Detection and Parameter Estimation of Single Component LFM Signals

In this article, we demonstrate how to detect and estimate parameters of single-component Linear Frequency Modulated (LFM) signals using MATLAB. We employ the Fractional Fourier Transform (FrFT) for signal processing and analysis, which serves as a powerful tool for decomposing signals into multiple frequency components and extracting their characteristics. For implementation, the MATLAB code will utilize FrFT algorithms to transform the signal into fractional domains where LFM components appear as concentrated peaks, enabling effective detection through peak search algorithms. Parameter estimation will be implemented by analyzing the peak positions in the fractional Fourier domain to calculate the chirp rate and initial frequency using mathematical relations between fractional order and LFM parameters. The simulation will include noise robustness testing and performance evaluation metrics for estimation accuracy. To summarize, this technical guide provides comprehensive details on single-component LFM signal detection and parameter estimation methodology, along with step-by-step MATLAB implementation guidelines. The content covers practical aspects including FrFT computation using built-in functions or custom algorithms, parameter extraction logic, and visualization techniques for time-frequency analysis. These resources aim to help researchers and engineers better understand and apply these techniques to achieve improved results in signal processing and frequency domain analysis applications.