Adaptive main-lobe clutter suppression algorithm based on data selection in spatial domain for small-aperture high-frequency surface-wave radar

2021 ◽  
Author(s):  
J. Li ◽  
X. Zhang ◽  
Q. Yang
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Spatial Domain ◽  
Data Selection ◽  
Main Lobe ◽  
Clutter Suppression ◽  
Small Aperture ◽  
Wave Radar

Vessel tracking with small-aperture compact high-frequency surface wave radar

2019 ◽  
Author(s):  
Weifeng Sun ◽  
Weimin Huang ◽  
Yonggang Ji ◽  
Yongshou Dai ◽  
Peng Ren ◽  
...  
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Small Aperture ◽  
Vessel Tracking ◽  
Wave Radar

scholarly journals A Single-Dataset-Based Pre-Processing Joint Domain Localized Algorithm for Clutter-Suppression in Shipborne High-Frequency Surface-Wave Radar

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3773
Author(s):  
Liang Guo ◽  
Xin Zhang ◽  
Di Yao ◽  
Qiang Yang ◽  
Yang Bai ◽  
...  
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Secondary Data ◽  
Real Data ◽  
Training Sample ◽  
Clutter Suppression ◽  
Low Velocity ◽  
Unscented Transformation ◽  
Wave Radar ◽  
Suppression Method

Due to the motion of the platform, the spectrum of first-order sea clutter will widen and mask low-velocity targets such as ships in shipborne high-frequency surface-wave radar (HFSWR). Limited by the quantity of qualified training samples, the performance of the generally used clutter-suppression method, space–time adaptive processing (STAP) degrades in shipborne HFSWR. To deal with this problem, an innovative training sample acquisition method is proposed, in the area of joint domain localized (JDL) reduced-rank STAP. In this clutter-suppression method, based on a single range of cell data, the unscented transformation is introduced as a preprocessing step to obtain adequate homogeneous secondary data and roughly estimated clutter covariance matrix (CCM). The accurate CCM is calculated by integrating the approximate CCM of different range of cells. Compared with existing clutter-suppression algorithms for shipborne HFSWR, the proposed approach has a better signal-to-clutter-plus-noise ratio (SCNR) improvement tested by real data.

Target monitoring using small-aperture compact high-frequency surface wave radar

2018 ◽  
Vol 33 (3) ◽  
pp. 22-31 ◽  
Author(s):  
Yonggang Ji ◽  
Jie Zhang ◽  
Yiming Wang ◽  
Weifeng Sun ◽  
Ming Li
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Small Aperture ◽  
Wave Radar ◽  
Target Monitoring

Cascaded method for ionospheric decontamination and sea clutter suppression for high‐frequency hybrid sky‐surface wave radar

2015 ◽  
Vol 9 (7) ◽  
pp. 562-571 ◽  
Author(s):  
Yajun Li ◽  
Yinsheng Wei ◽  
Yongpeng Zhu ◽  
Zhuoqun Wang ◽  
Rongqing Xu
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Clutter Suppression ◽  
Sea Clutter ◽  
Wave Radar

scholarly journals An Ionospheric Es Layer Clutter Model and Suppression in HF Surfacewave Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Yajun Li ◽  
Yinsheng Wei ◽  
Rongqing Xu ◽  
Zhuoqun Wang ◽  
Tianqi Chu
Keyword(s):  
Surface Wave ◽  
Fast Algorithm ◽  
High Frequency ◽  
Measured Data ◽  
Clutter Suppression ◽  
Screen Method ◽  
Proposed Model ◽  
Wave Radar ◽  
Simulation Results ◽  
Space Time Adaptive Processing

This paper based on a fast implemented multiphase screen method using DFT puts forward an ionospheric Es layer clutter model and uses the newly developed dimensionality reduction space-time adaptive processing- (STAP-) JDL algorithm to suppress Es layer clutter, which proves the validity of the proposed model. Firstly, the multiphase screen method was analyzed, and a fast algorithm using DFT was proposed. Then, based on the multiphase screen method and thorough simulation, we reached a conclusion of the high-frequency radio wave propagation’s fluctuation characteristics in the ionosphere. According to the results of the analysis, a new Es layer ionospheric clutter model was established and was compared with the measured data and verification was made. Finally, based on the built clutter model, JDL algorithm was applied to the high-frequency surface wave radar ionospheric clutter suppression, using the measured data to verify the validity of the model and algorithm. The simulation results showed that the built model can show the characteristics of the ionospheric Es layer clutter and that the JDL algorithm can suppress ionospheric Es layer clutter quite effectively.

scholarly journals Radio and Clutter Suppression Algorithm Based on Spatial Multiple Beams for Small-Aperture HFSWR

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Di Yao ◽  
Xin Zhang ◽  
Qiang Yang ◽  
Weibo Deng
Keyword(s):  
Performance Improvement ◽  
High Frequency ◽  
Main Beam ◽  
Clutter Suppression ◽  
Small Aperture ◽  
Phase Errors ◽  
Multiple Beams ◽  
Wave Radar ◽  
Doppler Angle ◽  
Significant Performance

Radio and clutter that cover a certain number of range-Doppler-angle cells have a major impact on the detection performance of a high-frequency surface wave radar (HFSWR) system. Especially for a small-aperture array, the angle spectrums of radio and clutter suffer from severe broadening, so the targets that are more easily submerged in the broadened radio and clutter can be hardly detected. To tackle this issue, this paper proposes an algorithm for radio decontamination and clutter suppression to enable detection of the submerged targets. First, the spatial correlation of the array is derived, and the characteristics of radio and clutter are analyzed based on angle-Doppler joint eigenvector. Then owing to the analysis, the information of radio and clutter in the main beam can be accurately estimated from that in the auxiliary beams and eliminated by subtracting it. The results of simulations and measured data indicate that the proposed method offers a significant performance improvement and has a strong robustness against the array amplitude-phase errors.

scholarly journals A Novel Main-Lobe Cancellation Method Based on a Single Notch Space Filter and Optimized Correlation Analysis Strategy

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Jiazhi Zhang ◽  
Xin Zhang ◽  
Weibo Deng ◽  
Liang Guo ◽  
Qiang Yang
Keyword(s):  
Surface Wave ◽  
Correlation Analysis ◽  
Measured Data ◽  
Training Data ◽  
Main Lobe ◽  
Clutter Suppression ◽  
Sea Clutter ◽  
First Order ◽  
Wave Radar ◽  
Space Filter

The high-frequency hybrid sky-surface wave radar (HFSSWR) is a new kind of over-the-horizon radar system. Combining the advantages of both the sky wave radar and the surface wave radar, HFSSWR has drawn much attention in recent years. But the new system also brings new challenges. One of the most severe problems is that the heterogeneous environment makes a big challenge for the sea clutter suppression processing. Due to the nonstationary properties of the ionosphere, the first-order sea clutter statistics change significantly among range bins. So the new efficient sea clutter suppression method is required, and the clutter characteristics analyses are also in urgent need of research in order to guide the design of the algorithm in the background of HFSSWR. In this paper, utilizing the measured data set, we first analyse the range and spatial characteristics of the nonhomogeneous first-order sea clutter in HFSSWR. Then, an improved main-lobe cancellation (IMLC) method based on single notch space filter and correlation analysis is proposed to get training data which contains precise clutter information. A main-lobe clutter canceller based on the single notch space filter has been developed to block the target component, and an optimized correlation analysis (OCA) strategy is presented to choose the efficient training data. Finally, the method is examined by measured data and the results indicate that the method has a good performance for broadening first-order sea clutter suppression than the traditional method.

Information Geometric Means-Based STAP for Nonhomogeneous Clutter Suppression in High Frequency Hybrid Sky-Surface Wave Radar

2021 ◽  
Vol 21 (2) ◽  
pp. 1787-1798
Author(s):  
Jiazhi Zhang ◽  
Xin Zhang ◽  
Weibo Deng ◽  
Lei Ye ◽  
Qiang Yang
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Clutter Suppression ◽  
Geometric Means ◽  
Wave Radar
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