Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Time and Space Attributes of Received Signal-Based Positioning Technology (TSARS) <s> An effective location algorithm, which considers non-line-of-sight (NLOS) propagation, is presented. By using a new variable to replace the square term and adding the loose variable, the problem becomes a mathematical programming problem, and then the NLOS propagation's effect can be evaluated. This method is simple and does not add much computation time. Compared with other methods, it has high accuracy. <s> BIB001 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Time and Space Attributes of Received Signal-Based Positioning Technology (TSARS) <s> We propose an IEEE 802.11b wireless LAN location system based on the time difference of arrival (TDOA) method. We confirm that IEEE 802.11b, as part of an indoor location system, is potentially highly accurate because of its broad bandwidth. When a location system is implemented in the IEEE 802.11b system, there are two important considerations; system architecture and required positioning accuracy. The accuracy of an indoor location system is apt to be degraded by multipath fading, which is a complex characteristic of indoor propagation. We developed a TDOA location system based on IEEE 802.11b, including several techniques such as access point (APs) synchronization, leading edge timing observations, and averaging with diversity. We experimentally evaluated the proposed system in a storehouse. The positioning accuracy when using ten APs and 3-branch diversity was 2.4 m at the 67/sup th/ percentile. <s> BIB002 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Time and Space Attributes of Received Signal-Based Positioning Technology (TSARS) <s> Nowadays, several systems are available for outdoor localization, such as GPS, assisted GPS and other systems working on cellular networks. However, there is no proper location system for indoor scenarios. Research into designing location systems for 802.11 networks is being carried out, so locating mobile devices on global networks (GSM/cellular + GPS + WLAN) finally seems feasible. The technique presented in this paper uses existing wireless LAN infrastructure with minor changes to provide an accurate estimation of the location of mobile devices in indoor environments. This technique is based on round-trip time (RTT) measurements, which are used to estimate distances between the device to be located and WLAN access points. Each RTT measurement estimates the time elapsed between the RTS (Request-to-Send) and the CTS (Clear-to-Send) frame of the 802.11 standard. By applying trilateration algorithms, an accurate estimation of the mobile position is calculated. <s> BIB003 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Time and Space Attributes of Received Signal-Based Positioning Technology (TSARS) <s> Location estimation as one of the most popular research areas has been recently attended because of wide range of its applications. K Nearest Neighbor (KNN) is a basic deterministic algorithm for locating which is widely used in fingerprinting approach. The performance of the KNN can be improved extensively by employing appropriate selection algorithm. In this paper, a novel algorithm called Dynamic KNN (D-KNN) which uses Angle of Arrival (AOA) and KNN as a hybrid method is proposed. This method comparing with KNN algorithm with constant K, selects the best number of nearest neighbors dynamically. It utilizes the adaptive antenna system to determine the user locative area by intersection of several obtained AOA. The best K neighbors which are located in the determined area can be selected to employ in the KNN. Analysis and simulation results are reported the best overall performance of D-KNN in different conditions. <s> BIB004
TSARS-based positioning technology mainly uses time and space attributes of received signal such as spatial distance, the time signal sending-receiving consumes and the spatial angle of signal. This technology includes TOA, AOA, and Time Difference of Arrival (TDOA) BIB004 . TOA calculates the distance according to the arrival time of the signal sent by different APs (Access Points) BIB001 . TDOA measures the delay time of the arrival signal BIB002 , while AOA measures the angle of the arrival signal. After obtaining the space-time relationship between the user and multiple APs, the user's position is calculated using trilateration BIB003 . To achieve high accuracy, at least three APs are required in this method. In some cases, additional hardware devices are needed, which leads to high deployment cost. As RF signal propagation in indoor environments is complex and can be affected by the multipath effect-human body interference and other factors-which creates many difficulties when measuring the RF signal and greatly affects positioning results.