Cognitive Waveform Design for Radar-Communication Transceiver Networks

The system architecture for cognitive radar-communication (CRC) transceiver is proposed. A cognitive waveforms design approach, which is suitable for simultaneously performing both data communication and target detection, is presented. This approach aims at estimating target scattering coefficient (...

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Main Authors: Yu Yao, Lenan Wu
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2018/4182927
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author Yu Yao
Lenan Wu
author_facet Yu Yao
Lenan Wu
author_sort Yu Yao
collection DOAJ
description The system architecture for cognitive radar-communication (CRC) transceiver is proposed. A cognitive waveforms design approach, which is suitable for simultaneously performing both data communication and target detection, is presented. This approach aims at estimating target scattering coefficient (TSC) from the radar scene and facilitating high data rate communications. In order to minimize the mean square error (MSE) of the TSC, a convex cost function is established. The peak to average power ratio- (PAPR-) constrained optimal solution is achieved by applying the Kalman filtering-based strategy to design the set of ultra-wideband (UWB) transmission pulses and embed into them the information data with the M-ary position phase shift keying modulation technique. In addition to theoretical considerations, the simulation results show an improvement in target scattering coefficient (TSC) estimation and target detection probability as the number of iterations increases, while still transmitting data rates in the range of several Mbps with low bit error rates between CRC transceivers.
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institution Kabale University
issn 0197-6729
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language English
publishDate 2018-01-01
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series Journal of Advanced Transportation
spelling doaj-art-64af2cf95f0347ed892844fb593f81d12025-02-03T06:11:08ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/41829274182927Cognitive Waveform Design for Radar-Communication Transceiver NetworksYu Yao0Lenan Wu1School of Information Engineering, East China Jiaotong University, Nanchang 330031, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaThe system architecture for cognitive radar-communication (CRC) transceiver is proposed. A cognitive waveforms design approach, which is suitable for simultaneously performing both data communication and target detection, is presented. This approach aims at estimating target scattering coefficient (TSC) from the radar scene and facilitating high data rate communications. In order to minimize the mean square error (MSE) of the TSC, a convex cost function is established. The peak to average power ratio- (PAPR-) constrained optimal solution is achieved by applying the Kalman filtering-based strategy to design the set of ultra-wideband (UWB) transmission pulses and embed into them the information data with the M-ary position phase shift keying modulation technique. In addition to theoretical considerations, the simulation results show an improvement in target scattering coefficient (TSC) estimation and target detection probability as the number of iterations increases, while still transmitting data rates in the range of several Mbps with low bit error rates between CRC transceivers.http://dx.doi.org/10.1155/2018/4182927
spellingShingle Yu Yao
Lenan Wu
Cognitive Waveform Design for Radar-Communication Transceiver Networks
Journal of Advanced Transportation
title Cognitive Waveform Design for Radar-Communication Transceiver Networks
title_full Cognitive Waveform Design for Radar-Communication Transceiver Networks
title_fullStr Cognitive Waveform Design for Radar-Communication Transceiver Networks
title_full_unstemmed Cognitive Waveform Design for Radar-Communication Transceiver Networks
title_short Cognitive Waveform Design for Radar-Communication Transceiver Networks
title_sort cognitive waveform design for radar communication transceiver networks
url http://dx.doi.org/10.1155/2018/4182927
work_keys_str_mv AT yuyao cognitivewaveformdesignforradarcommunicationtransceivernetworks
AT lenanwu cognitivewaveformdesignforradarcommunicationtransceivernetworks