The statistical analysis on real image from MSTAR data sets show the distribution has good performance on fitting high resolution SAR images.
MSTAR数据的统计分析结果表明该模型对于高分辨力的SAR图像有较好的适用性。
Finally, the MSTAR data with vehicle targets and natural terrains are used to validate the above algorithm, and the performance of this algorithm is good.
最后，利用MSTAR数据库中的车辆目标和自然地物数据验证了该算法，结果显示该特征具有较好的鉴别性能。
The simulation results using Moving and Stationary Target Acquisition and Recognition (MSTAR) data indicate that the error of the proposed method is small, and thus it has high accuracy.
移动与静止目标获取与识别（MSTAR）公共数据库实测数据的仿真结果表明，该方法估计误差较小，可获得较高的估计准确度。
The simulation results using Moving and Stationary Target Acquisition and Recognition (MSTAR) data indicate that the error of the proposed method is small, and thus it has high accuracy.
移动与静止目标获取与识别（MSTAR）公共数据库实测数据的仿真结果表明，该方法估计误差较小，可获得较高的估计准确度。
应用推荐