Low Cost Indoor Position Estimation Method Using Gaussian distribution and Poisson Distribution

Indoor position estimation applications is demanded extremely in commercial facilities. Recently, popular indoor commercial facilities have many wireless LAN access points (APs) installed. In addition, it is possible to observe the received signal strength indications (RSSI) from the APs even if these are not connected to the network. In this paper, we will consider the indoor location estimation scheme using wireless LAN. The position estimation for a smartphone (user terminal) is performed by acquiring the RSSI from the APs. An influence of multipath and shadowing can't be ignored in the commercial facility. Also, the APs' location are not known since each store installs them freely. Attenuation due to shielding affects obtained distance with Lateration. For this reason, Finger Print is effective in commercial facilities. The required position estimation accuracy is 4-10 m which is the size of one store. It is required that the position can be estimated immediately after data measurement. Therefore, an algorithm based on Bayesian estimation that takes a long time to create databases is not suitable. It is well-known that the radio wave distribution obeys the Gaussian distribution. Thence, it is possible to interpolate the database from few observation data. In this paper, we proposed a position estimation technique using an AP reliability summation method. The AP reliability is defined as the Gaussian distribution. On the other hand, user's position may be estimated incorrectly due to AP observed infrequently. Considering this, we propose position estimation technique employing an AP reliability weighted on Poisson distribution by observation the number of times. By using experiments at commercial facilities, we confirmed reduction of time required for database creation and improvement of accuracy by simple and low cost location estimation method using the above two proposed methods.