A CFAR Algorithm Based on Monte Carlo Method for Millimeter-Wave Radar Road Traffic Target Detection

The development of Intelligent Transportation Systems (ITS) puts forward higher requirements for millimeter-wave radar surveillance in the traffic environment, such as lower time delay, sensitivity, and better multi-target detection capability. Constant False Alarm Rate (CFAR) detector plays a vital role adaptive target radar. Still, traditional CFAR algorithms use sliding window to find limit speed efficiency. In cases, we propose discuss method, which transforms Monte Carlo simulation principle into randomly sampling instantaneous Range–Doppler Matrix (RDM) data, improve ability moving targets pedestrians vehicles environment. Compared with conventional methods, real experiments show that method breaks through reference limitation has accuracy, delay. We hope promote application road scenes.