Least-Squares-Based Iterative Multipath Super-Resolution Technique

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In this paper, we investigate the multipath resolution problem for direct sequence spread spectrum signals. To resolve multipath components arriving within a very short interval, we propose a new multipath super-resolution algorithm based on the iterative least-squares method. The proposed least-squares-based iterative multipath super-resolution (LIMS) algorithm exploits a triangular shaped auto-correlation function (ACF) of the pseudonoise (PN) sequence and simplifies the least-squares parameter estimation procedure using iterative and algebraic operations. This results in an algorithm demanding low computational load with a high multipath resolution capability. It is also discussed that the LIMS algorithm can be applied for recursive multipath tracking of source localization systems, such as the global navigation satellite systems (GNSS). Simulation results show that the LIMS algorithm maintains its good performance even in a low C/N-0 or severe multipath interference conditions.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2013-02
Language
English
Article Type
Article
Keywords

PN-CORRELATION METHOD; PARAMETER-ESTIMATION; MAXIMUM-LIKELIHOOD; GENERALIZED THEORY; DELAY ESTIMATION; CODE TRACKING; PART I; ALGORITHM; SIGNALS; MODEL

Citation

IEEE TRANSACTIONS ON SIGNAL PROCESSING, v.61, no.3, pp.519 - 529

ISSN
1053-587X
DOI
10.1109/TSP.2012.2225056
URI
http://hdl.handle.net/10203/174584
Appears in Collection
GT-Journal Papers(저널논문)
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