FMCW Radar Ranging and Angle Measurement with High-Resolution Algorithms - Undergraduate Thesis Project

FMCW (Frequency Modulated Continuous Wave) radar is a widely used technology in ranging and angle measurement applications. Its fundamental principle involves transmitting continuous frequency-modulated signals and analyzing the frequency difference between transmitted and reflected signals to calculate target distance and velocity. As an undergraduate thesis topic, FMCW radar combined with super-resolution algorithms like MUSIC, ESPRIT, and ROOT-MUSIC can significantly improve angle measurement accuracy, making it a research direction with both theoretical depth and practical value. In ranging applications, FMCW radar calculates target distance by measuring the frequency difference between transmitted and received signals, offering high precision and strong anti-interference capabilities. For angle measurement, traditional methods like beamforming may be limited by array aperture resolution. The introduction of MUSIC (Multiple Signal Classification) algorithm substantially enhances angle estimation accuracy by leveraging the orthogonality between signal subspace and noise subspace, estimating Direction of Arrival (DOA) through spectral peak search. In code implementation, MUSIC typically involves covariance matrix calculation, eigenvalue decomposition, and peak detection algorithms. ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm utilizes the rotational invariance property of arrays to reduce computational complexity, making it suitable for real-time applications. Implementation-wise, ESPRIT requires array manifold modeling and employs matrix pencil methods for parameter estimation. ROOT-MUSIC algorithm further optimizes MUSIC by replacing spectral peak search with polynomial root-solving, improving computational efficiency and resolution. The root-solving approach typically involves constructing characteristic polynomials and using numerical methods like Newton-Raphson iteration. This thesis topic comprehensively combines FMCW radar principles with modern super-resolution DOA estimation algorithms, enabling students to deeply understand core technologies in radar signal processing and array signal analysis. It also lays foundation for future applications in autonomous driving, UAV navigation, and other fields. From a programming perspective, implementation would involve signal generation modules, FFT processing for range detection, and array signal processing algorithms for angle estimation using MATLAB or Python with numerical computing libraries.