A study on Omnidirectional RCS Statistical Feature Extraction Method Based on Density-based Clustering

YUAN Zhentao; ZHANG Lifang; LI Zenghui; WANG Shasha; CONG Wenshan

doi:10.16592/j.cnki.1004-7859.2025071301

YUAN Zhentao, ZHANG Lifang, LI Zenghui, WANG Shasha, CONG Wenshan. A study on Omnidirectional RCS Statistical Feature Extraction Method Based on Density-based Clustering[J]. Modern Radar, 2025, 47(10): 73-76. DOI: 10.16592/j.cnki.1004-7859.2025071301

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A study on Omnidirectional RCS Statistical Feature Extraction Method Based on Density-based Clustering

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This paper uses measured radar cross-section(RCS) data as samples. By fully considering the distribution characteristics of the measured RCS data and dynamically eliminating outliers through the density clustering method, it effectively overcomes the impact of RCS fluctuations on statistical results. The method successfully extracts the omnidirectional RCS characteristics of aircraft. The effectiveness of the method was verified by collecting actual radar measurement data.

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A study on Omnidirectional RCS Statistical Feature Extraction Method Based on Density-based Clustering

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