Detection of Vehicles Through Fusion Sensor System

Reliable vehicle detection is critical for defense, border security, and intelligent transportation. Single-sensor systems often face challenges such as environmental noise, limited range, and high false alarm rates. To overcome these, we propose an integrated detection system that combines acoustic, seismic, and magnetic sensing. Acoustic signals capture vehicle engine and tire noise, seismic sensors detect ground vibrations induced by vehicle movement, and magnetic sensors register disturbances in the Earth’s magnetic field caused by metallic structures. A fusion framework is developed to integrate signals, employing preprocessing, feature extraction, and decision-level fusion. Experimental data shows that while seismic sensors alone can detect heavy vehicles at distances up to 1000 m with average vibration frequencies near 332 Hz, fusion significantly improves accuracy, reduces false alarms, and extends operational reliability. This paper highlights the feasibility of multi-sensor fusion for robust vehicle detection, offering applications in security, traffic monitoring, and emergency response.