A novel 3D position measurement and structure prediction method for RFID tag group based on deep belief network

Zhang, Xiao; Yu, Xiaolei; Zhou, Di; Zhao, Zhimin; Zhang, Wenjie; Lin, Li; Liu, Zhenlu

doi:10.1016/j.measurement.2018.12.071

Cited by 10 publications

(9 citation statements)

References 33 publications

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“…However, the performance of existing protocols in terms of execution time is not satisfactory. To obtain better time efficiency, a new protocol for unknown tag identification is proposed [3] . RFID technology has been widely used in logistics, object tracking and healthcare [4] .…”

Section: Inroductionmentioning

confidence: 99%

RFID-based identification and distance determination of objects

Qiu

Shen

Zhang

2023

2022 2nd Conference on High Performance Computing and Communication Engineering (HPCCE 2022)

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The simultaneous implementation of object ranging and object calibration based on received signal strength indication (RSSI) using RFID is the main focus of this research paper. Ranging technology is a low-cost and low-complexity distance measurement technology that is widely used in distance-based localization technology for wireless sensor networks. Due to the influence of non-visible range and multipath transmission in indoor environment, the ranging error is relatively large. The linear fitting characteristics of RSSI ranging model with path loss model in indoor environment are analyzed for the basic method of wireless signal ranging, signal channel characteristics affecting ranging in indoor environment, RSSI model and the actual measurement values of the relationship between RSSI and distance in indoor environment. In addition, the object calibration is carried out by using the electronic tag of RFID, and the experiment shows that the determination of the distance of the object can be realized while the object calibration is carried out.

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Section: Inroductionmentioning

confidence: 99%

RFID-based identification and distance determination of objects

Qiu

Shen

Zhang

2023

2022 2nd Conference on High Performance Computing and Communication Engineering (HPCCE 2022)

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“…The transformed interval of the revised normalization algorithm could be changed based on actual demands. The computation method of the improved normalization is shown in Equation (12), which could map the data into a value between 1 to…”

Section: Fused Distancementioning

confidence: 99%

“…According to various structures of buildings and layouts of indoor environments, indoor positioning techniques can be divided into building dependence and building independence methods. The former methods were primarily based on electromagnetic and acoustic signals, such as ultra-wideband (UWB) [2][3][4], Bluetooth [5,6], wireless fidelity (Wi-Fi) [7][8][9], radio frequency identification (RFID) [10][11][12], ultrasonic or acoustic [13,14], geo-magnetism [15,16], pseudolite [17,18], and so on. The latter ones were based on computer vision [19,20] and inertial navigation system (INS) or pedestrian dead reckoning (PDR) [21,22].…”

Section: Introductionmentioning

confidence: 99%

DBSCAN and TD Integrated Wi-Fi Positioning Algorithm

Cao

Wang

et al. 2022

Remote Sensing

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A density-based spatial clustering of applications with noise (DBSCAN) and three distances (TD) integrated Wi-Fi positioning algorithm was proposed, aiming to enhance the positioning accuracy and stability of fingerprinting by the dynamic selection of signal-domain distance to obtain reliable nearest reference points (RPs). Two stages were included in this algorithm. One was the offline stage, where the offline fingerprint database was constructed and the other was the online positioning stage. Three distances (Euclidean distance, Manhattan distance, and cosine distance), DBSCAN, and high-resolution distance selection principle were combined to obtain more reliable nearest RPs and optimal signal-domain distance in the online stage. Fused distance, the fusion of position-domain and signal-domain distances, was applied for DBSCAN to generate the clustering results, considering both the spatial structure and signal strength of RPs. Based on the principle that the higher resolution the distance, the more clusters will be obtained, the high-resolution distance was used to compute positioning results. The weighted K-nearest neighbor (WKNN) considering signal-domain distance selection was used to estimate positions. Two scenarios were selected as test areas; a complex-layout room (Scenario A) for post-graduates and a typical large indoor environment (Scenario B) covering 3200 m2. In both Scenarios A and B, compared with support vector machine (SVM), Gaussian process regression (GPR) and rank algorithms, the improvement rates of positioning accuracy and stability of the proposed algorithm were up to 60.44 and 60.93%, respectively. Experimental results show that the proposed algorithm has a better positioning performance in complex and large indoor environments.

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“…In Zhuang et al (2018), the wavelet threshold was proposed to denoise the multi-tag image, and the noise signal at different scales selects the wavelet coefficients of the corresponding noise level. In Guo et al (2017) and Zhuang et al (2019), the image restoration based on knife edge and Wiener filter was proposed, in which knife edge calculates point spread function (PSF), and then Wiener filter restores the degraded image. But it must add known blur kernel to multi-tag imaging.…”

Section: Introductionmentioning

confidence: 99%

RFID multi-tag dynamic detection measurement based on conditional generative adversarial nets and YOLOv3

Lin

Liu

et al. 2021

Transactions of the Institute of Measurement and Control

Self Cite

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The quality of multi-tag imaging greatly affects the effective detection of multi-tag. When multi-tag moves rapidly, the image may have serious dynamic blur, and tags can not be detected efficiently. In previous work, it is generally assumed that blur kernel and noise stationary to improve image quality. However, the dynamic deblurring of Radio Frequency Identification (RFID) multi-tag imaging is an ill-posed inverse problem. In this paper, firstly, blur-sharp multi-tag image pairs are made by superimposing and averaging the adjoin random frames. Then, we propose blind deblurring for dynamic RFID multi-tag imaging based on conditional generative adversarial nets (CGANs), which adds perceptual loss and content loss to generator to make image sharper. Finally, tags are detected by YOLOv3 in real time in end-to-end manner. Experimental results demonstrate that PSNR is at least 0.56dB higher and speed is at least 31.25 % faster than that of the current improved convolution neural networks (CNN). CGANs can remove image blur better, which has great superiority in the field of dynamic multi-tag imaging. In addition, YOLOv3 detects multi-tag quickly, thereby improving the detection accuracy.

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A novel 3D position measurement and structure prediction method for RFID tag group based on deep belief network

Cited by 10 publications

References 33 publications

RFID-based identification and distance determination of objects

RFID-based identification and distance determination of objects

DBSCAN and TD Integrated Wi-Fi Positioning Algorithm

RFID multi-tag dynamic detection measurement based on conditional generative adversarial nets and YOLOv3

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