基于运动失稳补偿的非接触式人员身份与姿势识别方法
By employing motion instability compensation and the GesAuthNet dual-branch deep neural network, the reliability issues of user behavior and authentication on mobile platforms using millimeter-wave radar are addressed, achieving high-precision authentication and gesture recognition with robustness and stability.
CN122110050BActive Publication Date: 2026-07-17NANJING UNIV OF POSTS & TELECOMM
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING UNIV OF POSTS & TELECOMM
- Filing Date
- 2026-04-28
- Publication Date
- 2026-07-17
Smart Images
Figure CN122110050B_ABST
Abstract
本申请属于毫米波雷达感知与人体姿态识别领域，公开了一种基于运动失稳补偿的非接触式人员身份与姿势识别方法，包括：步骤1、通过自适应筛选静态背景点，估计雷达自运动速度，并对点云坐标和微多普勒频谱进行补偿；步骤2、搭建GesAuthNet双分支深度神经网络得到形态参数姿势参数；步骤3、结合形态参数构建身份认证器来认证用户的合法性，结合姿势参数构建手势分类器来识别用户的手势。本申请具有运动失稳补偿能力、鲁棒手势特征提取能力、高精度身份认证与手势识别、强稳定性与鲁棒性的优点。
Need to check novelty before this filing date? Find Prior Art