Estimating the Instantaneous Frequency of Linear and Nonlinear Frequency Modulated Radar Signals-A Comparative Study

Area of Science:

• * Electrical Engineering
• * Signal Processing
• * Electronic Warfare

Background:

• * Automatic modulation recognition is crucial for electronic intelligence and support measures.
• * Accurate instantaneous frequency (IF) estimation is vital for radar signal classification.
• * Existing IF estimation methods for radar signals have limitations affecting classification performance.

Purpose of the Study:

• * To compare five popular methods for evaluating the IF-law of frequency modulated radar signals.
• * To propose and evaluate a novel generalized quasi-maximum likelihood (QML) method for IF estimation.
• * To investigate the influence of multipath effects on IF estimates.

Main Methods:

• * Comparison of five established IF estimation techniques, including phase finite differences and time-frequency representations.
• * Introduction of a new generalized quasi-maximum likelihood (QML) estimation approach.
• * Simulation experiments to assess estimator accuracy and multipath influence.

Main Results:

• * The proposed QML estimator demonstrates significantly higher accuracy compared to existing methods.
• * The study provides the first investigation into multipath effects on IF estimates in radar signals.
• * Performance comparison highlights the superiority of the QML method.

Conclusions:

• * The generalized QML method offers a more accurate approach to IF estimation for radar signals.
• * Understanding multipath influence is critical for robust modulation recognition systems.
• * This research advances the field of automatic modulation recognition in electronic warfare.