Company
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Back to Company Search0 BASE DESIGN, LLC
UEI: W52ZM2KUANR3
Number of Employees: 13
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
SBIR/STTR Involvement
Year of first award: 2017
5
Phase I Awards
2
Phase II Awards
40%
Conversion Rate
$589,712
Phase I Dollars
$1,749,922
Phase II Dollars
$2,339,634
Total Awarded
Awards
Opportunistic Passive RF Detection, Classification and Localization
Amount: $749,922 Topic: AFX20D-TCSO1
In the last decade there has been an exponential growth in the technology and application of unmanned air vehicles (UAVs) or “drones”. Once simple radio-controlled aircraft, modern UAVs are able to operate autonomously, in all conditions, and carry significant payloads. Civilian applications include drones for package delivery, inter- and intra- campus transport, eVTOL urban air mobility (UAM) for materials and people. In the defense sector, the US military has long used UAVs for ISR and for tactical operations. UAV and drone technology are now available to our advisories, having been used to target oil plants and military bases and operations. For commercial and non-hostile applications, tracking air vehicles, atmospheric conditions, and weather is critical to the widespread adoptions of manned and unmanned air vehicles (M/UAVs). However, neither transponders and beacons integrated in M/UAVs, nor implementation of a radar-based air traffic control (ATR) are practical due to spectrum regulation, development times, weight and cost. For non-cooperative and hostile applications, the lack of terrestrial based detection and tracking is a critical security gap; there is a requirement for “drone sensors” that can detect, classify, and locate a hostile drone to protect military operations. Currently there is no available passive M/UAV or drone sensor for either civilian or military applications. To address these critical gaps, 0BD and WRC are developing technology that exploits ubiquitous digital waveform broadcast (FM, TV), cellular network (4G, 5G), and other wireless signals as illumination sources of opportunity. The illumination sources are reflected passively off M/UAVs or phase shifted by weather and atmosphere. By collecting and analyzing these reflected and phase shifted signals, we have shown in Phase 1 and previous work, the ability to detect, classify, and locate M/UAVs and measure changes in atmospheric and meteorological conditions. We propose in this Phase 2 STTR to develop, prototype, and fabricate RF receivers and integrated signal processing to capture the opportunistic signals reflected by M/UAVs and use Deep Convolutional Neural Networks (DCNNs) that employ Transfer Learning (TL) to autonomous detect, classify, and track M/UAVs, outputting data that can be shared with other command and control systems.
Tagged as:
STTR
Phase II
2022
DOD
USAF
Multi-Static Opportunistic Sensing for Urban Air Management
Amount: $149,996 Topic: AFX20D-TCSO1
Technology is proposed that exploits coherent waveforms generated by a multitude of RF systems to detect, classify, localize and track aircraft. This capability is derived from existing bodies of research as well as applied development activities undertaken by the team to measure atmospheric conditions using opportunistic sources like 4G and 5G LTE, broadcast television and emergency responder signals. This capability requires no RF band licensing, exploits the coherent nature of the underlying waveforms, is implemented using common Software Defined Radio (SDR) semiconductors, and can be used for both terrestrial based systems or airborne systems. Novelty is derived by exploiting the underlying coherent waveforms as well as the precision timing of these signals. The near ubiquity of RF systems from 10MHz to 60GHz provides a plentiful range of signals to harvest for our multi-static detection capability. The fact that many of these systems are critical infrastructure requires them to maintain operations in nearly all conditions - often having regulatory requirements for 99.999% operational availability. The number and types of signals offer exceptional source redundancy allowing a system to "switch" between sources depending on operational conditions and resolution required. This provides inherent system robustness. This class of passive Radar system can be used to augment air traffic control and traffic management in heretofore never experienced patterns and densities associated with urban air mobility and unmanned air vehicle concepts. As Agility Prime advances these systems control and monitoring systems like this will become critical for regulatory approval. Management of air traffic in urban and suburban areas will require a multitude of monitoring systems irrespective of the capabilities required by regulatory bodies for aircraft organic sensor systems to track their position and report it via data links. Clearly the potential for aircraft to have failures, be intentionally tampered with, or to spoof other aircraft in a highly congested airspace, particularly around hubs, suggests that terrestrial and other airborne tracking systems will be required. The ability to license RF channels to operate new active systems is very difficult in most regions. The potential for passive Radar where RF signals - from HF through K band - are plentiful is a logical application. The approach we pursue is a novel adaptation of applied research conducted by the team to measure temperature and humidity using opportunistic signals. In that effort we used commercially available SDR chip sets. In this effort we will use similar SDR chip sets to ultimately arrive at a very low cost adaptive receiver. The architecture has the capability to be an exceptionally low "Size Weight and Power and Cost" (SWaP-C) device that has a broad range of military, commercial and consumer applications.
Tagged as:
STTR
Phase I
2021
DOD
USAF
Spectrum Attenuation Reporting Sensor System
Amount: $1,000,000 Topic: AF18B-T005
The Phase 2 development will yield a prototype Cognitive Data Sampling (CDS) system for 2 RF bands to fully demonstrate the capability of the underlying technology. This will include the development of RF antennas, RF signal conditioning for the bands, CDS analog to conversion module and a processor module. The processor module shall be comprised of a Commercial Off-The-Shelf (COTS) module that includes a CPU, GPU and FPGA. This system will enable measuring large instantaneous RF bandwidths (from 3 MHz to over 60 GHz) with minimal down conversion and channelization and provide reduced signal representation for high data throughput and real-time processing. This innovative system is based on mature technology and adapted for efficient RF detection at a significant reduction in cost of ownership. The system will provide complete RF spectral monitoring over extended bandwidths of interest and operate under real-time constrains. By operating at the sensor level and sampling intelligently, this system will reduce bandwidth constraints to downstream processing within the mesh network while maintaining complete coverage of the RF environment. This technology has application to a broad range of RF and optical systems including Identification Friend or Foe, Radar Warning Receiver, Laser Warning Receiver, IR Missile Warning System, Direction Finders, Anti-radiation Missiles, Directional Infrared Countermeasures (DIRCM), Countermeasure Dispenser System (CMDS), Jammers, Self-protection EW Suite, Electromagnetic Shielding/Hardening, Emission Control, Interference Mitigation and Counter UAV Systems.
Tagged as:
STTR
Phase II
2020
DOD
USAF
Low Power, Portable (Podable) Rapid Processing of High Sample-Rate In-Phase Quadrature (IQ) Data
Amount: $139,991 Topic: N193-139
We propose an innovative system to monitor RF spectrum and rapidly process High Sample Rate IQ data in real or near-real time for emitter detection and identification. We base this solution on a compressive sampling front end to generate IQ data with much lower data requirements than a standard Nyquist process coupled with machine learning algorithms designed to be used in lieu of or to augment the standard method of PDW generation and classification. This unique combination of technologies results in a system that offers full compliance with the requirements.
Tagged as:
SBIR
Phase I
2020
DOD
NAVY
Machine Learning to Enhance AF Simulator Training Systems
Amount: $49,814 Topic: AF193-CSO1
The application of machine learning technologies to a broad range of systems and problems has been under development for many years. The emergence of feature based adaptive algorithms as well as generalized deep networks has enabled the broad application. All of these techniques are dependent, at least initially, on labeled data. Many applications have serious confidentiality, privacy or propriety issues associated with their data sets. i.e, Limitations and bounds are placed on data. Our ML techniques have been focused on commercial applications in a wide range of markets - financial, biometric, monitoring - but all have been limited by data sources. We are proposing to use our ML techniques applied to AF VR enabled simulation systems to enhance and automate these systems as a low cost training technique to help pilots build and retain proficiency. This is enabled because the AF generates labeled simulation data every time these systems are used. This capability can be applied to ML enabled training and later can mature out of the simulation environment to become a pilot aid or core engine of an autonomy system.
Tagged as:
SBIR
Phase I
2020
DOD
USAF
Spectrum Attenuation Reporting Sensor System
Amount: $149,947 Topic: AF18B-T005
The radio frequency (RF) spectrum from frequencies below 100 kHz to over 95 GHz has become a crowded workspace for many commercial and military communications, navigation, and sensing applications. Across the spectrum, attenuation and noise levels determine channel and band usability, dynamically impacted by atmospheric physics, lightning, solar activity, unintended interferers, and, in hostile scenarios, jammers, EMP and HEMP events. Maintaining communications in a dynamically changing RF environment requires the characterization of RF spectrum attenuation and channel use. The WRC and 0BD propose a Spectrum Attenuation Reporting Sensor System (SARSS) that employs compressed sensing coupled to an array of ultra-wideband antennas, to perform precise, non-periodic sampling of the RF spectrum, characterizing the broadband spectrum attenuation, and disseminating, to local users or across a mesh network, an estimation of the usable channels.
Tagged as:
STTR
Phase I
2019
DOD
USAF
Innovative Low Flow Rate Energy Recovery System
Amount: $99,964 Topic: A17-089
The lack of potable water is widespread. The Army has portable seawater reverse osmosis (SWRO) desalination systems, however they are bulky, truck portable, energy expensive, and too large a scale for small unit level or the individual soldier.There is a need for a small scale, man-portableSWRO units. One impediment to creating this is the energy demands for SWRO systems. Large scale systems have developed energy recovery devices to reclaim the energy in the SWRO waste, these systems do not scale down to a man portable unit. This proposal outlines an innovative method to recover the SWRO waste energy, keep the system small and light, and allow flexibility for a wide range of water conditions and outputs. Using lightweight materials and nano-composite thin film coatings to both lubricate and protect the system from high salinities we propose a small energy recovery device.The system is driven by wastewater and input seawater pressurized to RO levels with a motor that supplies the necessary power above what is recovered. The system size and weight allows for development of a man portable, adaptable, desalinization system.
Tagged as:
SBIR
Phase I
2017
DOD
ARMY