Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.

In this paper, we address the problem global positioning system (GPS) signals tracking in low signal-to-noise ratio (SNR) and multipath plus interference environments using a two-step approach: a block-averaging pre-processing (BAP) which converts the zero-mean interferences to colored Gaussian noise and a maximum likelihood (ML) based algorithm combined with a whitening transform. We apply the recently proposed BAP technique to improve the SNR. For code tracking with multipath mitigation, we exploit the fact that during a period with no data bit edges, the propagation delay causes only a circular shift to the C/A code block. This allows the decomposition of the averaged data vector into a constant C/A code component plus an undesired signal component. An efficient temporal whitening transform is derived from the sample covariance matrix and applied to suppress strong colored interferers, rendering the ML estimation problem of the multipath parameters tractable. A computationally efficient procedure for solving the complex ML optimization problem is considered using a finite difference maximization technique. By estimating the multipath signals and subtracting their contributions in a sequential scheme, the code synchronization is achieved. The resulting robust ML (RML) tracking procedure is more efficient in mitigating multipath and non-Gaussian interferences. The performance of the developed RML receiver is evaluated through computer simulations to show its superiority over that of narrow correlator and MEDLL approach.

Main Author: Sahmoudi, M.
Other Authors: Amin, Moeness G.
Format: Villanova Faculty Authorship
Language: English
Published: 2009
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:173600
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dc_source_str_mv Signal Processing, Volume 89, Issue 7, July 2009.
author Sahmoudi, M.
author_facet_str_mv Sahmoudi, M.
Amin, Moeness G.
author_or_contributor_facet_str_mv Sahmoudi, M.
Amin, Moeness G.
author_s Sahmoudi, M.
spellingShingle Sahmoudi, M.
Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
author-letter Sahmoudi, M.
author_sort_str Sahmoudi, M.
author2 Amin, Moeness G.
author2Str Amin, Moeness G.
dc_title_str Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
title Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
title_short Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
title_full Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
title_fullStr Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
title_full_unstemmed Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
collection_title_sort_str robust tracking of weak gps signals in multipath and jamming environments.
title_sort robust tracking of weak gps signals in multipath and jamming environments.
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description In this paper, we address the problem global positioning system (GPS) signals tracking in low signal-to-noise ratio (SNR) and multipath plus interference environments using a two-step approach: a block-averaging pre-processing (BAP) which converts the zero-mean interferences to colored Gaussian noise and a maximum likelihood (ML) based algorithm combined with a whitening transform. We apply the recently proposed BAP technique to improve the SNR. For code tracking with multipath mitigation, we exploit the fact that during a period with no data bit edges, the propagation delay causes only a circular shift to the C/A code block. This allows the decomposition of the averaged data vector into a constant C/A code component plus an undesired signal component. An efficient temporal whitening transform is derived from the sample covariance matrix and applied to suppress strong colored interferers, rendering the ML estimation problem of the multipath parameters tractable. A computationally efficient procedure for solving the complex ML optimization problem is considered using a finite difference maximization technique. By estimating the multipath signals and subtracting their contributions in a sequential scheme, the code synchronization is achieved. The resulting robust ML (RML) tracking procedure is more efficient in mitigating multipath and non-Gaussian interferences. The performance of the developed RML receiver is evaluated through computer simulations to show its superiority over that of narrow correlator and MEDLL approach.
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dc.title Robust Tracking of Weak GPS Signals in Multipath and Jamming Environments.
dc.creator Sahmoudi, M.
Amin, Moeness G.
dc.description In this paper, we address the problem global positioning system (GPS) signals tracking in low signal-to-noise ratio (SNR) and multipath plus interference environments using a two-step approach: a block-averaging pre-processing (BAP) which converts the zero-mean interferences to colored Gaussian noise and a maximum likelihood (ML) based algorithm combined with a whitening transform. We apply the recently proposed BAP technique to improve the SNR. For code tracking with multipath mitigation, we exploit the fact that during a period with no data bit edges, the propagation delay causes only a circular shift to the C/A code block. This allows the decomposition of the averaged data vector into a constant C/A code component plus an undesired signal component. An efficient temporal whitening transform is derived from the sample covariance matrix and applied to suppress strong colored interferers, rendering the ML estimation problem of the multipath parameters tractable. A computationally efficient procedure for solving the complex ML optimization problem is considered using a finite difference maximization technique. By estimating the multipath signals and subtracting their contributions in a sequential scheme, the code synchronization is achieved. The resulting robust ML (RML) tracking procedure is more efficient in mitigating multipath and non-Gaussian interferences. The performance of the developed RML receiver is evaluated through computer simulations to show its superiority over that of narrow correlator and MEDLL approach.
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