Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.
본 논문에서는 위치기반서비스의 핵심기능을 담당하는 측위기술 중 흔히 사용되고 있는 삼각측량법과 최소자승법을 보정한 방법을 이용하여 객체의 위치를 결정하는 알고리즘의 산포를 감소시키는 방안을 연구하였다. 두 측위 방법에서 사용되는 거리값은 모두 동일한 보정과 필터링 과정을 적용하였으며, 프로그램 구현 후 실내에서 테스트를 실시하였다. 프로그램은 LabView 2010으로 구현하였고, 각각의 알고리즘을 모듈화하여 필터링 적용 전후 및 개선효과를 비교하기 쉽도록 구성하였다. 일반적인 환경에서 실험한 결과 삼각측량이 최소자승법보다 더 좋은 정확도를 보여주었고, 필터링 과정을 거칠수록 정확도가 향상되는 것을 확인하였다.