In order to integrate unmanned aerial vehicle (UAV) into the national airspace system safely, one of the keys is to realize UAV detect and avoid (DAA). Validating the effectiveness of DAA systems through rigorous simulation is crucial to ensure their reliability and compliance with aviation safety requirements. In this study, leveraging manned aircraft trajectory data obtained from RadarBox, Monte Carlo simulations are conducted to generate potential UAV flight paths for DAA evaluation. Subsequently, the birth-death process is employed to obtain the initial air risks associated with UAV flights. To evaluate the effectiveness of the DAA system, the same methodological framework is utilized to assess the mitigated risks after DAA system implementation. Based on simulations using manned aircraft data over the Chengdu region, the risk is successfully reduced from \(1.65111 \times 10^{ - 6}\) per flight hour to \(6.12871 \times 10^{ - 8}\) per flight hour, ensuring that UAV operations can meet the safety standards.