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Kinetic Realtime Observation Network Operation and Synchronization (KRONOS)

The Holloman High Speed Test Track conducts crucial subsonic and hypersonic sled testing over its extensive ten-mile course. Established in the 1980s, the track's original timing and control infrastructure, reliant on extensive 200-pair copper telephone wire networks, is now due for a comprehensive update to meet contemporary testing demands. The diversity of sensors along the track, from basic wire break detectors to sophisticated Doppler radar and real-time video systems, necessitates a unified time base for accurate data analysis. Moreover, the system's command-and-control capabilities are essential for initiating, halting, and managing tests, including critical emergency stop functions. An updated system must also facilitate efficient data retrieval, storage, and exportation in standard formats to ensure seamless interaction with measurement devices and secure transmission of test data back to the control center.

Within the KRONOS design, GPS provides a clock and UTC synchronization while an onboard Chip Scale Atomic Clock (CSAC) continues accurate timing even without a GPS signal. Timing nodes provide the 1ns accurate timestamp, the interface methods to various sensor and equipment, and the communications back to command over existing copper lines. An optional wireless or highspeed modem link provides faster data transmission and real time camera streaming, and the command-and-control center can be located on site or remote.

In this Phase I contract for the US Air Force, our objective is to lay the groundwork for a comprehensive system that revolutionizes the functionality and efficiency of the Holloman High Speed Test Track. This system will not only meet the stringent requirement of 1ns accurate distributed timing but also leverage the existing copper network infrastructure for command, control, and data transfer capabilities.



Wideband 16x12 Non-Blocking Radio Frequency Switch

Under a contract with the US Navy, BANC3 is currently developing a dynamically reconfigurable, minimal latency 6U Virtual Path Cross-Connect (VPX) wideband non-blocking radio frequency (RF) switch that can simultaneously handle thousands of diverse signals from multiple apertures to multiple channels on a single processing card to increase autonomy while addressing emerging and dynamic threats.

Our solution will enhance Signal Intelligence (SIGINT). An Electronic Support Measure (ESM) provides the passive capability to search, intercept, collect, classify, geo-locate, monitor, copy, exploit, and disseminate these signals over a specific RF range. A key subsystem to an ESM is the RF distribution, Current 6U RF switches are limited in the exploitation of the frequency spectrum due to size, weight, power, and cooling (SWaPC) constraints associated with the frequency response of the components in the signal conditioning path.

Our Phase 1 project is the development of a 16x12 non-blocking switch that operates from 1.5 MHz to 18 GHz. This non-blocking RF switch will maintain present 6U SWaPC constraints, and it will be a single processing card while maintaining open interface standards. The non-blocking RF switch must be able to route any of the 16 input apertures to any of the 12 output tuner channels while remaining dynamically reconfigurable via a sensor open systems architecture (SOSA). An RF Cascade analysis of the design will address the non-blocking RF switch’s performance in signals’ Gain, Isolation (input-coupled and output-coupled), Noise Figure (NF), as well as input third order Intercept Point (IIP3), 1 dB Compression Point (P1dB), and switching time.



Intelligent Wideband Signal Cueing for Electromagnetic Spectrum Monitoring

Today’s electromagnetic spectrum monitoring (ESM) missions require an increasingly wide radio frequency (RF) bandwidth to intercept, process, and analyze a myriad of threat signals including communications, data links, surveillance radars, and targeting radars. These emitter waveforms often employ sophisticated modulation techniques including phase modulation, spread spectrum, linear frequency modulation, and frequency agility that further emphasizes the need for wide bandwidth coverage. The proliferation of commercial communications systems adds to the complexity and density of the contested RF spectrum. Thus, legacy ESM systems that routinely covered up to 6 GHz must now be expanded to include X-band (8-12 GHz) and Ku-band (12-18 GHz) to address emerging threats in these portions of the RF spectrum.

Under this Phase 1 contract from the US Navy, BANC3 professionals are developing Machine Learning (ML) cue generators to identify and extract features or "cues" from data that can be used as input to an ML signal classification model. These cues are necessary for the model to learn patterns, make predictions, or classify data effectively. A cue generator will extract characteristics from a signal that are indicative of specific patterns, such as the presence of a Frequency Hopping Spread Spectrum (FHSS) signal. An effective cue generator should include Feature Extraction: identify and extract relevant signal parameters that can be used by an ML model; Preprocessing: clean and normalize the data to enhance the relevance of the extracted signal parameters; Data Reduction: reduce the complexity of the data to facilitate processing in the ML model; and Pattern Recognition: detect patterns or anomalies that can support signal classification

BANC3 specializes in the design, development, integration, and test of extremely wide instantaneous bandwidth software defined receiver (SDRX) systems for RF spectrum monitoring in support of military/aerospace missions. Our experience in this area includes the design and development of a channelized system to cover the full RF band with 25 separate channels that are processed in parallel, in real-time to achieve an instantaneous bandwidth of 18 GHz continuously with no data losses.