基于轻小型无人机雷达的植被高度反演方法

针对目前主流雷达传感器难以满足轻小型无人机载荷需要，且存在着数据获取成本高及算法模型复杂的问题，在自行研制的一种高度集成、轻量化且具有高可靠性的轻小型无人机雷达系统基础上，发展了一种植被高度信息反演新方法。该方法中使用二维滤波抑制直耦波能量，基于剩余图像熵的自适应主元分析去噪方法解决传统方法主元选择不稳定的问题，并基于互相关信息的后向投影算法进一步增强目标信号，最后应用Sobel算子提取植被高度。实验结果表明，该方法反演得到的植被高度和验证数据的相关性达到0.92,均方根误差可达1.28 m。

Vegetation height inversion method based on light-weighted and small UAV-radar

At present, the mainstream radar sensors are difficult to meet the demands of the light-weighted and small unmanned aerial vehicle (UAV), which usually need high cost of data acquisition and complicate models of algorithm. A highly integrated, lightweight and reliable radar system is designed, which can be carried on the light-weighted and small UAV. Based on this system, a novel method has been developed for vegetation height information inversion. The inversion algorithm suppress the direct coupled wave by two-dimensional filtering, settle the unstable selection of principle component by the adaptive principle component analysis denoising method with residual image entropy, further enhance the target signal by the back-projection algorithm based on cross-correlation information, and finally extract the vegetation height by implementing Sobel operator. The experiment results show that the correlation between the vegetation height derived from the proposed method and the verified data is 0.92, and the root mean square error is 1.28 m.