infrastructure projects for Command and Control (C2) are designed to integrate and align these processes through Information Technology (IT) services, such as decision aids, collaboration tools, and communication tools. New acquisition initiatives are driving infrastructure development to support the rapid fielding of capabilities through a modular software development approach. State-of-the-Art Shared Infrastructure Services can be developed using Agile Software Development (ASD) methods such as Scrum, Kanban, or Extreme Programming. However, the integration of these IT services cannot be easily planned since they are developed at the technology (i.e., software implementation) level according to the selected ASD method. Engineering the Infrastructure as Code (IaC) results in a gap between doctrinal processes and required system functionality since developers quickly code and configure small functional modular units at the technology level, while bypassing the traditional top-down waterfall flow from requirements to design. Furthermore, IaC does not explicitly require consulting a systems architecture. To improve the alignment of configured IT infrastructure services with doctrinal processes, this paper seeks to determine the extent to which agile Development Operations (DevOps) process can implement C2 doctrine while supporting dynamically-changing mission requirements and an operational environment. This paper proposes an automated Systems Engineering workflow to realize IT infrastructure services using Model-Driven Architecture (MDA) and a military DevOps.

Providing advanced healthcare to the warfighters in the battlefield has proven challenging due to the difficult environmental conditions and geographical separation between the injured warrior and healthcare providers. The introduction of Cyber Medicine enables physicians and soldiers to utilize technologies including mobile apps, robotics, connectivity to wired/wireless networks, satellites, clouds, HPCs, and software to identify, assess and treat the injured. However, what happens when the adversary attacks the cyber domain in addition to the physical domain? The answer could be that all automated systems will become suspect whether they are embedded systems, information processing systems, diagnosis and triage systems, or remote surgical robotics. This analysis identifies areas where the intelligent Cyber-Medical System can provide better healthcare to the battlefield including services to the disadvantaged soldier at the edge. Architecting intelligent systems starts with learning the desired system operation, sifting through historical data and procedure outcomes, assessing vulnerabilities, then delivering systems that mimics and augment human performance to solve problems. The battlefield Cybermedicine has the challenge of increased cyber security risks due to the need to be deployed in hostile environment, and the challenge of dealing with injuries that are unique to the battlefield. Moreover, the viability of intelligent automation depends on reliable connectivity and availability of reliable data and infrastructure, while the battlefield lacks both those conditions. The goal of this study is to deliver medical services and alleviate the vulnerability impacts through more secure design, development, deployment, maintenance, and operations. Additionally, this paper introduces new cybermedicine concepts and architectures that benefit from the various types of Machine Learning and Artificial Intelligence to build Cyber-Medical System that can resist corruption from unauthenticated users/data, and from active malware and physical media attacks.

To meet todays challenges in ISR (Intelligence, Surveillance and Reconnaissance) defense coalitions Systems of Systems (SOS) architectures are needed that are flexible, function in a networked environment and support relevant operational doctrine and processes. To enable the distributed production of intelligence in networked operations the Intelligence Cycle and Joint ISR (JISR) provide process descriptions that adhere to multinational and multisystem collaboration. An interoperable SOS architecture supporting those processes needs to make use of standards for data/information management with a special focus on dissemination. The NATO ISR Interoperability Architecture (NIIA) and supportive standards (STANAGS- standardization agreements) have been specified to provide a solution to these needs. In terms of data distribution, STANAG 4559 is the core standard of relevance here. It defines a concept, data- and information models, interfaces and services to support information dissemination according to JISR. The current specification for synchronization of JISR results however has some deficiencies in terms of implementation complexity, flexibility, robustness and performance. Thus, there is a need for a new approach to data dissemination in networks implementing STANAG 4559 that enables the usage of all aspects currently supported by this standard but seeks to solve the known issues. Thereupon this paper presents requirements for data dissemination in a JISR enterprise, derives key performance indicators (KPIs), identifies possible technical approaches and finally defines a new solution based on the concept of Hash Tries. Here a tree-based data structure is organized based on hashes of nodes, which allows a quick identification of changes in replicated data.

Heterogeneous system-on-chips (SoC) can increase the energy-efficiency of domain-specific computation by orders of magnitude compared to scalar processors. High-performance systems can be generated procedurally through example-driven inference of a domain of computation to facilitate the design of domain-specific SoCs. This paper focuses on the domain of signal processing as it plays a recurring and important role in automation. The expertise required to build processors well-suited to a specific computation domain, rather than a single application or general computation, is inferred through the statistical analysis of computation, hardware, and their affinity for each other. This paper highlights the development of an ontological inference engine to achieve this goal.

The main challenge of computer linguistics is to represent the meaning of text in a computer model. Statistics based methods with manually created features have been used for more than 30 years with a divide and conquer approach to mark interesting features in free text. Around 2010, deep learning concepts found their way into the text-understanding research community. Deep learning is very attractive and easy to apply but needs massive pools of annotated and high quality data from every target domain, which is generally not available especially for the military domain. When changing the application domain one needs additional or new data to adopt the language models to the new domain. To overcome the everlasting “data problem” we chose a novel two-step approach by first using formal representations of the meaning and then applying a rule-based mapping to the target domain. As an intermediate language representation, we used abstract meaning representation (AMR) and trained a general base model. This base model was then trained with additional data from the intended domains (transfer learning) evaluating the quality of the parser with a stepwise approach in which we measured the parser performance against the amount of training data. This approach answered the question of how much data we need to get the required quality when changing an application domain. The mapping of the meaning representation to the target domain model gave us more control over specifics of the domain, which are not generally representable by a machine learning approach with self-learned feature vectors.

In complex operational scenarios where multiple nations and forces cooperate, flexible System of Systems (SoS) architectures being customizable to specific operations are needed. Relevant operational processes as defined within Joint ISR (Intelligence, Surveillance and Reconnaissance) and the Intelligence Cycle need to be supported. To maximize efficiency and effectiveness of Joint ISR capabilities, each Joint ISR result needs to answer the corresponding information requirement accurately. Commanders must receive the relevant information in a condensed, well-prepared manner instead of being overflowed with large amounts of (raw) data. Ensuring a common understanding of each exchanged piece of information within the defence coalition is also of utmost importance. Architectures supporting these requirements need to make use of relevant standards and agreements for data/ information management. As reports may be provided by all Joint ISR capabilities, the topic of reporting is of high importance, here. Within the described context, our publication deals with formal reporting which can be defined as organizational process at which relevant information is provided as formal reports, i.e., as documents being structured according to pre-defined (agreed) rules. We present means for ensuring allied interoperability and further (semi-)automatic processability of the information being contained in formal reports by technical means and under consideration of the relevant doctrines and standards. We also address specific means needed to ensure the creation of formal reports of high quality. Finally, we discuss current issues and new requirements on formal reporting which have to be still addressed in the field of Joint ISR.

Applications of drones have been rapidly changing during the last years. The driver in development of drone systems in the past was the military. This changed due to the fast technological progress of drone systems in the private sector as well as the industrial market. Sinking costs, progressive miniaturization, functional enlargement and increasing performance and usability are key enabler for practical realization of previously only theoretical civil and military exertions. RD is currently developing systems-of-systems, grouping drones into swarms to solve or execute mostly non-complex tasks cooperatively to demonstrate feasibility with respect to pre-defined scenarios. The used mission management and control systems are often rudimental, non-dynamic and designed to serve only the corresponding scenarios. For real world applications of drone systems operating in cooperative groups this is insufficient, as flexible control mechanisms with respect to changing environments or mission targets are missing. This work addresses mission management and control as the central executing and overarching system glue, rendering effective and efficient application of drone swarms possible in the first place. Requirements to the command and control station, the operator as human in the loop and the assigned assets are investigated and consolidated into a novel approach. The system centric view is neglected in favour of a paradigm shift to macro control by introducing the "management by objective" approach based on prior work. The focus of mission control by the operator is moved from system-oriented control to a goal-oriented control focusing on results provided by the executing assets.

Cloud computing has transformed the evolution of software for much of information technology (IT) industry. Focusing on developing microservices rather than complete platforms has significant advantages, including enterprise interoperability, resiliency, and reduced system development and sustainment costs. Amazon Web Services (AWS), Google Cloud Platform, OpenStack, and Kubernetes are examples of public and private cloud technologies that commercial and government enterprise systems are migrating to. Unfortunately, these technologies do not extend to endpoints like Warfighter arm-mounted tablets and spacecraft. The goal of the Space Cloud Computing (SCC) project is to develop technologies that provide a corollary to public/private cloud concepts for all asset endpoints to enable new Warfighter planning and tasking concepts and superior levels of situational awareness. This paper explores the computation and networking challenges and solutions for such a platform in the space domain.