Detecting Internal Anomalies In Tree Trunks Using Radar Wave With High-Resolution

In order to evaluate the health condition,it is necessary to detect the internal structure and abnormal.In this paper,ground penetrating radar(GPR)was used to detect the structure and abnormality of tree trunks.Nondestructive detection for standing tree trunk was more difficult than that for other materials because of eharacteristics of radar wave imaging of standing tree trunk itself.The super-resolution imaging technology was studied from two aspects:vertical resolution and lateral resolution.The Hilbert transform method was used to track the horizon,the relative dielectric constant was estimated by the reflection amplitude method.In particular,the multiple signal classification(MUSIC)algorithm was used to estimate the time delay of the overlapped radar echo.Due to the contours of tree trunks are mostly irregular,the point cloud data technique was applied to construct three-dimensional models and extract the irregular contours of trunks.Based on the above techniques,the internal structure detection software was developed.The feasibility and accuracy of the methods were examined through numerical simulations,laboratory and field measurements.The results demonstrated that the applied methodology allowed for accurate characterizations of the internal inhomogeneity.The point cloud technique resolved the trunk well by providing high-precision coordinate information.The MUSIC algorithm provided accurate estimation of time delay.These integrated techniques thus proved to be promising for observing tree trunks and other cylindrical objects.The applied approaches offer a great promise for future 3D reconstruction of tomographic images with radar wave.