Parameter estimation of linear frequency modulation signals based on sampling theorem and fractional broadening

Area of Science:

• Signal Processing
• Radar Systems
• Electronic Warfare

Background:

• Linear Frequency Modulation (LFM) signals are crucial in radar systems.
• Parameter estimation of LFM signals is challenging in electronic warfare.
• Traditional Fractional Fourier Transform (FRFT) methods are computationally intensive due to optimal order search.

Purpose of the Study:

• To develop a novel, computationally efficient method for LFM signal parameter estimation.
• To enhance the speed of LFM parameter estimation using FRFT.
• To maintain accuracy while significantly reducing computation time.

Main Methods:

• Utilized sampling theorem to determine the optimal FRFT order search range.
• Applied FRFT to LFM signals within the calculated search range.
• Calculated fractional broadening to identify the optimal FRFT order.

Main Results:

• The proposed method demonstrated a six-fold increase in speed compared to traditional FRFT.
• Accuracy of parameter estimation was preserved.
• The method effectively estimated parameters of multi-component LFM signals in low SNR white Gaussian noise.

Conclusions:

• The novel FRFT-based method significantly improves LFM signal parameter estimation speed.
• This approach offers a viable solution for real-time electronic warfare applications.
• The method is robust even in noisy conditions and for complex signals.