China Communications • May 2019
171
Keywords: indoor positioning; compressive
sensing; FM broadcasting; DTMB
With the rapid development of the economy
and the deepening of the informationization
process, people urgently need location infor-
mation in daily life. Outdoor positioning can
be appropriately solved by Global Navigation
Satellite System (GNSS), while indoor posi-
tioning becomes a burning question. From the
initial auxiliary GNSS technology, which is
based on outdoor positioning, to other wire-
less signals instead of satellites are completely
used, many researchers have provided some
indoor positioning options. There are some
common technologies such as Radio Frequen-
cy Identification positioning [1], ultrasonic
positioning [2], infrared positioning [3], Blue-
tooth positioning [4], cellular positioning[5],
visible light communication positioning [6],
ultra wideband positioning [7] and Wi-Fi
positioning [8]-[10]. Generally, light, geo-
magnetism, and images are utilized in original
positioning.
Wi-Fi positioning technology is one of the
hottest research topics in current indoor posi-
tioning domain. Wi-Fi positioning collects the
Abstract: Location-Based Services have be-
come an indispensable part of our daily life,
the sparsity of location nding makes it possi-
ble to estimate specic position by Compres-
sive Sensing (CS). Using public Frequency
Modulation (FM) broadcasting and Digital
Television Terrestrial Multimedia Broadcast-
ing (DTMB) signals, this paper presents an
indoor positioning scheme, which is consisted
of an ofine stage and an online stage. In the
offline stage, the Received Signal Strength
(RSS) at the Reference Points (RPs) is mea-
sured, including the average and variance of
public FM broadcasting and DTMB signals.
In the online stage, the K-Weighted Nearest
Neighbor algorithm is used to fulfill coarse
positioning, which is able to narrow the selec-
tion scope of locations and choose partial RPs
for accurate positioning. Then, the accurate
positioning is implemented through CS. Ex-
periment shows that the average positioning
error of the proposed scheme is 1.63m. What’s
more, a CS-based method has been proposed
in this paper to reduce the labor cost when
collecting data. Experiment shows the average
positioning error is 2.04m, with the advantage
of a 34% labor cost reduction. Experiment
results indicate that the proposed system is a
practical indoor positioning scheme.
Based on Compressive Sensing
Menghuan Yang
1,2
, Hong Wu
1,2,
*
, Zhiyang Liu
1,2
, Shuxue Ding
1,3
, Hongzhao Peng
1,2
1
College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China
2
Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Tianjin 300350, China
3
School of Computer Science and Engineering, University of Aizu, Aizu-Wakamatsu 9658580, Japan
* The corresponding author, email: wuhong@nankai.edu.cn
Received: Jul. 6, 2018
Revised: Nov. 12, 2018
Editor: Wei Wang
EMERGING TECHNOLOGIES & APPLICATIONS