红外与毫米波学报2025，Vol.44Issue(6)：828-839,12.DOI:10.11972/j.issn.1001-9014.2025.06.002
基于反射层析激光雷达的目标轮廓图像重建
Target contour image reconstruction based on reflective tomography LiDAR
摘要
Abstract
Reflective tomography LiDAR(RTL)reconstructs target contours by acquiring laser echo projection data,but incomplete angular detection in practice often leads to insufficient projection data.To address this issue,the authors propose a target contour reconstruction method that combines the structural sparsity of projection data with a super-reso-lution convolutional neural network(SRCNN),based on the principles and technical implementation of RTL.This ap-proach effectively resolves the failure of traditional algorithms when projection data suffers from severe angular deficien-cy.Different from conventional RTL imaging methods that directly incorporate sparse reconstruction models,the au-thors first recover full-angle projection data by integrating sparse constraints with SRCNN based on geometry prior of the projection data,followed by standard RTL imaging algorithms to achieve complete target contour reconstruction.To validate the effectiveness of the proposed method,the authors design laser echo projection simulations based on the fac-et model and conduct field experiments.The results demonstrate that the authors achieve high-quality target contour re-construction under varying levels of projection data missing conditions.关键词
反射层析激光雷达/回波投影数据/不完备角度/目标轮廓图像重建Key words
reflective tomography LiDAR(RTL)/echo projection data/incomplete angle/target contour image reconstruction分类
数理科学引用本文复制引用
郭睿,楼荑,张鑫源,郭亮,胡以华..基于反射层析激光雷达的目标轮廓图像重建[J].红外与毫米波学报,2025,44(6):828-839,12.基金项目
国家自然科学基金(61871389) （61871389）
国防科技大学自主创新科学基金(24-ZZCX-JDZ-43) （24-ZZCX-JDZ-43）
国防科技大学青年自主创新科学基金(ZK23-45) Supported by the National Natural Science Foundation of China(61871389) （ZK23-45）
the National University of Defense Technology Inde-pendent Innovation Scientific Fund(24-ZZCX-JDZ-43) （24-ZZCX-JDZ-43）
the NUDT Youth Independent Innovation Scientific Fund(ZK23-45) （ZK23-45）
