Aug 4, 2020 · We propose a drone classification method for polarimetric radar, based on convolutional neural network (CNN) and image processing methods.

The result showed that the proposed method improved the accuracy from 89.9% to 99.8%, compared with single polarized micro-Doppler image. We compared the result.

Nov 18, 2024 · The proposed method improves drone classification accuracy when the micro-Doppler signature is very weak by the aspect angle." Financial support ...

Improved Drone Classification Using Polarimetric Merged-Doppler Images · Classification of Drones Using Edge-Enhanced Micro-Doppler Image Based on CNN.

Oct 22, 2024 · We propose a drone classification method based on convolutional neural network (CNN) and micro-Doppler signature (MDS).

Merged Doppler images (MDI) were used outdoors with 4-fold cross-validation and obtained 100% accuracy, but the indoor anechoic chamber demonstrated lower ...

Improved Drone Classification Using Polarimetric Merged-Doppler Images · Human–vehicle classification using feature-based SVM in 77-GHz automotive FMCW radar.

This method increases the classification accuracy for four types of targets (ships, birds, flapping birds, and bird flocks) from 93.13% to 97.13%, an ...

This study presents a dataset of bionic drones and introduces the Bionic Drone Identification Network (BDRNet).