Performance Analysis of DoA Algorithms using Real Time Data from mm Wave Radar
Sanjeeva Reddy S, Manoj Kumar M, J. Valarmathi · 2025
Millimeter-wave (mmWave) radar offers high-resolution sensing capabilities, enabling accurate detection of closely spaced targets along with the estimation of parameters such as position, range, velocity, and angle. This work focuses on Direction of Arrival (DoA) estimation using real-time data collected from the Infineon BGT60TR13C mmWave radar sensor. Prominent DoA estimation algorithms, including Conventional Beamforming (CBF), Multiple Signal Classification (MUSIC), and Sparse Parametric Iterative Covariance-based Estimation (SPICE), were implemented and evaluated using the collected data. The performance of these algorithms was assessed based on metrics such as Mean Square Error (MSE) and output Signal-to-Noise Ratio (SNR). Experimental results demonstrate that the SPICE algorithm outperforms traditional methods in terms of both accuracy and robustness, highlighting its effectiveness for high-resolution DoA estimation in practical mmWave radar systems.