Rome, NY, United States

ANDRO Computational Solutions, LLC

www.androcs.com
Rome, NY, United States
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Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase I | Award Amount: 150.00K | Year: 2015

ABSTRACT: The focus of this research will be on developing a model and associated computational tool called HPEM-Expert that is consistent with the Directed RF Energy Assessment Model 2, (DREAM2), which describes and predicts the effects of a high-power electromagnetic (HPEM) signal on a mobile target, to improve on the existing DREAM tool. Our approach will be to develop a modeling and simulation (M&S) based capability that is compatible with and enhances the DREAM framework and methodology. A proven toolkit framework design will be used that employs an innovative fault-tree based Sneak Circuit Analysis (SCA) approach to demonstrate the feasibility of the proposed concept to successfully function in a relevant scenario provided by the government. This framework will combine computational electromagnetics (CEM) solvers with a circuit solver and an SCA module to provide a solid foundation for establishing accurate front-door and back-door coupling models. This will set the stage for Phase II during which we will refine the framework and develop and demonstrate the failure analysis process as well as validate the new capability through detailed component testing and simulation. The initial product to be developed and demonstrated in Phase I will lead to a mature capability that will increase the Air Forces ability to protect its own electronic systems from HPEM effects, as well as to determine the level of damage incurred by/to potential adversaries.; BENEFIT: The product of this STTR project will increase the Air Forces ability to protect its own electronic systems from HPEM events. The commercial sector can also similarly benefit from the technology. For example, the EMI problems encountered on military aircraft are also a serious problem for the commercial airline industry. Commercial aircraft manufacturers currently use relatively crude codes (e.g., spreadsheets) or "back of the envelope" calculations to study EMI and safety problems associated with incident fields from ground radars and other high power sources. Such a sophisticated tool will allow for much greater accuracy and efficiency, which will in turn provide significant time and cost savings as well as enhance safety. Optimizing the design, performance, and application of HPEM-Expert can ultimately help to promote company competitiveness and productivity in these market niches. Also, as a result of the universal need for wireless communication and information collection, there is an increasing need for robust and hardened complex information systems to be integrated on host platforms.


Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase II | Award Amount: 749.86K | Year: 2012

ABSTRACT: The ultimate objective of the joint effort is to develop technology that will enable next-generation cognitive wireless networking between USAF space, air, and ground assets and achieve significant improvement in network throughput, delay, and reliability. Current practices that evolve around standard ad hoc networking techniques based on the layered protocol stack with fixed spectrum allocation are known to offer inadequate throughput and reliability in highly dynamic adversarial communication environments such as the space/air/ground USAF domain. The objective of this project is therefore to investigate, study, and demonstrate a completely new approach to joint routing and spectrum allocation. While the core of cognitive radio network proposals rely on the notion of spectrum hole, i.e., radios attempt to find a single unused band which can be opportunistically used by secondary users, in the work outlined in this report cognitive users transmit wideband spread-spectrum signals that are designed to adaptively avoid the interference dynamics of the available spectrum at the receiver. BENEFIT: If we are successful, we will implement and demonstrate the dynamic network control technology that will be instrumental towards developing the next generation cognitive networking technology between USAF space, air, and ground assets and achieve a significant improvement in network throughput, delay, and reliability.


Grant
Agency: Department of Defense | Branch: Air Force | Program: STTR | Phase: Phase I | Award Amount: 150.00K | Year: 2015

ABSTRACT: Our goal is to develop theoretical frameworks for efficient multisensor fusion of high dimensional data for target detection localization and tracking. We plan to develop novel algorithms based upon our previous research on copula theory to perform inference with multi-modal correlated sensor data. Copulas describes the dependence between random variables and allow one to optimally exploit the inherent low-dimensional characteristics of high dimensional data. They are popular in high-dimensional statistical applications as they allow one to easily model and estimate the distribution of random vectors by estimating marginals and copulae separately. There are many parametric copula families available that capture more information than traditional approaches while still maintaining low data communication rates to the central fusion center. We will evaluate achievable performance limits of the developed algorithms and compare the efficiency to several benchmark algorithms. Testing will be performed on physics based simulated data sets. The benchmark techniques we will consider will include conventional fusion of Kalman state spaces, principal component analysis (PCA) based methods and parametric likelihood-based approaches. The research output is expected to have significant implications in coping with the data deluge problem at individual sensors employed for detection, estimation and tracking in sensor and radar networks. ; BENEFIT: The proposed approach will permit improved sensor fusion of heterogeneous data sets with only a small increase in communication requirements over traditional fusion approaches. The technology benefits Air Force ISR and missile defense systems. Commercial applications include aviation radar systems as well as emerging multisensor systems.


Grant
Agency: Department of Defense | Branch: Army | Program: SBIR | Phase: Phase II | Award Amount: 1000.00K | Year: 2012

This effort considers the problem of Automatic Modulation Classification (AMC) using multiple asynchronous sensors in non-cooperative environments under low signal-to-noise ratio (SNR) regimes. The goal is to improve and demonstrate the performance of AMC systems on various weak signal scenarios in a multi-cast environment that a traditional single sensor would not be able to readily classify. Candidate approaches involve both distributed decision fusion as well as centralized data fusion of asynchronous sensor data for multi-hypothesis modulation classification. This effort will build upon the results of a prior phase study, where the asymptotic behavior of distributed modulation classification systems was analyzed and conditions under which asymptotic probability of error goes to zero were derived. Upper and lower bounds for probability of error were derived based on Chernoff and Bhattacharyya error exponents and Monte Carlo sampling techniques. The optimal fusion rule for multi-hypothesis testing was developed and comparisons were carried out with the majority fusion rule. A maximum likelihood based centralized fusion problem was also formulated where each sensor experiences a different SNR and the network is asynchronous, i.e. each sensor has a non-identical phase, frequency and timing offset. In this effort, a novel centralized data fusion algorithm with multiple asynchronous sensors will be developed. The problem of asynchronous sensor data fusion for AMC using multiple sensors is considered untapped. A novel Distributed Automatic Modulation Classification (DAMC) technology and innovative approach are presented that exploits asynchronous multiple sensor data in the most effective way possible for this purpose. For distributed fusion, the proposed technology, based on a theoretical understanding of independence and dependence (Copula theory), will enable the development of novel fusion methodologies for maximized classification performance. Additionally, for time critical applications, sequential classification procedures will be explored. Time and computational complexity are also considered in proposed algorithms in view of limited computational resources. New algorithms will be developed and existing ones will be enhanced in this phase, along with trials for distributed signal sensing. Classification hardware prototypes will be tested and a robustness test of the new methods will be presented. The development of real-time software implementing this system will be produced and demonstrated. The completion of this phase will result in a mature DAMC technology, which will be inserted into selected hardware and undergo operational tests with real world signal transmission and reception in a fully functional, distributed sensor network.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 149.96K | Year: 2013

This proposed research is to investigate and validate Software Defined Radio (SDR) based, multi-function portable network sensing and intrusion detection algorithms suitable for small dismounted radio platforms used to support Command and Control (C2) standard sensor interfaces carried in the field and for sensor data exfiltration. A new capability called Transmission Cyberspace is proposed that will enable DoD military SDRs in the battlefield that are in close proximity to hostile foreign networks to be cognizant of their surrounding radio frequency (RF) environment. A novel and robust network discovery capability will be developed to rapidly assess the potential for RF intrusion, cyber attacks or other unauthorized access to SDRs and Cognitive Radio and Sensor Networks (CRSNs) along with implementing effective defense strategies. This will be accomplished through the application of a suite of algorithms that fundamentally exploit the multidimensional and joint orthogonal nature of the RF signal space. A hybrid class of algorithms and techniques will be used, namely: multiobjective optimization, game theory, spectrum sense and adapt, distributed detection, joint cognitive routing and spread-spectrum channelization, and automated modulation classification. A unique physical (PHY) layer protection scheme is then used to thwart attacks and to augment upper layer (data, MAC, network) multi-level security methods to deny cyber attacks and to ensure secure communications and trusted network routing. These algorithms will leverage the SDR"s ability to sense the presence of other wireless networks, monitor those networks and detect when and where hostile intrusion attempts might arise.


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: SBIR | Phase: Phase II | Award Amount: 975.00K | Year: 2014

In Phase I, our team applied their extensive experience in this area to develop and implement a unified target characterization and correlation framework focused on sensor hand-over (SHO) between electro-optic/infrared (EO/IR) and radar. The SHO system is designed to operate in an environment with multiple heterogeneous sensors where detection, classification and localization information is exchanged among multiple platforms. Our ultimate goal is to transition an effective sensor hand-over module based upon an automated and autonomous information extraction and fusion suite. We have developed a unique multi-frame assignment based approach that works with tightly coupled target characterization and track correlation. In order to get the best out of all available RF and EO/IR sensors, we have developed meta-features that are both invariant to sensor type and also amenable for optimal track correlation across sensors. We have also developed efficient fusion or correlation algorithms based upon these pseudo-features that yield better common tracks and facilitate accurate track hand-over. Approved for Public Release 14-MDA-7739 (18 March 14).


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase II | Award Amount: 149.43K | Year: 2014

This research effort is to develop a tool to model the electromagnetic vulnerability/interference (EMV/I) of electronic systems, subsystems and components to directed-energy HPM weapons. A complete HPM-Expert conceptual framework has been developed for performing simulation-based failure analyses that establishes HPM weapons"effects on targeted electronics associated with both front- and back-door coupling paths (e.g., communications systems, electro-optical/infrared sensors, Global Positioning Systems, inertial navigation systems, and processors). The focus is on device/component/circuit-level EMV/I and quantifying associated disturbance, disruption, or damage (DDD) thresholds. A combination of system-level analytical and numerical tools, statistical electromagnetics, domain decomposition, and sneak circuit analysis (SCA) techniques are integrated and applied to address this problem in the frequency domain and which can be extended into the time domain. This will lead to a mature capability that will increase the Navy"s ability to protect its own electronic systems from HPM attack, as well as to determine the level of damage incurred by the enemy. The objective of this proposed effort is two-fold: (i) develop a pre-prototype HPM-Expert computer modeling and simulation capability based on the refined conceptual framework and demonstrate it on a sample challenge problem to be postulated by the government; and (ii) develop a working prototype capability that integrates the various algorithms and tools into a single, stand-alone package consisting of an analytical approach and process definition that can be readily transitioned for use in selected military Programs of Record as well as commercialized in cooperation with one or more technology transition partners.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 80.00K | Year: 2014

This Phase I proposal for unclassified basic research and exploratory development titled Mitigation of Military Communication and Radar System Interference from Current and Future Fixed and Mobile Wireless Broadband Systems: Interference Resilient Waveforms is submitted in response to Department of Defense SBIR Program Solicitation Number 14.2, Topic N142-106. This proposal outlines an innovative cooperative research and development effort headed by ANDRO Computational Solutions, LLC with commercial communication systems consultant Dr. Liu, and advanced radar and JSF advisor from Lockheed Martin Dr. Kryzak. The team will develop a solution enabling air-to-air missions at low altitudes in the environment with in-band interference from Unlicensed National Information Infrastructure (UNII). We will propose waveforms effective in heavily occupied relevant RF spectrum, inundated with dynamic composite signals of various encoding and modulations. In addition to waveform designs, for a multi-tiered interference mitigation, our concept considers deception and signal exploitation techniques, aimed to invoke favorable UNII response and fortuitous RF illumination/shadowing respectively. The team will develop waveform designs suitable for use in Navy airborne radar systems operating in the presence of UNII devices and an implementation plan showing how the techniques can be integrated into the radar system and extended for use in airborne data link systems.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase II | Award Amount: 881.00K | Year: 2014

This effort proposes to customize ANDROs Transmission Cyberspace (TC) concept developed in Phase I for rapid installation on the prototype SDR hardware and testing in a small network configuration in tactical environment. Three modules Cyber, ISR Force Protection and DSA will be derived from TC and ported to Thales SIGINT/EW Mission Module (SEMM) that attaches to the tactical radio AN/PRC-148B MBITR2. The five-node network tests will demonstrate technical capabilities of SDRs networked via SRW. These capabilities are expected to enable enhanced situational awareness and cyber protection of our forward deployed forces relying on a small network of radios. The first demo is scheduled at Thales extensive networks communication facility. For visualization we will leverage RadiantBlues ROVER display capability. Two laboratory tests will be followed by two field demonstrations at the Aberdeen Proving Grounds and Fort Benning, GA in March and June 2015. The laboratory tests and the demonstrations will be configured as up to a five-node network in increasingly representative tactical environments.


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: SBIR | Phase: Phase I | Award Amount: 150.00K | Year: 2013

We propose to develop and implement a set of algorithms within a unified target characterization and correlation framework capable of operating in a multiple heterogeneous sensor environment where detection, classification, localization and track priority information is exchanged among multiple platforms. Our goal is to deliver an effective automated and autonomous information extraction and fusion system that can be incorporated in today"s operational systems. The primary focus will be on the development of algorithms for target characterization and correlation that can handle the difficult track handover between PTSS EO/IR boost phase detection sensors and weapon control sensors such as Aegis or AN/TPY-2. Information fusion with heterogeneous sensors is challenging because non-kinematic features are different for each sensor type making it is difficult to correlate features across sensors. Thus, it is necessary to develop meta-features that are sensor invariant and amenable to optimal track correlation across sensors. Once this target characterization is carried out effectively, the next task is to develop efficient fusion or correlation algorithms that can yield better common tracks and facilitate accurate track hand-over. In our approach, target characterization (information extraction) and correlation (information fusion) are tightly coupled problems that are addressed jointly to ensure optimal overall performance.

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