森林垂直结构信息缺乏严重制约森林地上生物量估算精度的提高。立体雷达具备对森林垂直结构探测的能力，但早期雷达图像分辨率低。TerraSAR-X等高分辨率雷达数据的出现为利用立体雷达数据进行森林垂直结构探测提供了新的契机。本研究尝试采用立体雷达处理技术，利用TerraSAR-X stripmap模式数据，以内蒙古根河大兴安岭林区和长白山自然保护区为研究区，重点探讨金字塔分层匹配策略中涉及的关键匹配参数对DSM提取精度的影响规律。结果发现：（1）影像匹配采用的金字塔层数对DSM提取精度影响明显，在大兴安岭研究区，采用5、6、7层金字塔匹配得到的DSM误差在±10 m内的像元百分比分别为81.8%、77.7%和77.1%，5层金字塔能以较高的初始分辨率减少林区纹理信息的损失；在长白山研究区，采用7层金字塔得到的DSM能够抑制明显的误匹配点，提高地形提取精度；（2）影像匹配窗口对同名点识别的质量影响明显，采用25×25的匹配窗口，与9×9匹配窗口相比，大兴安岭和长白山研究区影像的平均相关性分别由0.43、0.40提高到0.49、0.45，林区纹理信息欠丰富，宜采用较大匹配窗口；（3）大兴安岭和长白山研究区提取的DSM与参考DSM线性回归的RMSE分别为6.682 m和10.384 m，DSM误差主要存在于坡度变化剧烈的地区，透视收缩和叠掩等几何畸变导致匹配结果不可靠。

The information on vertical forest structure is important to accurately estimate aboveground biomass. Stereoscopic radar has the capability to detect the vertical structure of forest stands. However, the radar image resolution is low in the early stages. The emergence of high-resolution radar data such as TerraSAR-X provides an opportunity to detect vertical forest structures using stereoscopic radar data. The goal of the current study is to examine the influence of critical matching parameters on DSM extraction using stereoscopic radar data.We evaluated the DSMs extracted using the TerraSAR-X stereoscopic radar data of stripmap mode over the Daxing'anling forest area and Changbai Mountain nature reserve. The critical parameters examined included the number of pyramid layers, matching window size, and search range.Result: (1) In the Daxing'anling study area where the parallax was small, the DSM accuracy improved as the number of pyramid layers decreased. We used five, six, and seven pyramid layers in the matching process. DSM errors within ± 10 m accounted for 81.8%, 77.7%, and 77.1% of the total number of pixels. Over the area where the parallax was large, such as in the Changbai Mountain study area, increasing the number of pyramids proved useful in correcting matching errors. The DSM obtained by the seven pyramid layers could reflect the correct terrain. (2) A large matching window improved the correlation of the image pair and reduced the noise caused by the lack of texture information in the forest area. The average correlation of the two study areas increased from 0.43 and 0.40 to 0.49 and 0.45, respectively, when a large window was applied over the two test areas. (3) Compared with that of the reference data, the RMSEs of the extracted DSM were 6.682 and 10.384 m over the Daxing'anling area and Changbai Mountain, respectively. Large errors occurred where the slope changed significantly. Significant slope changes resulted in large geometric distortions such as foreshortening and overlap. In these cases, corresponding matching points could not be found with our matching algorithm, resulting in the failure of matching results.The influences of critical matching parameters on DSM extraction were obvious. The proper settings of the number of pyramid layers, matching window size, and search ranges should be carefully evaluated.