Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)
ÇѱÛÁ¦¸ñ(Korean Title) |
AP ÁÖº¯ ȯ°æ Á¤º¸¸¦ ÀÌ¿ëÇÑ WLAN ±â¹Ý ½Ç³» À§Ä¡ÃßÁ¤ ¾Ë°í¸®Áò |
¿µ¹®Á¦¸ñ(English Title) |
WLAN-based Indoor Positioning Algorithm Using The Environment Information Surround Access Points |
ÀúÀÚ(Author) |
±è¹Ì°æ
½Å¿ä¼ø
¹ÚÇöÁÖ
Mikyeong Kim
YoSoon Shin
Hyun-Ju Park
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¿ø¹®¼ö·Ïó(Citation) |
VOL 15 NO. 03 PP. 0551 ~ 0560 (2011. 03) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù WLANÀ» ±â¹ÝÀ¸·Î ÇÏ´Â ½Ç³» À§Ä¡ÃßÁ¤ ½Ã½ºÅÛ¿¡ ´ëÇÑ °ü½ÉÀÌ Áõ°¡ÇÏ°í ÀÖ´Ù. ´ëºÎºÐÀÇ WLANÀ» ±â¹ÝÀ¸·Î ÇÏ´Â À§Ä¡ÃßÁ¤ ½Ã½ºÅÛµéÀº fingerprinting ±â¹ýÀ» »ç¿ëÇÑ´Ù. fingerprinting ±â¹ý¿¡¼ À̵¿°´Ã¼ÀÇ À§Ä¡Á¤È®µµ´Â ÂüÁ¶ Á¡ÀÇ ¼ö¿¡ ºñ·ÊÇÑ´Ù. ÇÏÁö¸¸ ÂüÁ¶ Á¡ÀÇ ¼ö¿¡ µû¶ó training ´Ü°è¿¡¼ fingerprint µ¥ÀÌÅͺ£À̽º¸¦ »ý¼ºÇϱâ À§ÇØ ¸¹Àº ½Ã°£°ú ³ë·ÂÀ» ¿ä±¸ÇÑ´Ù. ÀÌ·¯ÇÑ ¹®Á¦Á¡µéÀ» ÇØ°áÇϱâ À§ÇØ, º» ³í¹®¿¡¼´Â WLAN ±â¹Ý APµéÀÇ ÁÖº¯ ȯ°æÁ¤º¸¸¦ ÀÌ¿ëÇÏ¿© AP¿Í À̵¿ °´Ã¼ °£ÀÇ °Å¸®¸¦ »êÃâÇÏ¿© À§Ä¡¸¦ ÃßÁ¤ÇÏ´Â »õ·Î¿î ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÏ¿´À¸¸ç, À̵¿ °´Ã¼ÀÇ À§Ä¡ Á¤È®µµ¸¦ °³¼±Çϱâ À§ÇÏ¿© Á¦¾È ¾Ë°í¸®Áò¿¡ ÆÄƼŬ ÇÊÅ͸¦ Àû¿ëÇÏ¿´´Ù. ÀÌ ¾Ë°í¸®ÁòÀ» ±¸ÇöÇϱâ À§ÇÏ¿© ¸ÕÀú APµéÀÇ ÁÖº¯¿¡ Á¸ÀçÇÏ´Â º®, ö¹®, À¯¸®¹®, ÆÄƼ¼Ç µî°ú °°Àº ȯ°æ Á¤º¸ µ¥ÀÌÅͺ£À̽º¸¦ ±¸ÃàÇÏ¿´°í À§Ä¡ ÃßÁ¤Àº °¨¼è ¸ðµ¨°ú °æ·Î ¼Õ½Ç ¸ðµ¨À» ÀÌ¿ëÇÏ¿´´Ù. Á¦¾È ¾Ë°í¸®ÁòÀ» ½ÇÇèÀ» ÅëÇÏ¿© È®ÀÎÇÑ °á°ú À§Ä¡ Á¤È®µµ´Â ³·¾ÒÁö¸¸ fingerprintingÀÇ ¹®Á¦Á¡À» ÇØ°áÇÏ¿´´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Recently, There has been increasing concern about WLAN-based indoor positioning system. Most of the existing WLAN-based positioning systems use a fingerprinting method as a main approach. In the fingerprinting approach, the accuracy of the location of a mobile objects is proportional to the number of reference points. However, depending on the increasing number of reference points in the training phase, it requires more time and effort to create fingerprint database. To solve these problems, we propose the new indoor positioning algorithm that calculate the distance between a mobile objects and an AP using the information of surrounding environment WLAN based APs and applied the particle filter to the proposed algorithm in order to improve the accuracy of the estimated location in this paper. To implement this algorithm, at first environmental information database such as wall, iron door, glass door, partition etc. existing in the periphery of the AP should be established. The positioning use attenuation model and path loss model. Our experimental results with proposed algorithm are verified that the positioning accuracy was low but solved the problems with fingerprinting, compared with other positioning algorithms.
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Å°¿öµå(Keyword) |
À§Ä¡ÃßÁ¤
ÆÄƼŬ
ÇÊÅÍ
¾Ë°í¸®Áò
position estimation
particle
filter
algorithm
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ÆÄÀÏ÷ºÎ |
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