Low-Complexity Joint Range and Doppler FMCW Radar Algorithm Based on Number of Targets

Area of Science:

• Electrical Engineering
• Signal Processing
• Radar Systems

Background:

• Frequency-modulated continuous wave (FMCW) radar systems are crucial for various applications, including automotive and surveillance.
• Existing low-complexity algorithms for FMCW radar, such as region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based methods, have limitations in adaptability.
• The computational complexity of FMCW radar algorithms is a significant factor affecting real-time performance.

Purpose of the Study:

• To propose a novel, low-complexity joint range and Doppler FMCW radar algorithm.
• To develop an adaptive algorithm that optimizes complexity based on the number of detected targets.
• To demonstrate the effectiveness and efficiency of the proposed algorithm in real-world FMCW radar environments.

Main Methods:

• Analysis of computational complexity for ROI-based and partial DFT-based FMCW radar algorithms.
• Identification of the number of targets as a key determinant of algorithm complexity.
• Development of a target-number-dependent algorithm that dynamically selects between two low-complexity FMCW radar processing strategies.

Main Results:

• The number of targets significantly influences the complexity of FMCW radar algorithms.
• The proposed adaptive algorithm achieves lower computational complexity compared to fixed low-complexity algorithms.
• Experimental validation using real FMCW radar systems confirms the algorithm's effectiveness and efficiency, measured by CPU time and floating-point operations.

Conclusions:

• The proposed FMCW radar algorithm effectively reduces computational complexity by adapting to the number of targets.
• This adaptive approach offers a practical solution for enhancing the performance of real-time FMCW radar systems.
• The algorithm demonstrates robust performance in practical scenarios, validated through real-world experiments.