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Shrestha A.,ARCON Corporation | Xing L.,University of Massachusetts Dartmouth | Coit D.W.,Rutgers University
IEEE Transactions on Reliability | Year: 2010

Multistate systems (MSS) are systems in which the system and its components are characterized by multiple states or performance levels. Component importance or sensitivity analysis facilitates the identification of vulnerabilities within the system, and aids in the quantification of criticalities of the system components. Multistate component importance analysis poses unique challenges to existing methods that are primarily based on binary-state applications. This paper presents an analytical method based on multistate multivalued decision diagrams (MMDD) for multistate component importance analysis. The contribution of this work is two-fold: 1) a novel, efficient algorithm for directly generating an MMDD model from multistate capacity network specifications without inefficient enumeration of multistate minimal path or cut vectors; and 2) an efficient, exact MMDD-based approach for evaluating MSS reliability and importance measures. The advantages of the proposed method are illustrated through a comparison with existing methods, and through detailed analyses of three case studies. © 2006 IEEE.

Li M.,ARCON Corporation | Kokar M.M.,Northeastern University
IEEE Transactions on Intelligent Transportation Systems | Year: 2010

This paper addresses the high computational complexity of generating multistep conflict resolution advisories (RAs) in air traffic control. Because this problem is known to be NP-hard, one cannot expect algorithms that will solve every instance of the problem independent of its size. Thus, the goal is to develop more efficient algorithms that can analyze a wider space of possible RAs, for instance, horizontal maneuvers. This paper presents a study of the use of abstraction to such a problem. However, abstractions can lead to wrong decisions, e.g., to maneuvers that result in unsafe states. Such abstractions are referred to as inconsistent. To avoid these kinds of problems, we use the so-called Q2 abstractions, which are derived from the specifications of a problem and are guaranteed to be consistent. To assess the usability of the Q2 approach to computing horizontal RAs, we analyze the impact of such abstractions on the computational cost of an exhaustive search algorithm and on the quality of RAs found. The results show that the use of the Q 2 approach lowers the conflict-resolution computation time without losing much of the quality of solutions. © 2006 IEEE.

Wu T.-J.,National Cheng Kung University | Chen P.,Syracuse University | Yan Y.,ARCON Corporation
Signal Processing | Year: 2013

We propose a consistent criterion WIC vc (vector corrected weighed average information criterion) for model order selection in multivariate linear regression models. The WIC vc is a weighted average of the asymptotically efficient criterion KIC vc (vector corrected Kullback information criterion) and the consistent criterion MBIC (multivariate Bayesian information criterion). The WIC vc behaves like KIC vc in small samples and behaves like MBIC in large samples. A numerical study comparing the performance of the proposed criterion with several available model selection criteria has been done. It shows that, over a wide range of small, moderate and large sample sizes, the WIC vc is more stable in comparison to other criteria in the study; that is, the WIC vc is either as good or comes in a strong second, whereas other criteria vary more in performance ranking. Therefore, the WIC vc is a very reliable and practical criterion. © 2012 Elsevier B.V.

Akcakaya M.,ARCON Corporation | Nehorai A.,Washington University in St. Louis
IEEE Transactions on Signal Processing | Year: 2011

We consider the effect of imperfect separability in the received signals on the detection performance of multi-input multi-output (MIMO) radar with widely separated antennas. The mutual orthogonality among the received signals is often assumed but cannot be achieved in practice for all Doppler and delay pairs. We introduce a data model considering the correlation among the data from different transmitter-receiver pairs as unknown parameters. Based on the expectation maximization algorithm, we propose a method to estimate the target, correlation, and noise parameters. We then use the estimates of these parameters to develop a statistical decision test. Employing the asymptotic statistical characteristics and the numerical performance of the test, we analyze the sensitivity of the MIMO radar with respect to changes in the cross-correlation levels of the measurements. We demonstrate the effect of the increase in the correlation among the received signals from different transmitters on the detection performance. © 2011 IEEE.

Akcakaya M.,ARCON Corporation | Muravchik C.H.,National University of La Plata | Nehorai A.,Washington University in St. Louis
IEEE Transactions on Signal Processing | Year: 2011

We propose to design a small-size antenna array having high direction-of-arrival (DOA) estimation performance, inspired by the Ormia ochracea's coupled ears. The female Ormia is able to locate male crickets' call accurately, for reproduction purposes, despite the small distance between its ears compared with the incoming wavelength. This phenomenon has been explained by the mechanical coupling between the Ormia's ears, modeled by a pair of differential equations. In this paper, we first solve the differential equations governing the Ormia ochracea's ear response, and convert the response to the prespecified radio frequencies. Using the converted response, we then implement the biologically inspired coupling as a multi-input multi-output filter on a uniform linear antenna array output. We derive the maximum likelihood estimates of source DOAs, and compute the corresponding Cramér-Rao bound on the DOA estimation error as a performance measure. We also consider a circular array configuration and compute the mean-square angular error bound on the three-dimensional localization accuracy. Moreover, we propose an algorithm to optimally choose the biologically inspired coupling for maximum localization performance. We use Monte Carlo numerical examples to demonstrate the advantages of the coupling effect. © 2011 IEEE.

Schindler J.K.,ARCON Corporation
IEEE International Symposium on Phased Array Systems and Technology | Year: 2013

We assess the usefulness of compressive sensing (CS) for processing signals from sparse or highly thinned receive arrays. Compressive sensing consists of a theory and related algorithms for solving under determined linear equations with the assumption that solutions have only a few non-zero or dominant values and the remaining values are zero or small. Sparse arrays are a natural application of CS when (a) there are only a few array observations with each expressed as a linear combination of the received plane wave signal amplitudes and (b) there are a large number of possible angles of arrival of signals but only a few signals are actually present. Our approach employs linear beamforming of the sparse array signals to create data for compressive sensing that are a linear combination of the plane wave signal amplitudes. The beamforming matrix serves to create coefficients in this linear combination that nearly orthonormal, a requirement for successful application of CS. We evaluate CS for the problem of a five element sparse array located on a 90° sector of a circular arc with large radius of curvature. Elements of the sparse array are themselves digitally beamformed phased arrays with main beams steered to a common direction. We found that compressive sensing works well for large signal to noise, reliably indicating the direction of arrival of a plane wave within the beamwidth of the phased array element and potentially reliable resolution of two equal intensity plane waves within one tenth of the beamwidth of the sparse array. False plane wave indications occur with significant probability when the signal to noise is small. However, an n or more of m indication algorithm with m statistically independent noise samples reduces significantly the probability of false indication. © 2013 IEEE.

An analysis is presented of scattering of an electromagnetic linearly polarized plane wave by a multilayered sphere. The focus is on obtaining a computational form of the Mie coefficients for the scattered field. A central role is played by ratios of spherical Bessel functions that can be calculated easily, rapidly, and accurately by recurrence relations whose stabilities are demonstrated. Logarithmic derivatives are not employed. A detailed outline is given of a carefully tested computer program for implementing and validating the analysis. Numerous comparisons are given of numerical results obtained with this program with corresponding results in the literature. Important properties of the Mie coefficients and aspects of the scattered field are discussed including the loci of the Mie coefficients in the complex plane; the resonances of the Mie coefficients; the extinction, scattering, and absorption efficiencies of the scattered field; radiation pressure; the Debye series, and the complex angular momentum (CAM) method. © 2015 IEEE.

Mailloux R.J.,ARCON Corporation
IEEE Antennas and Propagation Society, AP-S International Symposium (Digest) | Year: 2015

This paper addresses the use of displaced columns in an array with one plane of narrow scan and one with wide angle scan. It is demonstrated that this technique can significantly reduce the quantization lobes due to using large elements or subarrays with constant phase and amplitude in the columns. The technique is shown to impose no limit on bandwidth. © 2015 IEEE.

Mailloux R.J.,ARCON Corporation
IEEE Antennas and Propagation Society, AP-S International Symposium (Digest) | Year: 2014

This paper describes the developments that led to array scanning, with emphasis on the early years when scanning transitioned from concept to fact. The paper emphasizes the role that technology played in the time-line for this transition. © 2014 IEEE.

Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 99.92K | Year: 2010

The objective of this project is to design and demonstrate the feasibility of an innovative physical layer enhanced information fusion approach for real-time detection of air-to-air and ground-to-air spoofed ADS-B reports. The main components of our innovative system include: (1) physical layer based ADS-B spoofing detection; (2) onboard sensors based ADS-B spoofing detection; (3) ground ADS-B spoofing detection; (4) information fusion of multiple ADS-B spoofing detectors. Physical layer based ADS-B spoofing detection and Dempster-Shafer fusion are two core components of our proposed technique. Our algorithm is applicable to all airspaces no matter they are covered by radars/Multilateration or not. The physical layer based method can detect not only the spoofing attack in the air (spoof ADS-B report of aircraft), but also spoofing attack on the ground (spoof the ground station broadcasting). Our physical layer enhanced information fusion system for airborne ADS-B spoofing detection has wide military and commercial applications. BENEFIT: This innovative physical layer enhanced information fusion approach for detection of air-to-air and ground-to-air spoofed ADS-B reports has large potential applications for military and commercial platforms. The primary DoD applications include manned military aircraft, unmanned military aircraft, and helicopter. Our ADS-B spoofing detection technique can protect DOD aircraft from denial of aircraft access attacks via spoofed ADS-B reports. Commercial applications include civil aircraft and UAVs. It can be used directly in the Next Generation Air Transportation Systems (NextGen) to improve the safety, capacity, and efficiency of commercial flights.

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