云南地区RFID物流供应链的仿生定位感知MAC协议研究

无源射频识别(RFID)的物流供应链是物联网的重要应用领域之一，而其标签的MAC协议又是无源RFID物流供应链的支撑技术之一。由于云南地区物流具有识别数量多、识别对象物理性能复杂和识别系统应简单的特点，而传统的MAC协议把无源RFID作为随机多址系统、需对标签数做盲估计且较少考虑捕获效应，因此用于该地区存在识别时间较长、计算复杂度较高和标签易漏读等问题。针对传统MAC协议的这些问题，本项目拟构建一种仿超声波回声定位效应的标签信息传输模式及定位信息感知模式。首先把供应链中运动标签集合作为基本识别单位，实现非随机多址系统，然后借鉴动物对定位信息的获取与处理的反馈机理，采用仿超声导频序列获取空闲、成功和冲突的多维矢量信息，再以非盲的原则对该矢量信息进行处理，利用自适应学习和嵌入式二进制树算法来感知定位信息以实现对目标标签的识别，从而达到减少识别时间、降低复杂度和防止标签漏读的目的。

Supply chain (SC) based on passive radio frequency identification (RFID) is an improtant application field in Internet of Things, and medium access control (MAC) protocol for passive RFID tag is a key technology in SC based on passive RFID. Logistics in Yunnan region has the following features: too many identify items, complex physical property of identify items and simple identifycation systems. Since conventional MAC protocols consider passive RFID as a random access system, require blind tag number estimation and hardly consider capture effec, the convential protocols applied to the region have the disadvantages of longer identification delay, higher computational complexity and more identification ommision. For the disadvantages, this proposal will paropse a MAC protocol, and investigate a tag information transmission mode and a location perception mode based on bionic echolocation effect. In this proposal, we consider an RFID system as a un-random system by dividing tags in SC into several moved tag sets, and identify the tag by the echolocation information. First, the proposed MAC protocol will adopt simulated-ultrasonic pilots to collect a vector of idle, successful and collision information; second, the protocol will unblindly process the vector, and use an adaptive algorithm and a nested binary tree algorithm to percept the tag echolocation information; finaly, a reader can identify tags by the percepted information. From the methods above, this proposed protocol may reduce idientification delay, lower computational complexity and avoid identification ommision.