A forest litter water content hierarchical detection method based on broadband microwave and width learning
By using a multi-layer antenna array and a width learning system, the problems of changes in litter accumulation thickness and noise interference in microwave detection equipment have been solved, achieving high-precision detection of litter moisture content, which is suitable for field equipment with limited computing power.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING TECH & BUSINESS UNIV
- Filing Date
- 2026-04-23
- Publication Date
- 2026-07-17
AI Technical Summary
Existing microwave detection equipment cannot adapt to changes in the thickness of litter accumulation, feature selection is easily affected by noise, and traditional prediction models struggle to balance efficiency and accuracy.
A multi-layer antenna array is used to acquire signals. The air medium layer and the effective test medium layer are identified by differential comparison. The high-dimensional microwave frequency points are evaluated by combining the inter-class divergence and intra-class divergence ratios. A width learning system is introduced for feature screening and prediction. The ridge regression formula is used for moisture content detection.
It breaks through the bottleneck of detecting the varying thickness of forest litter accumulation, improves detection accuracy and anti-interference ability, is suitable for deployment of field detection equipment with limited computing power, and achieves high-precision detection of litter moisture content.
Smart Images
Figure CN122409705A_ABST