摘要： 采用3D空间内RFID标签阵列布局，以感知棉花中异物的数量、位置及类型。以标签的接收信号强度（RSS）和相位为特征量，提出欧几里得距离比算法与最小二乘法以提升定位成功率。基于不同异物对信号特征的差异化影响，构建决策树模型实现异物类型的感知。经实验验证，定位误差优化后控制在5%以内，且能精准识别棉花中的四种异物类型，展现出良好的感知与识别性能。

中图分类号：TP391.45 文献标志码：A DOI: 10.16157/j.issn.0258-7998.256927
中文引用格式： 李彦旭，朱悦诚. 基于RFID标签阵列对棉花内异物的定位识别[J]. 电子技术应用，2026，52(4)：139-143.
英文引用格式： Li Yanxu，Zhu Yuecheng. Positioning and identification of foreign substances in cotton based on RFID tag arrays[J]. Application of Electronic Technique，2026，52(4)：139-143.

Positioning and identification of foreign substances in cotton based on RFID tag arrays

Abstract： In this paper, an RFID tag array layout in 3D space is adopted to perceive the quantity, location and type of foreign objects in cotton. Taking the received signal strength (RSS) and phase of the tag as characteristic quantities, the Euclidean distance ratio algorithm and the least square method are proposed to improve the positioning success rate. Based on the differentiated influence of different foreign objects on signal characteristics, a decision tree model is constructed to achieve the perception of foreign object types. Experimental verification shows that the positioning error is controlled within 5% after optimization, and it can accurately identify four types of foreign substances in cotton, demonstrating excellent perception and recognition performance.

Key words : RFID tag array；positioning；decision tree model；identification