Radio-Map Search Algorithm Based on Steepest Descent Principle
For most of the Ad-Hoc systems, position information is very important. Indoor scenario is a blind area of Global Navigation Satellite System (GNSS) service, which affects the application of Ad-Hoc technology. Fingerprint positioning technology is one of the most popular indoor localization methods. Searching strategy is one of the key techniques of fingerprint positioning. Because the data amount of the radio-map, which is used as the database of the system, is very big. Currently, the main accelerating measure of radio-map searching is clustering. But clustering brings some problems to the system, such as jittering and jamming. This paper proposes a novel radio-map searching strategy. Based on the steepest descent principle, the searching order is changed in the proposed method, compared with traditional clustering-positioning strategy. Thus, the radio-map is used in one piece, which is different from the traditional clustering-matching strategy. Simulations and experiments verified that the positioning accuracy of the proposal is better than that of the traditional method.
KeywordsDatabase searching Indoor positioning Fingerprint localization Steepest descent principle
This research is supported by the Fundamental Research Funds for the Central Universities DUT16RC (3)100, And partly supported by the National Natural Science Foundation of China (NO. 61701072).
- 1.Zou, G., Ma, L., Zhang, Z., Mo, Y.: An indoor positioning algorithm using joint information entropy based on WLAN fingerprint. In: Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), Hefei, China (2014)Google Scholar
- 2.Liu, X., Zhang, S., Zhao, Q., Lin, X.: A real-time algorithm for fingerprint localization based on clustering and spatial diversity. In: International Congress on Ultra-Modern Telecommunications and Control Systems, Moscow, Russa (2010)Google Scholar
- 3.Li, K., Bigham, J., Tokarchuk, L., Bodanese, E.L.: A probabilistic approach to outdoor localization using clustering and principal component transformations. In: 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC), Italian, Sardinia (2013)Google Scholar
- 5.Lee, C.W., Lin, T.N., Fang, S.H., Chou, Y.C.: A novel clustering-based approach of indoor location fingerprinting. In: 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), London, England (2013)Google Scholar
- 6.Premchaisawatt, S., Ruangchaijatupon, N.: Enhancing indoor positioning based on partitioning cascade machine learning models. In: 2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), Nakhon Ratchasima (2014)Google Scholar
- 7.Dousse, O., Eberle, J., Mertens, M.: Place learning via direct WiFi fingerprint clustering. In: 2012 IEEE 13th International Conference on Mobile Data Management, Bengaluru, Karnataka (2012)Google Scholar
- 8.Lin, H., Chen, L.: An optimized fingerprint positioning algorithm for underground garage environment. In: 2016 International Conference on Information Networking (ICOIN), Kota Kinabalu (2016)Google Scholar
- 9.Zhang, W., Hua, X., Yu, K., Qiu, W., Zhang, S.: Domain clustering based WiFi indoor positioning algorithm. In: 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares (2016)Google Scholar
- 10.Zhong, W., Yu, J.: WLAN floor location method based on hierarchical clustering. In: 2015 3rd International Conference on Computer and Computing Science (COMCOMS), Hanoi, Vietnam (2015)Google Scholar
- 11.Lin, Y.T., Yang, Y.H., Fang, S.H.: A case study of indoor positioning in an unmodified factory environment. In: 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea (2014)Google Scholar
- 12.Cai, D.: A retail application based on indoor location with grid estimations. In: 2014 International Conference on Computer, Information and Telecommunication Systems (CITS), Jeju, Korea (2014)Google Scholar