MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum
Aiming at the problem of large amount of calculation and long recognition time of traditional method of modulation identification of centralised multiple-input multiple-output (MIMO) radar signal, partial zero-delay instantaneous autocorrelation spectrum is proposed to identify the modulation of cen...
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Online Access: | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0031 |
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doaj-f8e16cce577f4838a27f38cfb12295952021-04-02T12:43:08ZengWileyThe Journal of Engineering2051-33052019-06-0110.1049/joe.2019.0031JOE.2019.0031MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrumXian Rao0Xuezhi Zhao1Ling Zhang2Xidian UniversityXidian UniversityXidian UniversityAiming at the problem of large amount of calculation and long recognition time of traditional method of modulation identification of centralised multiple-input multiple-output (MIMO) radar signal, partial zero-delay instantaneous autocorrelation spectrum is proposed to identify the modulation of centralised MIMO radar here. In this method, the modulation identification of the centralised MIMO radar is performed by extracting the ratio of the sub-peak to the highest peak in the zero-delay transient autocorrelation spectrum of the part signal. The computational complexity of this method is low, and it identifies without additional features for coded MIMO radar signals. Here, the definition of partial instantaneous correlation spectrum is given; the feasibility of using this method to identify the modulation type of the centralised MIMO radar is analysed, and the identification process is discussed. It is showed that the proposed method can shorten the recognition time while guaranteeing the detection performance under a certain SNR in the simulation results.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0031modulationcomputational complexitycorrelation methodsMIMO communicationradar signal processingMIMO systemsMIMO radarMIMO radar signals modulation recognitionpartial instantaneous autocorrelation spectrumlong recognition timemodulation identificationmultiple-input multiple-output radar signalzero-delay instantaneous autocorrelation spectrumcentralised MIMO radarzero-delay transient autocorrelation spectrumpart signalcoded MIMO radar signalspartial instantaneous correlation spectrummodulation type |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xian Rao Xuezhi Zhao Ling Zhang |
spellingShingle |
Xian Rao Xuezhi Zhao Ling Zhang MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum The Journal of Engineering modulation computational complexity correlation methods MIMO communication radar signal processing MIMO systems MIMO radar MIMO radar signals modulation recognition partial instantaneous autocorrelation spectrum long recognition time modulation identification multiple-input multiple-output radar signal zero-delay instantaneous autocorrelation spectrum centralised MIMO radar zero-delay transient autocorrelation spectrum part signal coded MIMO radar signals partial instantaneous correlation spectrum modulation type |
author_facet |
Xian Rao Xuezhi Zhao Ling Zhang |
author_sort |
Xian Rao |
title |
MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
title_short |
MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
title_full |
MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
title_fullStr |
MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
title_full_unstemmed |
MIMO radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
title_sort |
mimo radar signals modulation recognition based on partial instantaneous autocorrelation spectrum |
publisher |
Wiley |
series |
The Journal of Engineering |
issn |
2051-3305 |
publishDate |
2019-06-01 |
description |
Aiming at the problem of large amount of calculation and long recognition time of traditional method of modulation identification of centralised multiple-input multiple-output (MIMO) radar signal, partial zero-delay instantaneous autocorrelation spectrum is proposed to identify the modulation of centralised MIMO radar here. In this method, the modulation identification of the centralised MIMO radar is performed by extracting the ratio of the sub-peak to the highest peak in the zero-delay transient autocorrelation spectrum of the part signal. The computational complexity of this method is low, and it identifies without additional features for coded MIMO radar signals. Here, the definition of partial instantaneous correlation spectrum is given; the feasibility of using this method to identify the modulation type of the centralised MIMO radar is analysed, and the identification process is discussed. It is showed that the proposed method can shorten the recognition time while guaranteeing the detection performance under a certain SNR in the simulation results. |
topic |
modulation computational complexity correlation methods MIMO communication radar signal processing MIMO systems MIMO radar MIMO radar signals modulation recognition partial instantaneous autocorrelation spectrum long recognition time modulation identification multiple-input multiple-output radar signal zero-delay instantaneous autocorrelation spectrum centralised MIMO radar zero-delay transient autocorrelation spectrum part signal coded MIMO radar signals partial instantaneous correlation spectrum modulation type |
url |
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0031 |
work_keys_str_mv |
AT xianrao mimoradarsignalsmodulationrecognitionbasedonpartialinstantaneousautocorrelationspectrum AT xuezhizhao mimoradarsignalsmodulationrecognitionbasedonpartialinstantaneousautocorrelationspectrum AT lingzhang mimoradarsignalsmodulationrecognitionbasedonpartialinstantaneousautocorrelationspectrum |
_version_ |
1721567949141049344 |