Volume 13, Number 06, March 2023

Advanced Clutter Mitigation Method for Surveillance Radar using Machine Learning

  Authors

Malwinder Singh, Shashi Ranjan Kumar and Bhukya Soumya Mishra, Bharat Electronics Limited, India

  Abstract

This research focuses on improving the ground clutter mitigation by integrating ML methods with traditional methods (such as CFAR and Doppler processing) of X-band surveillance radar. Discriminative machine learning methods are used as they have the ability to learn without the knowledge of distribution type. The techniques used to accomplish research includes raw IQ radar data collection, data labelling, and feature generation, statistical significance of generated features, model (DT, SVM and ANN) training and model evaluation. The results indicate improvement in mitigation of ground clutter for different scenarios. The research also discusses the future work related to this research.

  Keywords

Artificial Neural Network (ANN), Constant False Alarm Rate (CFAR), Digital Down Conversion(DDC), Decision Tree (DT), Fast Fourier Transform (FFT), false negatives (FN), false positives (FP), In PhaseQuadrature Phase (IQ), Machine leaning (ML), Support Vector Machine (SVM), true negatives (TN), true positives(TP)