An Assessment of Indoor Geolocation Systems

Currently there is a need to design, develop, and deploy autonomous and portable indoor geolocation systems to fulfil the needs of military, civilian, governmental and commercial customers where GPS and GLONASS signals are not available due to the limitations of both GPS and GLONASS signal structure designs. The goal of this dissertation is (1) to introduce geolocation systems; (2) to classify the state of the art geolocation systems; (3) to identify the issues with the state of the art indoor geolocation systems; and (4) to propose and assess four WPI indoor geolocation systems. It is assessed that the current GPS and GLONASS signal structures are inadequate to overcome two main design concerns; namely, (1) the near-far effect and (2) the multipath effect. We propose four WPI indoor geolocation systems as an alternative solution to near-far and multipath effects. The WPI indoor geolocation systems are (1) a DSSS/CDMA indoor geolocation system, (2) a DSSS/CDMA/FDMA indoor geolocation system, (3) a DSSS/OFDM/CDMA/FDMA indoor geolocation system, and (4) an OFDM/FDMA indoor geolocation system. Each system is researched, discussed, and analyzed based on its principle of operation, its transmitter, the indoor channel, and its receiver design and issues associated with obtaining an observable to achieve indoor navigation. Our assessment of these systems concludes the following. First, a DSSS/CDMA indoor geolocation system is inadequate to neither overcome the near-far effect not mitigate cross-channel interference due to the multipath. Second, a DSSS/CDMA/FDMA indoor geolocation system is a potential candidate for indoor positioning, with data rate up to 3.2 KBPS, pseudorange error, less than to 2 m and phase error less than 5 mm. Third, a DSSS/OFDM/CDMA/FDMA indoor geolocation system is a potential candidate to achieve similar or better navigation accuracy than a DSSS/CDMA indoor geolocation system and data rate up to 5 MBPS. Fourth, an OFDM/FDMA indoor geolocation system is another potential candidate with a totally different signal structure than the pervious three WPI indoor geolocation systems, but with similar pseudorange error performance

Generalized Parabolic Cylinder Function Distribution

), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use of the publication of trade names, trademarks, service marks, or similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. This paper discussed generalized parabolic cylinder function (or GPCF) distribution i (or GPCFD) probability density function (pdf) in a manner that is original and never presented before in the literature. For GPCF the closed form expression of the cumulative distribution function (cdf) is given by means of series expansion of the four Kampé de Fériet functions and six confluent hypergeometric series of two variables. Numerical results are derived for each case to validate the theoretical models presented in the paper

BIOGRAPHY

graduate courses and conducts research in the field of navigation and wireless communications. Dr. Progri was the Program Co-Chair for the Wireless Telecommunications Symposium 2006 and 2005 respectively. He was the faculty advisor of the ION-Cal Poly Pomona student chapter of the ION-So Cal section the 1 st student ION chapter in LA area. He is a member of ION, RIN, and AIG and a senior member of the IEEE

BIOGRAPHY

graduate courses and conducts research in the field of navigation and wireless communications. Dr. Progri was the Program Co-Chair for the Wireless Telecommunications Symposium 2006 and 2005 respectively. He was the faculty advisor of the ION-Cal Poly Pomona student chapter of the ION-So Cal section the 1 st student ION chapter in LA area. He is a member of ION, RIN, and AIG and a senior member of the IEEE

Maximum-likelihood GPS parameter estimation

ABSTRACT: Recently we proposed an acquisition process for a maximum-likelihood GPS receiver that considers the joint processing of all GPS satellite waveforms. The resulting estimator was shown to provide an elegant solution to the near -far problem and to perform better than the suboptimal sliding-correlator estimator. However, the proposed acquisition model included only the code search, which estimates just the time of arrival (TOA) between a GPS satellite and a maximum-likelihood GPS receiver. In this paper we enhance the acquisition process by including the estimation of Doppler along with the estimation of the TOA, which results in a two-dimensional Doppler and code search. A maximum-likelihood GPS receiver would require only one front-end hardware section for processing all GPS signals in view, thus simplifying the entire architecture of a GPS receiver. An assessment based on theoretical performance and simulation results indicates that a maximum-likelihood GPS receiver can achieve an order-of-magnitude performance improvement relative to a sliding-correlator GPS receiver. Simulation data will be validated in the near future using GPS acquisition data from the Novatel ProPack AG-G2ϩDB9-RT2 , and the results of this work will be presented in a future publication

A Solution to the Recursive Generalized Eigenvalue Problem

Dr. Matthew Bromberg is an independent consultant. For the last 6 years Dr. Bromberg has been involved in the research and development of array processing algorithms for reuse enhancement for wireless communication systems and for interference mitigation for both commercial and military applications while he was at Radix Technologies. Dr. Bromberg was a key inventor of the technology that led to the formation and funding of Beam Reach Networks and the formation of Protean Radio Networks. He has authored several papers and patents in this area. Abstract Previously, we have discussed a recursive solution to the vector normal equation utilizing the recursive Cholesky and Modified Gram-Schmidt Orthogonalization (MGSO) algorithms. Previously, we have also discussed a blind adaptive approach for detection and extraction of signals of interest in the presence of noise and interference without relying on preamble or training sequences. The heart of the blind adaptive algorithm is based upon solving the recursive generalized eigenvalue problem, the solution of which is discussed in this paper based on the recursive Cholesky or QR factors and the Householder and QL algorithm with implicit shifts. Even though, the solution to the recursive generalized eigenvalue problem is slightly more efficient than the solution to the direct generalized eigenvalue when all the eigenvalues and eigenvectors are required, the improvement is more noticeable when only one eigenvalue and the corresponding eigenvector are required. Therefore, the solution that is proposed here serves well for recursive generalized eigenvalue problems that require only one eigenvalue and the corresponding eigenvector