基于透视原理、地面试验中对于较高目标的观测存在着一定的偏差。这种偏差随传感器高度、观测角度、视场角大小、观测位置等多个因素改变。由于垄行作物空间结构和温度分布的复杂性 ,在采用较大视场角测量方向亮温的地面实验中 ,将不可避免地存在着误差。采用一个简化的三分量二维结构模型对这种误差进行初步的分析与估算。亮温三分量分别为植被、被阳光照到的亮土和植被阴影下的暗土。作物的结构简化为剖面为矩形的无限长平行体。通过对这三个分量在传感器视场中面积权重的计算来模拟目标结构、传感器高度、位置、视场角大小、观测角度等因素对测量结果产生的影响。模拟结果表明 ,在垂直观测中 ,视场中的植被权重往往被高估 ,偏差随传感器高度的降低急剧增加。在倾斜观测中 ,由于一种互补效应的产生 ,偏差被限制在一个较低的范围内。经过分析 ,减小误差的最有效办法是提高传感器高度。最后 ,实验数据与模拟结果进行了比较。恰当地选取模型输入 ,两种数据能非常好的吻合。 Based on the principle of perspective, there is a certain bias in the observation of higher targets in ground tests. This deviation with the sensor height, angle of observation, angle of view the size of the observation location and other factors change. Due to the complexity of the spatial structure and temperature distribution of ridge crops, there is an inevitable error in the ground experiments using the larger field of view to measure the direction of the bright temperature. A simplified three-component two-dimensional structure model is used to analyze and estimate this error. Bright temperature three components were vegetation, the sun shines bright soil and vegetation under the shadow of the soil. The structure of the crop is simplified as an infinitely parallel body with a rectangular section. Through the calculation of the area weights of these three components in the sensor’s field of view, the influences of the target structure, the height of the sensor, the position, the angle of view angle and the observation angle on the measurement results are simulated. The simulation results show that in the vertical observation, the vegetation weight in the field of view is often overestimated, and the deviation increases sharply with the decrease of the height of the sensor. In tilt observations, deviations are limited to a lower range due to a complementary effect. After analysis, the most effective way to reduce the error is to increase the height of the sensor. Finally, the experimental data and simulation results were compared. Proper selection of model input, the two data can be very good match.