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Company Information:

Company Name:
Signal Innovations Group, Inc.
Address:
4721 Emperor Blvd.
Suite 330
Durham, NC 27703-
Phone:
(919) 794-3322
URL:
EIN:
201104360
DUNS:
147201342
Number of Employees:
31
Woman-Owned?:
No
Minority-Owned?:
No
HUBZone-Owned?:
No

Commercialization:

Has been acquired/merged with?:
N/A
Has had Spin-off?:
N/A
Has Had IPO?:
N/A
Year of IPO:
N/A
Has Patents?:
N/A
Number of Patents:
N/A
Total Sales to Date $:
$ 0.00
Total Investment to Date $
$ 0.00
POC Title:
N/A
POC Name:
N/A
POC Phone:
N/A
POC Email:
N/A
Narrative:
N/A

Award Totals:

Program/Phase Award Amount ($) Number of Awards
SBIR Phase I $1,264,843.00 12
SBIR Phase II $7,810,681.00 10

Award List:

Database Expansion Issues

Award Year / Program / Phase:
2005 / SBIR / Phase I
Award Amount:
$99,042.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Abstract:
Software tools will be developed that define the underlying phenomenology of greatest importance to radar CID performance, allowing a trace back to the responsible target scattering physics. The proposed research entails development of algorithms that identify the target-sensor orientations (poses)… More

Sensor Exploitation by Adaptive/Learning Systems (SEALS)

Award Year / Program / Phase:
2005 / SBIR / Phase I
Award Amount:
$99,998.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Abstract:
Information-exploitation algorithms are proposed for Air Force sensing and weapons systems, motivated by the inevitable variability and differences seen between conventional training and testing data. Adaptive feedback is proposed, yielding an active-learning framework, wherein the algorithm… More

Sensor Exploitation by Adaptive/Learning Systems (SEALS)

Award Year / Program / Phase:
2006 / SBIR / Phase II
Award Amount:
$750,000.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Paul Runkle, COO/President
Abstract:
Signal Innovations Group (SIG) and its Fast Track partner, Integrian (www.integrian.com), propose development of an adaptive video sensing system, with a focus on intelligence, surveillance, and reconnaissance (ISR). The proposed adaptive system is applicable for ISR in general environments,… More

Database Expansion Issues

Award Year / Program / Phase:
2006 / SBIR / Phase II
Award Amount:
$745,943.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Paul Runkle, CEO/Director of Engineeri
Abstract:
State-of-the-art radar combat ID (CID) must address target identification in complex environments, often with very limited measured training data. Consequently, the algorithms frequently rely on data computed via numerical models, as a function of required sensor conditions (bandwidth,… More

Signal Processing and Exploitation for High-Dimensional Synthetic Aperture Radar (SAR)

Award Year / Program / Phase:
2006 / SBIR / Phase I
Award Amount:
$99,980.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Paul Runkle, Chief Executive Officer
Abstract:
We seek to address limitations of conventional 2D SAR imaging by investigating a new class of 3D imaging techniques that exploit the complicated non-planar relative rotation between a target and radar system. The proposed technique builds upon fundamental work on invariants from range-dependent… More

Efficiently Computing and/or Compensating for Object Variability in Automatic Target Recognition (ATR) Applications

Award Year / Program / Phase:
2007 / SBIR / Phase I
Award Amount:
$99,866.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Jonathan Woodworth, Principal Engineer II
Abstract:
There are numerous targets of interest to the Air Force that may be manifested in many different forms. For example, many ground targets may be configured with or without particular subcomponents, and such subcomponents may also be situated in different locations on a given target. Moreover, the… More

Efficiently Computing and/or Compensating for Object Variability in Automatic Target Recognition (ATR) Applications

Award Year / Program / Phase:
2008 / SBIR / Phase II
Award Amount:
$741,212.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Felix Lu, Vice-President
Abstract:
A research program is proposed on the integration of signal processing and electromagnetic modeling, to address the problem of performing ATR with targets possessing a high degree of variability. Sparseness is employed from two perspectives. First, in the signal processing component, sparse… More

In situ learning for underwater object recognition

Award Year / Program / Phase:
2009 / SBIR / Phase I
Award Amount:
$69,934.00
Agency / Branch:
DOD / NAVY
Principal Investigator:
Patrick Rabenold, Principal Engineer
Abstract:
We propose a principled in situ learning framework that is appropriate for a Bayesian classifier implemented with semi-supervised and multi-task learning. We will investigate several different forms of in situ learning, and will perform testing on measured data to help define which is most… More

CONTEXT-DRIVEN LANDMINE DETECTION USING SEMI-SUPERVISED MULTI-TASK LEARNING

Award Year / Program / Phase:
2010 / SBIR / Phase I
Award Amount:
$69,982.00
Agency / Branch:
DOD / ARMY
Principal Investigator:
Levi Kennedy, Vice President of Engineering
Abstract:
The proliferation of landmines continues to be a problem of worldwide humanitarian urgency. While airborne sensors have demonstrated significant utility in covering a wide area at a high stand-off distance, the variety of deployment methods, environments, mine types, and operating conditions… More

Exploiting Multipath for Efficient Target Classification

Award Year / Program / Phase:
2010 / SBIR / Phase I
Award Amount:
$79,796.00
Agency / Branch:
DOD / NAVY
Principal Investigator:
James Baxter, Engineer 4
Abstract:
Automatic target recognition(ATR) for tactical military targets is a very challenging problem, particularly when the number of observed aspects of a target is subject to the operational constraints of the sensor platform. When the target is situated in the presence of a complicated background… More

In situ learning for underwater object recognition

Award Year / Program / Phase:
2010 / SBIR / Phase II
Award Amount:
$1,453,945.00
Agency:
DOD
Principal Investigator:
Patrick Rabenold, ENG 3 – (919) 323-3452
Abstract:
In the proposed Phase II program, the methods developed and implemented during Phase I research will be fully integrated within a common Bayesian in situ learning framework. We have developed several Bayesian classifiers, to which we will apply label acquisition and label confidence techniques.… More

Signal Processing and Exploitation for High-Dimensional Synthetic Aperture Radar (SAR)

Award Year / Program / Phase:
2010 / SBIR / Phase II
Award Amount:
$746,065.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Paul Runkle, President
Abstract:
A probabilistic ATR framework is proposed to exploit coincident multi-aspect radar and EO video data for target detection, tracking, and classification/identification. The mathematical framework is constituted by four principal components with a particular focus on exploitation of 3D information… More

Performance Prediction of Feature Aided Trackers using Persistent Sensors

Award Year / Program / Phase:
2011 / SBIR / Phase I
Award Amount:
$97,310.00
Agency:
DOD
Principal Investigator:
Jonathan Woodworth, Vice President/Engineer 5 – (919) 323-3450
Abstract:
The proposed Phase I program will develop a Bayesian framework for modeling and predicting track uncertainty and performance as a function of OCs and integrate this framework with algorithms for tracking vehicles in WAMI. The proposed Performance and Uncertainty Modeling and Prediction for Tracking… More

Detection, Tracking, and Classification of Dismounts

Award Year / Program / Phase:
2011 / SBIR / Phase I
Award Amount:
$99,285.00
Agency:
DOD
Principal Investigator:
Chris Lunsford, Engineering Technical Lead – (919) 323-3407
Abstract:
Situational awareness is paramount when conducting operations in potentially hostile terrain. Vehicle operators must focus on multiple tasks simultaneously: navigation, collision avoidance, location of possible IED threats, and identification of dismount threats. Fatigue and distractions affect… More

CONTEXT-DRIVEN LANDMINE DETECTION USING SEMI-SUPERVISED MULTI-TASK LEARNING

Award Year / Program / Phase:
2011 / SBIR / Phase II
Award Amount:
$773,820.00
Agency:
DOD
Principal Investigator:
Levi Kennedy, Engineer 5 – (919) 323-3456
Abstract:
Fully automated approaches to target detection are efficient at processing large amounts of data but often rely heavily on the training data and the model employed. Training data and modeling assumptions can be violated in the operational environments where the algorithms are applied. Alternatively,… More

High Range Resolution (HRR)-Surrogate SAR Target Identification

Award Year / Program / Phase:
2012 / SBIR / Phase I
Award Amount:
$149,940.00
Agency:
DOD
Principal Investigator:
Jim Baxter, Engineer 4 – (919) 323-3453
Abstract:
ABSTRACT: The Air Force has invested considerable resources into collecting and synthesizing radar data for training and testing ATC/R systems. Significant cost savings may be realized if these existing datasets may be leveraged for training new sensors and modalities. Signal Innovations Group… More

Interactive Generative Manifold Learning

Award Year / Program / Phase:
2013 / SBIR / Phase I
Award Amount:
$149,903.00
Agency:
DOD
Principal Investigator:
Patrick Rabenold, Engineer 4 – (919) 323-3452
Abstract:
Signal Innovations Group proposes a hierarchical Bayesian approach for non-linear dimensionality reduction that addresses three key challenges: learning a reversible mapping from a high-dimensional observed space to a low-dimensional embedded space, learning the dimension of the embedded space, and… More

Detection, Tracking, and Classification of Dismounts

Award Year / Program / Phase:
2013 / SBIR / Phase II
Award Amount:
$599,960.00
Agency:
DOD
Principal Investigator:
Mark Kolba, ENG 3 – (919) 794-3750
Abstract:
The detection and tracking of dismounts and the identification of threatening dismounts are critical challenges for ensuring mission success and troop safety when conducting tactical vehicle operations in hostile environments. Vehicle operators must focus on multiple tasks simultaneously: … More

New Radar Exploitation Methods for Combat Identification

Award Year / Program / Phase:
2013 / SBIR / Phase I
Award Amount:
$149,807.00
Agency:
DOD
Principal Investigator:
James Baxter, Principal Engineer – (919) 323-3453
Abstract:
ABSTRACT: Current automatic target recognition (ATR) training processes require expensive data collections or extensive, high fidelity target modeling and validation whose costs and lead times will limit the ongoing sustainability of ATR target databases. Radar based systems for combat… More

High Range Resolution (HRR)-Surrogate SAR Target Identification

Award Year / Program / Phase:
2013 / SBIR / Phase II
Award Amount:
$749,797.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Jim Baxter, ENGINEER 4 – (919) 323-3453
Abstract:
ABSTRACT: This program will develop salient feature analysis and saliency cueing capabilities for SAR-based exploitation and demonstrate this technology with operationally relevant data and classifiers. This saliency technology will immediately enable the development of exploitable, robust,… More

Interactive Generative Manifold Learning

Award Year / Program / Phase:
2014 / SBIR / Phase II
Award Amount:
$499,985.00
Agency / Branch:
DOD / NAVY
Principal Investigator:
Patrick Rabenold, Principal – (919) 323-3452
Abstract:
Signal Innovations Group (SIG) proposes a Phase II program that addresses three primary capabilities for applications involving high-dimensional observed data: reversible nonlinear data dimensionality reduction, static and dynamic synthesis of data in the observed space based on a low-dimensional… More

New Radar Exploitation Methods for Combat Identification

Award Year / Program / Phase:
2014 / SBIR / Phase II
Award Amount:
$749,954.00
Agency / Branch:
DOD / USAF
Principal Investigator:
Jim Baxter, Principal Engineer – (919) 323-4813
Abstract:
ABSTRACT: The Phase II program will develop and mature a new salient physics-driven solution for CID feature design and classification to support onboard CID and decision fusion for remotely piloted vehicles. Saliency analysis will be used to develop databases of compact, simple geometric features… More