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 A Modified STAP Estimator for Superresolution of Multiple Signals

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongbao Wang ◽  
Junhao Xie ◽  
Zilong Ma ◽  
Taifan Quan
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Surface Wave ◽  
High Frequency ◽  
Real Data ◽  
Multiple Signals ◽  
First Order ◽  
Wave Radar ◽  
Simulation Results ◽  
Space Time Adaptive Processing

A modified space-time adaptive processing (STAP) estimator is described in this paper. The estimator combines the incremental multiparameter (IMP) algorithm and the existing beam-space preprocessing techniques yielding a computationally cheap algorithm for the superresolution of multiple signals. It is a potential technique for the remote sensing of the ocean currents from the broadened first-order Bragg sea echo spectrum of shipborne high-frequency surface wave radar (HFSWR). Some simulation results and real-data analysis are shown to validate the proposed algorithm.

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.

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 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

scholarly journals The Application of JDL to Suppress Sea Clutter for Shipborne HFSWR

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Zhenyuan Ji ◽  
Chunlei Yi ◽  
Junhao Xie ◽  
Yang Li
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Real Data ◽  
The Novel ◽  
Clutter Suppression ◽  
Sea Clutter ◽  
Digital Beamforming ◽  
Wave Radar ◽  
Novel Method ◽  
2D Fft

This paper deals with the problem of sea clutter suppression for shipborne high frequency surface wave radar (HFSWR) based on the joint domain localized (JDL) adaptive processing algorithm. The performance of the novel method is compared with 2D FFT plus digital beamforming (FFT-DBF) and orthogonal weight in different azimuths. The results based on simulated and real data show that the novel method provides higher detection performance than others.

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