MATLAB Code Implementation for Instantaneous Frequency Estimation

In the field of signal processing, instantaneous frequency estimation is a crucial topic, particularly suitable for analyzing non-stationary signals. Implementing this functionality through MATLAB enables intuitive visualization of a signal's time-frequency characteristics.

Instantaneous frequency primarily reflects how a signal's frequency varies over time, typically implemented using the analytic signal method. The core steps include:

Hilbert Transform: First, perform Hilbert transformation on the original signal to construct an analytic signal, eliminating negative frequency components. Phase Extraction: Calculate the phase angle of the analytic signal, then obtain instantaneous frequency through phase differencing or differentiation. Phase Unwrapping: Due to potential phase jumps introducing errors, phase continuity correction is required.

MATLAB's advantage lies in its built-in `hilbert()` function which directly generates analytic signals. Combined with the `unwrap()` function to eliminate phase jumps, instantaneous frequency estimation can be completed through differential operations. This method works well for narrowband signals, but may require integration with time-frequency analysis tools (such as Short-Time Fourier Transform) for broadband signal applications.