Abstract
In this paper, we proposed an indoor lightwave positioning system contains correlation operations with genetic algorithms. The implemented CDMA signaling system by spread spectrum (SS) codes can locate the position of the robot receiver as against noise interference. In the allocated LED transmitters, each channel of the transmitted signals is modulated into a series of maximal-length sequence code (M-sequence code) by LED light blinking. In the robot receiver, correlation peaks detection between received summed signal and each local replica signal is based to estimate the distance from each transmitter to the robot. We choose three transmitters among five to closest to the robot for more reliable positioning information. The robot positioning is first estimated by time difference of arrival (TDOA) and then genetic algorithm (GA) optimization is applied for more accurate robot location. We finally simulate out the TDOA result and analyze the accuracy of the robot position.
| Original language | English |
|---|---|
| Pages (from-to) | 304-311 |
| Number of pages | 8 |
| Journal | Procedia Computer Science |
| Volume | 110 |
| DOIs | |
| Publication status | Published - 2017 Jan 1 |
| Event | 14th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2017 - Leuven, Belgium Duration: 2017 Jul 24 → 2017 Jul 26 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
Cite this
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Integrating Correlation Acquisition with Location Optimization for Accurate Indoor Lightwave Robot Positioning. / Liu, Chun Chieh; Cheng, Jhe Ren; Huan, Jen-Fa.
In: Procedia Computer Science, Vol. 110, 01.01.2017, p. 304-311.Research output: Contribution to journal › Conference article
TY - JOUR
T1 - Integrating Correlation Acquisition with Location Optimization for Accurate Indoor Lightwave Robot Positioning
AU - Liu, Chun Chieh
AU - Cheng, Jhe Ren
AU - Huan, Jen-Fa
PY - 2017/1/1
Y1 - 2017/1/1
N2 - In this paper, we proposed an indoor lightwave positioning system contains correlation operations with genetic algorithms. The implemented CDMA signaling system by spread spectrum (SS) codes can locate the position of the robot receiver as against noise interference. In the allocated LED transmitters, each channel of the transmitted signals is modulated into a series of maximal-length sequence code (M-sequence code) by LED light blinking. In the robot receiver, correlation peaks detection between received summed signal and each local replica signal is based to estimate the distance from each transmitter to the robot. We choose three transmitters among five to closest to the robot for more reliable positioning information. The robot positioning is first estimated by time difference of arrival (TDOA) and then genetic algorithm (GA) optimization is applied for more accurate robot location. We finally simulate out the TDOA result and analyze the accuracy of the robot position.
AB - In this paper, we proposed an indoor lightwave positioning system contains correlation operations with genetic algorithms. The implemented CDMA signaling system by spread spectrum (SS) codes can locate the position of the robot receiver as against noise interference. In the allocated LED transmitters, each channel of the transmitted signals is modulated into a series of maximal-length sequence code (M-sequence code) by LED light blinking. In the robot receiver, correlation peaks detection between received summed signal and each local replica signal is based to estimate the distance from each transmitter to the robot. We choose three transmitters among five to closest to the robot for more reliable positioning information. The robot positioning is first estimated by time difference of arrival (TDOA) and then genetic algorithm (GA) optimization is applied for more accurate robot location. We finally simulate out the TDOA result and analyze the accuracy of the robot position.
UR - http://www.scopus.com/inward/record.url?scp=85028638182&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028638182&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2017.06.099
DO - 10.1016/j.procs.2017.06.099
M3 - Conference article
AN - SCOPUS:85028638182
VL - 110
SP - 304
EP - 311
JO - Procedia Computer Science
JF - Procedia Computer Science
SN - 1877-0509
ER -