Tactical ISR/C2 Integration with AI/ML Augmentation

NPS NRP Project PresentationNAVPLAN 2021 specifies Distributed Maritime Operations (DMO) with a tactical grid to connect distributed nodes with processing at the tactical edge to include Artificial Intelligence/Machine Learning (AI/ML) in support of Expeditionary Advanced Base Operations (EABO) and Littoral Operations in a Contested Environment (LOCE). Joint All-Domain Command and Control (JADC2) is the concept for sensor integration. However, Intelligence, Surveillance and Reconnaissance (ISR) and Command and Control (C2) hardware and software have yet to be fully defined, tools integrated, and configurations tested. This project evaluates options for ISR and C2 integration into a Common Operational Picture (COP) with AI/ML for decision support on tactical clouds in support of DMO, EABO, LOCE and JADC2 objectives.Commander, Naval Surface Forces (CNSF)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Malicious Digital Penetration of United States Weaponized Military Unmanned Aerial Vehicle Systems: A National Security Perspective Concerning the Complexity of Military UAVs and Hacking

The United States’ (US) military unmanned aerial vehicle (UAV) has seen increased usage under the post 9/11 military engagements in the Middle East, Afghanistan, and within American borders. However, the very digital networks controlling these aircrafts are now enduring malicious intrusions (hacking) by America’s enemies. . The digital intrusions serve as a presage over the very digital networks the US relies upon to safeguard its national security and interests and domestic territory. The complexity surrounding the hacking of US military UAVs appears to be increasing, given the advancements in digital networks and the seemingly inauspicious nature of artificial intelligence and autonomous systems. Being most victimized by malicious digital intrusions, the US continues its military components towards growing dependence upon digital networks in advancing warfare and national security and interests. Thus, America’s netcentric warfare perspectives may perpetuate a chaotic environment where the use of military force is the sole means of safeguarding its digital networks

5G: 2020 and Beyond

The future society would be ushered in a new communication era with the emergence of 5G. 5G would be significantly different, especially, in terms of architecture and operation in comparison with the previous communication generations (4G, 3G...). This book discusses the various aspects of the architecture, operation, possible challenges, and mechanisms to overcome them. Further, it supports users? interac- tion through communication devices relying on Human Bond Communication and COmmunication-NAvigation- SENsing- SErvices (CONASENSE).Topics broadly covered in this book are; • Wireless Innovative System for Dynamically Operating Mega Communications (WISDOM)• Millimeter Waves and Spectrum Management• Cyber Security• Device to Device Communicatio

Custom wireless sensor for monitoring grazing of free-range cattle

Scope and Method of Study: The purpose of this study was to develop a wireless sensor device capable of sensing cattle grazing activity. This included design and build of a miniaturized PCB, sensor specification, data processing, and experimental validation. Experiments were conducted in cooperation with the Oklahoma State University, Animal Science and Biosystems Engineering departments. The primary objective of this study was to provide information supporting the use of an accelerometer sensor for monitoring free-range cattle grazing activity. A wireless sensor platform was also developed for sensor and wireless communication development needs. Secondary objectives included exploring alternative applications, such as monitoring cattle waste excretion events, and identifying wireless network functionality for agricultural environments.Findings and Conclusions: During this study, parameters for using an accelerometer based grazing sensor were established relative to the head motion of grazing cattle. Initially, a survey of literature and video analysis of foraging livestock animals were conducted, where 0.5-8 bites/sec was confirmed as animal bite rate range. The preliminary video analysis provided guidelines for establishing a sensing strategy. Sensor data processing algorithm development and sampling rate selection were driven by video provided characteristics and sensor platform capability. The Fast Fourier Transform (FFT) was selected as the core component of the sensor's algorithm. The FFT was able to characterize grazing motions because of the animal's near-continuous periodic head movements. At least five bite cycles and a 32 Hz sampling rate were required for proper algorithm implementation. A sample size of 256 data points were collected for each accelerometer axis, and proved to be adequate for the FFT computations. A revised sample rate of 21.74 Hz was presented once the FFT was implemented in firmware. This new rate retained well performing FFT calculations based on the understanding that bite rates faster than 4 bites/sec were due to nibbling and partial bites. The FFT's Spectral power was binned and stored for the purpose of data compression and reduced wireless transmissions.The wireless sensor device platform was built using the CC1010 microcontroller/transceiver IC. The CC1010 provided integrated features commendable for fast FFT processing and conservative PCB layout design. The radio was configured for robust operation by using a 915 MHz carrier frequency, Manchester encoding, and 64 kHz frequency spread. A small, helical, and omnidirectional antenna was mounted directly to the PCB. Link budget was estimated to be 81 dBm, which equated to a 282 m (925 ft) transmission distance in optimum conditions. The device's dimensions were 19.6 mm (0.77 in) X 71.8 mm (2.83 in) X 11.0 mm (0.43 in). A custom PVC enclosure was used to house the device. For deploying experiments, the enclosure was fastened to a standard nylon turnout halter. A miniature GPS logger was also attached to the halter, which allowed for constructing grazing maps.Additionally, the proposed wireless sensor device was used to detect cattle urination and defecation events. This was accomplished by attaching the device to an animal's tail and sensing its elevated movements. Tilt measurements in the z-axis (front-to-back) direction provided the most prominent evidence of a distinct tail movement pattern during excretion events. A pattern recognition strategy was shown as a viable sensing method.An outline for a multilevel-networked system was also generated. This included cellular and internet communications, along with a customized application software for base/node management

Global Shipping Container Monitoring Using Machine Learning with Multi-Sensor Hubs and Catadioptric Imaging

We describe a framework for global shipping container monitoring using machine learning with multi-sensor hubs and infrared catadioptric imaging. A wireless mesh radio satellite tag architecture provides connectivity anywhere in the world which is a significant improvement to legacy methods. We discuss the design and testing of a low-cost long-wave infrared catadioptric imaging device and multi-sensor hub combination as an intelligent edge computing system that, when equipped with physics-based machine learning algorithms, can interpret the scene inside a shipping container to make efficient use of expensive communications bandwidth. The histogram of oriented gradients and T-channel (HOG+) feature as introduced for human detection on low-resolution infrared catadioptric images is shown to be effective for various mirror shapes designed to give wide volume coverage with controlled distortion. Initial results for through-metal communication with ultrasonic guided waves show promise using the Dynamic Wavelet Fingerprint Technique (DWFT) to identify Lamb waves in a complicated ultrasonic signal

Exploring Motion Signatures for Vision-Based Tracking, Recognition and Navigation

As cameras become more and more popular in intelligent systems, algorithms and systems for understanding video data become more and more important. There is a broad range of applications, including object detection, tracking, scene understanding, and robot navigation. Besides the stationary information, video data contains rich motion information of the environment. Biological visual systems, like human and animal eyes, are very sensitive to the motion information. This inspires active research on vision-based motion analysis in recent years. The main focus of motion analysis has been on low level motion representations of pixels and image regions. However, the motion signatures can benefit a broader range of applications if further in-depth analysis techniques are developed. In this dissertation, we mainly discuss how to exploit motion signatures to solve problems in two applications: object recognition and robot navigation. First, we use bird species recognition as the application to explore motion signatures for object recognition. We begin with study of the periodic wingbeat motion of flying birds. To analyze the wing motion of a flying bird, we establish kinematics models for bird wings, and obtain wingbeat periodicity in image frames after the perspective projection. Time series of salient extremities on bird images are extracted, and the wingbeat frequency is acquired for species classification. Physical experiments show that the frequency based recognition method is robust to segmentation errors and measurement lost up to 30%. In addition to the wing motion, the body motion of the bird is also analyzed to extract the flying velocity in 3D space. An interacting multi-model approach is then designed to capture the combined object motion patterns and different environment conditions. The proposed systems and algorithms are tested in physical experiments, and the results show a false positive rate of around 20% with a low false negative rate close to zero. Second, we explore motion signatures for vision-based vehicle navigation. We discover that motion vectors (MVs) encoded in Moving Picture Experts Group (MPEG) videos provide rich information of the motion in the environment, which can be used to reconstruct the vehicle ego-motion and the structure of the scene. However, MVs suffer from high noise level. To handle the challenge, an error propagation model for MVs is first proposed. Several steps, including MV merging, plane-at-infinity elimination, and planar region extraction, are designed to further reduce noises. The extracted planes are used as landmarks in an extended Kalman filter (EKF) for simultaneous localization and mapping. Results show that the algorithm performs localization and plane mapping with a relative trajectory error below 5:1%. Exploiting the fact that MVs encodes both environment information and moving obstacles, we further propose to track moving objects at the same time of localization and mapping. This enables the two critical navigation functionalities, localization and obstacle avoidance, to be performed in a single framework. MVs are labeled as stationary or moving according to their consistency to geometric constraints. Therefore, the extracted planes are separated into moving objects and the stationary scene. Multiple EKFs are used to track the static scene and the moving objects simultaneously. In physical experiments, we show a detection rate of moving objects at 96:6% and a mean absolute localization error below 3:5 meters

Advanced Robot Path Planning (RRT)

Tato diplomová práce práce se zabývá plánováním cesty všesměrového mobilního robotu pomocí algoritmu RRT (Rapidly-exploring Random Tree – Rychle rostoucí náhodný strom). Teoretická část popisuje základní algoritmy plánování cesty a prezentuje bližší pohled na RRT a jeho potenciál. Praktická část práce řeší návrh a tvorbu v zásadě multiplatformní C++ aplikace v prostředí Windows 7 za použití aplikačního frameworku Qt 4.8.0, která implementuje pokročilé RRT algoritmy s parametrizovatelným řešičem a speciálním dávkovým režimem. Tento mód slouží k testování efektivnosti nastavení řešiče pro dané úlohy a je založen na post-processingu a vizualizaci výstupu měřených úloh pomocí jazyka Python. Vypočtené cesty mohou být vylepšeny pomocí zkracovacích algoritmů a výsledná trajektorie odeslána do pohonů Maxon Compact Drive všesměrové mobilní platformy pomocí CANopen. Aplikace klade důraz na moderní grafické uživatelské rozhraní se spolehlivým a výkonným 2D grafickým engine.This master's thesis deals with path planning of omnidirectional mobile robot using the RRT algorithm (Rapidly-exploring Random Tree). Theoretical part describes basic algorithms of path planning and presents closer view on RRT and its potential. Practical part deals with designing and creation of essentially multiplatform C++ application in Windows 7 environment with Qt 4.8.0 application framework, which implements advanced RRT algorithms with user-programmable solver and special batch mode. This mode is used for testing the effectiveness of solver on given tasks and it is based on postprocessing and visualization of measurement tasks output by Python language. Computed paths can be enhanced by shortening algorithms and result trajectory sent to Maxon Compact Drives of omnidirectional platform via the CANopen. Application puts emphasis on modern GUI with reliable and powerful 2D graphics engine.

5G: 2020 and Beyond

The future society would be ushered in a new communication era with the emergence of 5G. 5G would be significantly different, especially, in terms of architecture and operation in comparison with the previous communication generations (4G, 3G...). This book discusses the various aspects of the architecture, operation, possible challenges, and mechanisms to overcome them. Further, it supports users? interac- tion through communication devices relying on Human Bond Communication and COmmunication-NAvigation- SENsing- SErvices (CONASENSE).Topics broadly covered in this book are; • Wireless Innovative System for Dynamically Operating Mega Communications (WISDOM)• Millimeter Waves and Spectrum Management• Cyber Security• Device to Device Communicatio