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Abstract

Novel Research in Sciences

Particle Phase Recognition Based on KNN Algorithm for Spaceborne Dual Frequency Radar

  • Open or CloseXufeng Jin and Nan Li*

    School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China

    *Corresponding author:Nan Li, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China

Submission: April 7, 2021;Published: April 29, 2021

Abstract

This paper analyzes the feasibility of recognizing the precipitation phase through simulating reflectivity factor of particles with different phases at Ku and Ka band by the T-matrix method; and then uses simulation results as true values to make phase recognition for different types of precipitation by the KNN algorithm. According to the results, mixed phase particles in stratiform precipitation are partially overlapped with other particles on the ZeKu-DFR plane, for which the KNN model can reach an accuracy rate up to 91%. Solid particles and liquid particles in convective precipitation are slightly overlapped on the ZeKu-DFR plane, for which the KNN model can reach an accuracy rate up to 99%.

Keywords:DPR; T-matrix; Phase recognition; KNN

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