Clutter Mitigation in Indoor Radar Sensors Using Sensor Fusion Technology

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 10; p. 3113
• Main Authors: Singh, Srishti, Lee, Ha-Neul, Park, Yuna, Kim, Sungho, Park, Si-Hyun, Yang, Jong-Ryul
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.05.2025; MDPI
• Subjects: Accuracy; Boxes; Cameras; clutter mitigation; Communication; Fourier transforms; Localization; low-resolution camera; Methods; millimeter-wave radar sensor; Privacy; Radar systems; sensor fusion; Sensors; Signal processing; signal-to-noise ratio; Velocity; sensor fusion; millimeter-wave radar sensor; clutter mitigation; low-resolution camera; signal-to-noise ratio
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s25103113

A methodology utilizing low-resolution camera data is proposed to mitigate clutter effects on radar sensors in smart indoor environments. The proposed technique suppresses clutter in distance–velocity (range–Doppler) images obtained from millimeter-wave radar by estimating clutter locations using approximate spatial information derived from low-resolution camera images. Notably, the inherent blur present in low-resolution images closely corresponds to the distortion patterns induced by clutter in radar signals, making such data particularly suitable for effective sensor fusion. Experimental validation was conducted in indoor path-tracking scenarios involving a moving subject within a 10 m range. Performance was quantitatively evaluated against baseline range–Doppler maps obtained using radar data alone, without clutter mitigation. The results show that our approach improves the signal-to-noise ratio by 2 dB and increases the target detection rate by 8.6% within the critical 4–6 m range, with additional gains observed under constrained velocity conditions.