Imaging Method Based on Time Reversal Channel Compensation
Author(s) -
Bing Li,
BinJie Hu
Publication year - 2015
Publication title -
international journal of antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.282
H-Index - 37
eISSN - 1687-5877
pISSN - 1687-5869
DOI - 10.1155/2015/894608
Subject(s) - signal (programming language) , transceiver , computer science , lossy compression , compensation (psychology) , lossless compression , channel (broadcasting) , spurious relationship , algorithm , position (finance) , amplitude , function (biology) , electronic engineering , artificial intelligence , wireless , engineering , optics , telecommunications , physics , psychology , finance , data compression , machine learning , evolutionary biology , psychoanalysis , economics , biology , programming language
The conventional time reversal imaging (TRI) method builds imaging function by using the maximal value of signal amplitude. In this circumstance, some remote targets are missed (near-far problem) or low resolution is obtained in lossy and/or dispersive media, and too many transceivers are employed to locate targets, which increases the complexity and cost of system. To solve these problems, a novel TRI algorithm is presented in this paper. In order to achieve a high resolution, the signal amplitude corresponding to focal time observed at target position is used to reconstruct the target image. For disposing near-far problem and suppressing spurious images, combining with cross-correlation property and amplitude compensation, channel compensation function (CCF) is introduced. Moreover, the complexity and cost of system are reduced by employing only five transceivers to detect four targets whose number is close to that of transceivers. For the sake of demonstrating the practicability of the proposed analytical framework, the numerical experiments are actualized in both nondispersive-lossless (NDL) media and dispersive-conductive (DPC) media. Results show that the performance of the proposed method is superior to that of conventional TRI algorithm even under few echo signals
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