Determination of an Indoor Target Position: An Accurate and Adaptable Approach Based on Differential Positioning. (13th December 2019)

• Record Type: Journal Article
• Authors: Wang, Siye; Ding, Chang; Huang, Weiqing; Zhang, Yanfang; Jiang, Jianguo; Zhu, Shaoyi; Cui, Yue; Lin, Jun-yu
• Other Names: Monti Giuseppina Academic Editor.
• Is Part Of: International journal of antennas and propagation. Volume 2019(2019)
• Publication Date: 2019-12-13
• Subjects: Electronic apparatus and appliances -- Periodicals; Antennas (Electronics) -- Periodicals; Radio wave propagation -- Periodicals; Antennes (Électronique); Ondes radioélectriques -- Propagation; Antennas (Electronics); Electronic apparatus and appliances; Radio wave propagation; Electronic journals; Periodicals; 621.382405
• DOI: 10.1155/2019/6202095
• Languages: English
• ISSNs: 1687-5869

Abstract

Abstract : The growing demand for new products that rely on the accurate identification of a target's location indoors, while remaining mindful of cost, continues to drive research in this important and challenging area. Researchers are actively pursuing algorithmic improvements to eliminate errors introduced from complex interference factors present in indoor, wireless communication environments. In this work, we adopt a differential signal strength method in the design of our new indoor localization algorithm. The proposed algorithm reduces errors in the time domain by smoothing out the wireless signal fluctuations, thus stabilizing the signal; a single exponential algorithm is applied to the signal strength parameters collected to accomplish this. The target's position is then computed by utilizing both the plane geometric method and difference localization theory. This combination of techniques is reasonable for the environment under consideration (small scale, wireless), as the multipath effects for the signal are approximately equal under these conditions. In addition, the proposed approach is compatible with a wide variety of technologies (e.g., RFID and Bluetooth); it can be cost-effectively deployed by leveraging an existing hardware infrastructure. The proposed approach has been implemented and experimentally validated. The test results are very promising: they indicate that our algorithm improves the positioning accuracy by 70%–80% in comparison with the trilateration and LANDMARC positioning algorithms.