Passive multiple target indoor localization based on joint interference cancellation in RFID system

Passive multiple target indoor localization based on joint interference cancellation in RFID system

Citation Author(s):
Meng
Liu
Submitted by:
Meng Liu
Last updated:
Wed, 01/23/2019 - 07:07
DOI:
10.21227/b8j8-6r18
License:
Dataset Views:
174
Share / Embed Cite

CATEGORIES

Abstract: 

Radio frequency identification (RFID) provides a simple and effective solution to the passive indoor localization. The conventional wisdom about RFID localization is utilizing reference tags. It performs well in tag or single passive target localization. However, in the passive multiple target scenario, reference tag based localization suffers from some limitations, including the array aperture, mutual coupling of reference tags, and coherent superimposition of target signals. These problems are harmless and ignored in tag or single passive target localization, but degrade the performance severely in passive multiple target scenario. Therefore, in this letter, the authors propose a joint interference cancellation method to mitigate the effect of these limitations. Uniform circle array (UCA) of reference tags were utilized to reduce the limitation of array aperture. A carefully designed relative position of adjacent reference tags and a modified channel model were combined to reduce the mutual coupling. A virtual distributed radar was utilized to reduce the false positive and false negative estimations. The system was evaluated in real indoor environment using noodles and colas as targets. The accuracy of target number estimation is 97.5%, the spatial resolution is about 50cm, and the median error of 2-D multi-target localization is about 5.5cm.

Instructions: 

Passive indoor localization has been researched for many years[1]-[4].The goal of this challenging problem is to estimate the coordinates of targets which do not carry any auxiliary devices. The radio frequency identification (RFID) technology presents an efficient and low-cost indoor localization solution. The pioneers mostly focused on the localization methods for RFID reader [5], tags [6], or single tag-free target [7]. These kind of methods are excellent but unsuitable for the passive multiple target scenario. There are two main problems. One is the effect of interference that came from the array and among targets. The other is how to distinguish the coherent signals, in other words, to estimate the number of targets from the superimposed received signal. Some traditional methods such as the akaike information criterion (AIC) and gerschgorin disks estimation (GDE) [8] are disable to estimate the number of coherent signals. The sub-space methods like space smoothing (SS) MUSIC algorithm [9] can distinguish the multiple incident coherent signals efficiently only in the far field assumption but become almost invalid in the near field indoor environment.

Recently, for the passive multiple target localization, channel blocking or shadowing loss [10], [11] was analyzed and utilized. The transmitters and receivers were deployed densely as the uniform linear arrays to make the measured area almost full of the line of sight (LOS) propagations. The changes of channel parameters indicate the position information. Radio tomographic imaging (RTI) method [12], which is inspired from medical and geophysical imaging systems, is also based on shadowing loss. The measured area was divided into small pixel and the shadowing loss is approximated as a weighted summation of attenuation of each pixel [13]. The ellipsoid weighted model [14] was used to determine the weight of each link. However, the “interest range” of channel blocking is small. The target, which is more than 15.8cm away from the LOS path, will have no effect on the received signal strength (RSS) at 2.4 GHz frequency [15]. This means a large number of transceiver nodes to ensure the coverage of LOS in the measured area. Besides, the method based on channel blocking also need to match the paths with targets, and this process is usually computational infeasible [16]. 

Against this background, we propose a passive multiple target localization utilizing the diffuse reflection of the targets. Spatial spectrum was calculated by 2-Dimensional maximum likelihood function and a joint interference cancellation method was introduced to make spatial spectrum work well. Uniform circle array (UCA) of reference tags were deployed instead of uniform linear array (ULA) to reduce the aperture limitation. A carefully designed relative position of adjacent reference tags and a modified channel model were combined to reduce the mutual coupling. At last, a virtual distributed radar was constructed to reduce false positive and false negative estimations. 

 

 

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Login or subscribe now. Sign up to be a Beta Tester and receive a coupon code for a free subscription to IEEE DataPort!

Embed this dataset on another website

Copy and paste the HTML code below to embed your dataset:

Share via email or social media

Click the buttons below:

facebooktwittermailshare
[1] Meng Liu, "Passive multiple target indoor localization based on joint interference cancellation in RFID system", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/b8j8-6r18. Accessed: Dec. 09, 2019.
@data{b8j8-6r18-18,
doi = {10.21227/b8j8-6r18},
url = {http://dx.doi.org/10.21227/b8j8-6r18},
author = {Meng Liu },
publisher = {IEEE Dataport},
title = {Passive multiple target indoor localization based on joint interference cancellation in RFID system},
year = {2018} }
TY - DATA
T1 - Passive multiple target indoor localization based on joint interference cancellation in RFID system
AU - Meng Liu
PY - 2018
PB - IEEE Dataport
UR - 10.21227/b8j8-6r18
ER -
Meng Liu. (2018). Passive multiple target indoor localization based on joint interference cancellation in RFID system. IEEE Dataport. http://dx.doi.org/10.21227/b8j8-6r18
Meng Liu, 2018. Passive multiple target indoor localization based on joint interference cancellation in RFID system. Available at: http://dx.doi.org/10.21227/b8j8-6r18.
Meng Liu. (2018). "Passive multiple target indoor localization based on joint interference cancellation in RFID system." Web.
1. Meng Liu. Passive multiple target indoor localization based on joint interference cancellation in RFID system [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/b8j8-6r18
Meng Liu. "Passive multiple target indoor localization based on joint interference cancellation in RFID system." doi: 10.21227/b8j8-6r18