Journal
SENSORS
Volume 15, Issue 11, Pages 29661-29684Publisher
MDPI
DOI: 10.3390/s151129661
Keywords
WSNs; three-dimensional deployment; calibration; localization
Funding
- National Natural Science Foundation of China [61273078, 61471110]
- China Postdoctoral Science Special Foundation [2014T70263]
- China Postdoctoral Science Foundation [2012M511164]
- Chinese Universities Scientific Foundation [N130404023, N110804004, N140404014]
- Liaoning Doctoral Startup Foundation [20121004]
- Foundation of Liaoning Educational Commission [L2014090]
Ask authors/readers for more resources
Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furniture. However, a 3D system, like Cricket, can reduce the negative impact of obstacles to the maximum extent and guarantee the sensing signal transmission by using the line of sight (LOS). However, most of the traditional localization methods are not available for the new deployment mode. In this paper, we propose the self-localization of beacons method based on the Cayley-Menger determinant, which can determine the positions of beacons stuck in the ceiling; and differential sensitivity analysis (DSA) is also applied to eliminate measurement errors in measurement data fusion. Then, the calibration of beacons scheme is proposed to further refine the locations of beacons by the mobile robot. According to the robot's motion model based on dead reckoning, which is the process of determining one's current position, we employ the H-infinity filter and the strong tracking filter (STF) to calibrate the rough locations, respectively. Lastly, the optimal node selection scheme based on geometric dilution precision (GDOP) is presented here, which is able to pick the group of beacons with the minimum GDOP from all of the beacons. Then, we propose the GDOP-based weighting estimation method (GWEM) to associate redundant information with the position of the target. To verify the proposed methods in the paper, we design and conduct a simulation and an experiment in an indoor setting. Compared to EKF and the H-infinity filter, the adopted STF method can more effectively calibrate the locations of beacons; GWEM can provide centimeter-level precision in 3D environments by using the combination of beacons that minimizes GDOP.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available