Indoor positioning through an iterative method in dense Wi-Fi-direct networks with Wi-Fi direct devices

An iterative algorithm that estimates the position of tracked subjects based on the estimated position of other tracked subjects nearer to the reference points is proposed. The method starts by estimating the position of all tracked subjects (client) by trilateration using Wi-Fi radio signal strength indicators (RSSI) from known Access Points. Subjects nearest to the access points will then be possibly rated as the access points for next iteration. The iteration process stops until the estimation difference between current and previous estimates is less than a threshold value. Kalman filter is added to minimize the impact of irregular RSSI. The proposed method requires sufficient number of clients in the tracked area. The method could be implemented on a mobile device within existing Wi-Fi network without the need for additional devices or infrastructure.