Target tracking system for multi-sensor data fusion

The aim is to study the radar target tracking system for multi-sensor data fusion. Multi-sensor data fusion is important for achieving information complementarity, improving target tracking accuracy and recognition capabilities, and enhancing the system's anti-jamming. Aiming at the architecture of radar and infrared tracking, an information fusion algorithm based on radar and infrared sensor optimal data compression is proposed for single target tracking. Then, the algorithm of track correlation and track fusion in multi-target tracking is simulated and analyzed. The results show that the optimized algorithm improves the correct correlation rate of the track. The multi-sensor target fusion tracking can avoid the limitations of a single sensor, and improve the accuracy of target tracking. Therefore, it can be concluded that the designed radar infrared netted data fusion system has excellent anti-jamming performance. It greatly improves the target tracking accuracy.