Aiming at the problem of outlier detection in 2D lidar scanning data,the nearest neighbor distance local outlier factor detection algorithm is proposed.Firstly,the definition of global outliers in 2D lidar scanning data is given,and then the global outliers of scanned data are detected； secondly,the local outliers of scanned data are detected by using local outlier factor； finally,the algorithm is verified by using five sets of 2D radar scanning data in actual environment.The results show that:the nearest neighbor distance local outlier factor detection algorithm can detect the abnormal value of 2D lidar scanning data,and the average false alarm rate of the algorithm is 1.228%,and the average calculation time is 0.842 seconds,which can meet the actual needs.