1.  Field
The following description relates generally to positioning techniques, and more particularly to a technology for filtering inaccurate locations of mobile terminals. 
2.  Description of the Related Art
Positioning techniques using a wireless communication infrastructure vary depending on the types of infrastructure and service coverage.  A global navigation satellite system (GNSS) is a system that determines a user's location by using signals from satellites orbiting the Earth, and examples thereof include a global positioning system (GPS) of the U.S., a global navigation satellite system (GLONASS) of Russia, a Galileo of Europe, and the like, which are currently in operation, or are scheduled to be operated.  The GNSS, which is disposed to cover the entire globe, includes: a satellite that transmits signals that include precise visual information and satellite orbit information; a receiver that receives four or more satellite signals to calculate location and velocity; and a ground controller that monitors and controls satellite status and orbit. 
In a case of level ground or a suburban area where a direct line of sight of a satellite and a receiver is secured, the GNSS provides high accuracy and availability within 10 meters, whereas in a case of a congested unban area that is a non-line of sight area, the error of location information is substantially 50 meters due to multipath errors, and sensitivity of a reception signal is degraded in an indoor environment, such that it fails to acquire a signal, and it is not possible to determine location and velocity. 
A cellular-based positioning technique determines a user's location by using location information of a mobile communication base station and a measured signal, and may be classified into cell-ID, enhanced-observed time difference (E-OTD), advanced-forward link trilateration (AFLT), and the like, depending on the number of base stations available for a terminal.  As characteristics of the mobile telecommunication infrastructure allow its services to be provided to most parts of urban and suburban areas, the cellular-based positioning technique may determine location even in an indoor environment, as well as in an outdoor environment, but its positioning accuracy varies depending on the disposition density of base stations, and it has a relatively low positioning accuracy of about 100 m to 800 m on average.  For this reason, it is inappropriate to be used for indoor and outdoor navigation services or the like, which requires positioning accuracy of several meters or so. 
Assisted GNSS technologies enhance minimum sensitivity of a reception signal of the GNSS receiver mounted in a user terminal, and acquire supplementary information from a positioning server to reduce time-to-first-fix (TTFF), thereby enabling fast determination of location in a congested urban area where a signal is weak.  However, assisted GNSS technologies are not appropriate for an indoor environment, since a signal is significantly weak. 
WiFi-based positioning techniques are provided to overcome the above difficulty of indoor positioning, and typical examples thereof include a method of calculating a terminal location by using WiFi access points (AP) and a measured signal, and a fingerprinting method using a radio map of WiFi access points (AP).  In the WiFi AP-based positioning method, WiFi access points are estimated by using collected locations of vehicles or pedestrians and reception signal strength of WiFi access points, and then a terminal location is calculated by using positioning algorithms, such as Trilateration, weighted centroid localization (WCL), Monte-Carlo, or the like.  In the fingerprint method, collected locations of vehicles and pedestrians and reception signal strength (RSS) of WiFi Aps are processed to generate a radio map of a reference location, and patterns of reception signal strength of WiFi APs measured in a terminal are compared to the generated radio map to estimate that a reference location having a minimal RSS error is a terminal location. 
In view of the above analysis, the WiFi-based positioning techniques may provide relatively precise information on a terminal location in an indoor environment, compared to the conventional GNSS technique or a cellular-based positioning technique.  However, the conventional WiFi-based positioning technique has difficulty providing heading information, which is useful information in addition to location information, such that it may be difficult to filter abnormal information.  Further, in a case of a pedestrian who is moving while holding a terminal, a formulated equation of motion may not be applied in the WiFi-based positioning technique since a pedestrian moves more freely compared to a user aboard an airplane or in a car. 
A sensor-based positioning technique has technical characteristics that may make up for the drawbacks of the Wi-Fi-based positioning technique for indoor use.  Basically, the sensor-based positioning technique calculates a terminal location by combining one or more of an accelerometer, a gyroscope, a magnetometer, a barometer, an inclinometer, a proximity sensor, and the like, which are mounted inside or outside a terminal.  Such sensor-based positioning technique has the following effects.  First, it is rarely affected by an external environment of a terminal, unlike the GNSS or the WiFi-based positioning techniques.  That is, a terminal location is calculated by using internal physical characteristics of a sensor (acceleration, velocity, rotational speed, etc.)  as information for direct measurement, such that it is not likely that measurement information may be distorted by a complex indoor environment.  Secondly, a terminal location may be determined in every case even without a nearby positioning infrastructure.  That is, in the WiFi-based positioning technique, a terminal location may be determined only if there are nearby WiFi APs, such that if there are no WiFi APs, a terminal location may not be determined, whereas in the sensor-based positioning technique, a terminal location may be calculated all the time by using sensor information as long as a sensor is connected to a terminal, such that terminal location information may be readily available.  Thirdly, a sensor price is becoming reasonable with the development of a micro electro-mechanical systems (MEMS) technology and the widespread distribution of smartphones, such that a technology of mounting a sensor in a smartphone is being widely used, and the use of a sensor in combination with the conventional GNSS technique is being facilitated. 
However, the sensor-based positioning technique also has drawbacks to be overcome.  First, a sensor that employs the MEMS technology does not have a high quality, thereby requiring calibration before use to remove a sensor error component caused by bias, drift, or the like.  However, if the calibration is not performed well, an error of a terminal location measured by using measurement information will increase significantly with the lapse of time.  Further, values of sensor errors caused by bias or drift are different depending on a terminal environment, such as a temperature or the like, so a sensor may need to be calibrated for every terminal used.  Secondly, the sensor-based positioning technique relates to relative positioning, rather than absolute positioning, such that an absolute location of a starting point is required to know an absolute location of a terminal.  In order to overcome such drawbacks, the sensor-based positioning technique is required to be used in combination with the GNSS technique that may provide an absolute location, or with the WiFi-based positioning technique that is mapped with an absolute location.  Thirdly, in order to provide a precise terminal location for an extended period of time, the sensor-based positioning technique needs to remove accumulated location errors by correction not only before determination of location, but also in the course of determination.  For terminal correction, location information of the GNSS that may provide an absolute location is also used, and points of interest (POI) in a map may also be used for the correction.