RADAR SIGNAL ANALYSIS TOOL

Project Overview

This tool was developed to analyze various aspects of radar signal processing pipelines, with a focus on identifying and quantifying issues in real radar data. It provides comprehensive evaluation of noise floor measurements, signal magnitude assessment, vector misalignment detection, and phase mismatch identification.

Key Features

• Noise floor analysis: Measures and characterizes the noise floor in radar systems to establish baseline performance metrics
• Signal magnitude evaluation: Quantifies signal strength across different operational conditions
• Vector misalignment detection: Identifies discrepancies in vector alignment that could impact system performance
• Phase mismatch analysis: Evaluates phase coherence across radar channels

Technical Implementation

The tool is implemented in Python, leveraging libraries such as NumPy for numerical calculations, Matplotlib for visualization, and Pandas for data manipulation. The architecture follows a modular design to allow for easy extension and adaptation to different radar systems.

Business Impact

The tool has been integrated into the company's automated software testing pipeline, where it plays a critical role in identifying issues in software being developed. By providing quantitative metrics on radar performance, it enables more objective evaluation of system improvements and regression testing.

Results and Outcomes

Since its deployment, the tool has helped identify several subtle issues in the signal processing pipeline that were previously undetected. These discoveries led to improved performance in noise rejection and signal detection, ultimately enhancing the overall radar system effectiveness.

« BACK TO PROJECTS