A joint spatial-polarization adaptation method for DOA estimation under mainlobe jamming

Li, Binbin; Liu, Weijian; Zhou, Bin; Chen, Hui; Ni, Mengyu; Wang, Xiaoge

doi:10.1109/radar53847.2021.10028326

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…The adaptive space-time vector pattern can be shaped as the subtraction of eigen beams from the quiescent space-time vector pattern, which can be expressed as follows [20]:…”

Section: Eigen-projection Matrix Preprocessing Methodsmentioning

confidence: 99%

Space-Time Adaptive Processing Clutter-Suppression Algorithm Based on Beam Reshaping for High-Frequency Surface Wave Radar

Yang

Xin

et al. 2022

Remote Sensing

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In high-frequency surface wave radar (HFSWR) systems, clutter is a common phenomenon that causes objects to be submerged. Space-time adaptive processing (STAP), which uses two-dimensional data to increase the degrees of freedom, has recently become a crucial tool for clutter suppression in advanced HFSWR systems. However, in STAP, the pattern is distorted if a clutter component is contained in the main lobe, which leads to errors in estimating the target angle and Doppler frequency. To solve the main-lobe distortion problem, this study developed a clutter-suppression method based on beam reshaping (BR). In this method, clutter components were estimated and maximally suppressed in the side lobe while ensuring that the main lobe remained intact. The results of the proposed algorithm were evaluated by comparison with those of standard STAP and sparse-representation STAP (SR-STAP). Among the tested algorithms, the proposed BR algorithm had the best suppression performance and the most accurate main-lobe peak response, thereby preserving the target angle and Doppler frequency information. The BR algorithm can assist with target detection and tracking despite a background with ionospheric clutter.

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“…The adaptive space-time vector pattern can be shaped as the subtraction of eigen beams from the quiescent space-time vector pattern, which can be expressed as follows [20]:…”

Section: Eigen-projection Matrix Preprocessing Methodsmentioning

confidence: 99%

Space-Time Adaptive Processing Clutter-Suppression Algorithm Based on Beam Reshaping for High-Frequency Surface Wave Radar

Yang

Xin

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

A joint spatial-polarization adaptation method for DOA estimation under mainlobe jamming

Cited by 1 publication

References 7 publications

Space-Time Adaptive Processing Clutter-Suppression Algorithm Based on Beam Reshaping for High-Frequency Surface Wave Radar

Space-Time Adaptive Processing Clutter-Suppression Algorithm Based on Beam Reshaping for High-Frequency Surface Wave Radar

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