Implementation of Data Fusion Algorithms for Millimeter Wave Radar and Infrared Radar

In this research, we focus on implementing data fusion algorithms between millimeter wave radar and infrared radar systems. By leveraging multi-sensor data fusion techniques, we can effectively integrate and analyze data collected from both radar types. The primary objective is to develop a novel algorithm capable of fusing millimeter wave and infrared radar data to produce more accurate and comprehensive results. Our approach involves implementing fusion algorithms that may include Kalman filtering for temporal data correlation, coordinate transformation functions for spatial alignment, and feature-level fusion techniques for enhanced target recognition. We will conduct thorough investigations of existing fusion methodologies and validate our algorithms through experimental testing with real-world data across various scenarios and conditions. The implementation will likely involve Python or MATLAB code for data preprocessing, sensor calibration, and fusion logic, ensuring robust performance in diverse operational environments. This research aims to contribute valuable insights to the field of millimeter wave and infrared radar data fusion and advance its technological development.