In recent years, radio frequency (RF) situational awareness has attracted the interest of many DoD programs. Its practical application in analyzing the behavior of both friendly and adversarial units from a new RF signal transmission perspective offers versatile utility to a broad range of DoD-related scenarios. It is critical to understand how the RF spectrum is used by different RF applications, how the emitters behave in a given operational environment, and which types of transmissions behave in a distinctive way in order to better comprehend the immediate situation and locate potential threats. In this proposal, we propose an RF situational awareness solution that is well-equipped to deal with a large amount of RF signals collected from a congested environment in near real-time. The proposed pattern of life engine, named PoLICE, consists of three main components: the RF data collector, signal database, and PoLICE. The data collector consists of a software-defined radio (SDR) receiver and a signal preprocessor, which is able to capture the RF signals in the target frequency band and extract the features of the intercepted signals. The data collector is deployed on Navy platforms and sensor units on the battlefield. The PoLICE module is implemented as a web service deployed on a server or any equivalent platform such as a distributed edge network. The PoLICE module ingests the collected signal data from the databases and sends the corresponding signal information to each pattern of life (PoL) analyzer for pattern learning and anomaly detection. The results of PoL analysis will be displayed to the operators and analysts through our GUI, which can be accessed from anywhere using any device. With this solution, the human operators and analysts are able to receive alerts and direct their focus to abnormal signals instead of being overwhelmed by a vast amount of intercepted RF signals. Our solution supports different types of deployment, including the standalone mode where all components are deployed on a single Navy platform, and distributed mode, where different components can be deployed to different platforms/infrastructures and connected through Navy networks.
Benefit: As a final product, our PoLICE will be implemented with a set of RF receivers for spectrum monitoring and a web application for RF signal processing. To support different types of missions, our product is able to support both centralized and distributed data processing. To better utilize the computational resources, the web application can be deployed to an edge network formed by a set of units or platforms on the battlefield or a remote cloud server. The PoLICE backend program will automatically retrieve newly received RF data, perform data processing, pattern learning, and anomaly detection, and keep updating the results displayed through the web GUI. Currently, there is no viable commercial product available on the market that can provide such a comprehensive solution covering RF receivers, RF signal preprocessing, distributed data storage, and RF PoL analysis. For the DoD market, our product is able to provide support for SIGINT, spectrum surveillance, and RF situational awareness related applications. Our first transition target would be the Office of Naval Research (ONR) Code 31, Information, Cyber and Spectrum Superiority. The capabilities enabled by PoLICE will provide significant contributions to their operational needs. Our next transition target will be Navy programs working on command & control (C2) applications. For example, Naval Information Warfare Center Pacific (NIWC Pacific) is conducting multiple C2 related programs. The global C2 systems market size is projected to grow from USD 33 billion in 2019 to USD 43.9 billion by 2025, at a CAGR of 4.9% from 2019 to 2025. As a key aspect in C2 applications, our RF situational awareness solution will also have a good entry point into this market. In the commercial market, there are many applications that can benefit greatly from our PoLICE solution. One prominent opportunity is in supporting spectrum monitoring and analysis for wireless service providers, by monitoring the spectrum usage of their customers, detecting unexpected interference or spectrum occupation, and optimizing their resource management. The overall spectrum analyzer market was valued at USD 999.2 million in 2015 and is expected to reach USD 1.75 billion by 2022, at a CAGR of 8.48% between 2016 and 2022. Our PoLICE product has the potential to become a competitive player in this market.
Keywords: pattern of life, pattern of life, LSTM, Waveform Pattern, time-frequency analysis, SIGINT, anomaly detection, Machine Learning, RF Situational Awareness
