Improved RSS Data Generation Method Based on Kriging Interpolation Algorithm
- PDF / 1,149,027 Bytes
- 13 Pages / 439.37 x 666.142 pts Page_size
- 8 Downloads / 231 Views
Improved RSS Data Generation Method Based on Kriging Interpolation Algorithm Yongxing Wang1 · Gang Hua2 · Weige Tao1 · Lei Zhang1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The traditional method of constructing RSS fingerprint database costs a large amount of time and human resource due to adopting the point-by-point method to sample RSS value, and consequently the positioning method based on RSS fingerprint model is difficult to be widely applied. In this paper, a RSS data generation method is proposed based on Kriging spatial interpolation algorithm. The proposed method firstly selects the model of variogram according to the properties of field, and subsequently solves the variogram by using the observation points with the restriction of unbiased estimation and minimum estimation variance, finally calculates RSS data for the estimation points. The experimental results show that the proposed method accurately acquires the RSS data of estimation points while the required reference points are much less than that of conventional point-by-point method. Keywords RSS fingerprint · Kriging interpolation algorithm · Target position · Fingerprint model
1 Introduction With the rapid development of mobile communication technology, more and more researchers pay attention to the location-based services, of which the open problem is how to position users accurately. Among the numerous wireless positioning algorithm, the most widely used positioning method is RSS (Received Signal Strength)-based method owing to the simple deployment, low-cost hardware and single parameter etc., which has been the research hotspot until now [1].
This work is supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 18KJB510011), The National Natural Science Foundation of China (Nos. 51574232, 61701202) * Yongxing Wang [email protected] 1
School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, China
2
School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221008, Jiangsu, China
13
Vol.:(0123456789)
Y. Wang et al.
The RSS-based positioning methods are classified into two categories: one is based on signal attenuation model(SAM) and the other is based on RSS fingerprint model(FPM). In SAM, the attenuation information is transformed into range information, and subsequently the range information is used to calculate users’ coordinate positions based on the relative method such as triangulation. However, in a confined space, the propagation of wireless signal is very complicated, and therefore, the RSS is influenced by some unmeasurable factors, such as penetration loss of the surface, multipath effect and co-channel interference etc.. For instance, in 2.4 GHZ wireless band, the domestic microwave oven and Bluetooth equipment are interference source [2, 3]. Generally, in confined space, the SAM-based position method generates considerable position error due
Data Loading...
