원문정보
초록
영어
With the rapid development of wireless communication and embedded system, wireless positioning systems are paid more and more attention to. Radio Frequency Identification (RFID) localization system is getting more important, due to its own advantages, such as no contact, non-line-of-sight nature, promising transmission range and cost-effectiveness. To improve the accuracy of active RFID indoor location system, some traditional RFID indoor localization systems were studied, such as LANDMARC. On this basis, an adaptive self-correction location algorithm was presented, which uses a positioning correction value to correct the positioning result. N minimum errors and position results are obtained by using adaptive K-nearest neighbor algorithm N times. The positioning correction value calculated with N minimum errors in weighted way. The sum of the positioning average value and the positioning correction value would be the final positioning results. Experimental results show that compared with adaptive K-nearest neighbor algorithm and error self-correction algorithm, the proposed method provides a higher accuracy and stability.
목차
1. Introduction
2. Analyzing of LANDMARC and Error Self-correction
2.1. Principle of LANDMARC
2.2. Error Self-correction
2.3. Problems with Error Self-correction
3. Adaptive Self-correction
4. Localization Algorithm Based on Adaptive Self-correction
5. Experiments and Analysis
5.1. Noise Model
5.2. Comparation of the Positioning Average Error under Different N
5.3. Positioning Accuracy
6. Conclusions and Future Work
Acknowledgement
References