Arnie Neidhardt

Telcordia Technologies, Middlesex, New Jersey, United States

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Publications (3)0 Total impact

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    ABSTRACT: The benefits of Global Positioning System (GPS) are recognized in numerous military as well as civilian applications. In many situations, however, GPS signals are simply not available or, at best, intermittently observable. This paper describes a novel location tracking system, called self-correcting adaptive tracking system (SATS), which focuses on solving group location problem when GPS is not available. In our location tracking system, we use a tracking mechanism that allows locating group members based on their pair wise distance information. A key innovation of SATS is that we use an adaptive search algorithm to find the new position estimate based on constraints given by the ranged data. In addition, our location tracking system is capable of extracting directional information normally unavailable in ranging system, which allows us to adaptively stabilize the orientation of the group. The SATS methodology has been prototyped and tested as part of an Office of Navy Research (ONR) program.
    Preview · Conference Paper · Dec 2008
  • A. Neidhardt · H. Luss · K.R. Krishnan
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    ABSTRACT: Modern technology can equip small devices (like mobile phones) with sensing-capabilities for various threats, offering a mobile, 'opportunistic' pool of secondary sensors that can be polled to augment the information provided by a pre-deployed set of primary sensors, to reduce uncertainty in threat-detection. We derive an optimal decision-rule for fusing the information from fixed and mobile, accounting for the costs of erroneous decisions. We also formulate a model for an 'equitable' solution to the problem of the optimal positioning of sensors.
    No preview · Conference Paper · Mar 2008
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    Arnie Neidhardt · Judith Jerkins · K. R. Krishnan
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    ABSTRACT: We present an analytical model and propose an efficient algorithm for evaluating call blocking in GSM networks with directed retry, where a call blocked by the sector of its initial attempt may be redirected to one or more alternative sectors. Since exact solution by Markov-chain analysis is unfeasible in large networks owing to the size of the state-space, we propose a method for an approximate solution, which is shown to be highly accurate in two small examples. .
    Full-text · Article · Jan 2008