Considering error of radar data as well as the influence of airflow and other factors,introduce Kalman filter into the flight short-term collision detection,to get more accurate forecast. The known research shows that flight track error obeys to zero mean Gaussian model. Kalman filter can effectively deal with the error distribution model. Filtering results are closer to the actual conditions,and make a valid prediction of the unknown state. According to the civil aviation flight safety requirements,in this paper,forecast the flight conflict in horizontal and vertical direction. Through theoretical analysis and simulation experiments show that the method can not only forecast the real collision,but also provide the reference information as probability for potential collision.% 考虑到雷达数据的误差以及气流等随机因素影响，将卡尔曼滤波引入飞行器短期冲突检测中，以实现更精确的预报。已知研究表明飞行航迹误差服从零均值高斯分布模型。卡尔曼滤波能有效地应对该误差分布模型，滤波结果更接近实际飞行情况，并对未知状态进行有效预测。按照民航飞行安全要求，文中对飞行水平方向和垂直方向的冲突进行预测。通过理论分析和仿真模拟试验，对比传统方法，文中提供的方法不但能对真实存在冲突做出准确预报，还能对潜在的冲突以概率的形式提供参考信息。
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