Wideband Interference Time-Frequency Feature Prediction and Its Application to Cognitive Radar HRRP Estimation

被引：2

作者：

Wan, Pengcheng ^{[1
]}

Feng, Weike ^{[1
]}

Tong, Ningning ^{[1
]}

Hu, Xiaowei ^{[1
]}

Zheng, Guimei ^{[1
]}

机构：

[1] Air Force Engn Univ, Air & Missile Def Coll, Xian 710051, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2022年 / 19卷

基金：

中国国家自然科学基金;

关键词：

Radar; Estimation; Radar measurements; Time-frequency analysis; Interference; Cognitive radar; Spatiotemporal phenomena; deep learning (DL); high-resolution range profile (HRRP); wideband interference (WBI); NARROW-BAND;

D O I：

10.1109/LGRS.2022.3187292

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Wideband interference (WBI) is detrimental to high-resolution radar due to its high power and wide frequency occupancy. In this study, a deep learning (DL) method is proposed to predict the time-frequency (TF) feature of WBI and applied to cognitive radar high-resolution range profile (HRRP) estimation. Specifically, by performing short-time Fourier transform (STFT) on the WBI signal collected in the past and using a sliding window, a series of WBI TF figures is generated. A long short-time memory (LSTM) network is then used to learn the spatiotemporal (ST) correlation of these TF figures, thus predicting the WBI TF feature in the future, based on which, a cognitive method is used for target HRRP estimation with reduced influences of WBI. Numerical results demonstrate the effectiveness of the proposed methods.

引用

页数：5

共 14 条

[1] High Range Resolution Profile Estimation via a Cognitive Stepped Frequency Technique [J].

Aubry, Augusto ;

Carotenuto, Vincenzo ;

De Maio, Antonio ;

Pallotta, Luca .

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2019, 55 (01) :444-458

[2] Near Range Radar Imaging Based on Block Sparsity and Cross-Correlation Fusion Algorithm [J].

Feng, Weike ;

Yi, Li ;

Sato, Motoyuki .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (06) :2079-2089

[3] Wideband Interference Suppression for SAR via Instantaneous Frequency Estimation and Regularized Time-Frequency Filtering [J].

Han, Wenchang ;

Bai, Xueru ;

Fan, Weiwei ;

Wang, Li ;

Zhou, Feng .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

[4] Reweighted Tensor Factorization Method for SAR Narrowband and Wideband Interference Mitigation Using Smoothing Multiview Tensor Model [J].

Huang, Yan ;

Zhang, Lei ;

Li, Jie ;

Chen, Zhanye ;

Yang, Xi .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 58 (05) :3298-3313

[5] A Novel Tensor Technique for Simultaneous Narrowband and Wideband Interference Suppression on Single-Channel SAR System [J].

Huang, Yan ;

Zhang, Lei ;

Li, Jie ;

Hong, Wei ;

Nehorai, Arye .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (12) :9575-9588

[6] Avoidance of Time-Varying Radio Frequency Interference With Software-Defined Cognitive Radar [J].

Kirk, Benjamin H. ;

Narayanan, Ram M. ;

Gallagher, Kyle A. ;

Martone, Anthony F. ;

Sherbondy, Kelly D. .

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2019, 55 (03) :1090-1107

[7]

Lang P., 2020, arXiv

[8] A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed l0 Norm [J].

Mohimani, Hosein ;

Babaie-Zadeh, Massoud ;

Jutten, Christian .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (01) :289-301

[9] Efficient and Robust RFI Extraction Via Sparse Recovery [J].

Nguyen, Lam H. ;

Tran, Trac D. .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2016, 9 (06) :2104-2117

[10] Convolutional LSTM-based Long-Term Spectrum Prediction for Dynamic Spectrum Access [J].

Shawel, Bealethem S. ;

Woldegebreal, Dereje H. ;

Pollin, Sofie .

2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2019,

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