摘要:
In some implementations, a location of a mobile device can be determined by calculating an average of the locations of wireless signal transmitters that have transmitted signals received by the mobile device. In some implementations, locations are weighted with coefficients and the average is a weighted average. In some implementations, the locations of the wireless signal transmitters are determined based on identification information encoded in the wireless signals received by the mobile device. The identification information can include an identifier for a wireless signal transmitter. The identification information can include characteristics of the received wireless signal that can be used to identify wireless signal transmitters. In some implementations, identification information from one signal can be combined with identification information from another signal to determine a location of a wireless transmitter.
摘要:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective altitude of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective altitude of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective altitude of the wireless access gateway. The server can send the effective altitude of the wireless access gateway to other mobile devices for estimating altitudes of the other mobile devices.
摘要:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective altitude of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective altitude of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective altitude of the wireless access gateway. The server can send the effective altitude of the wireless access gateway to other mobile devices for estimating altitudes of the other mobile devices.
摘要:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective location of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective location of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective location of the wireless access gateway. The server can send the effective location of the wireless access gateway to other mobile devices for estimating locations of the other mobile devices.
摘要:
In some implementations, a location of a mobile device can be determined by calculating an average of the locations of wireless signal transmitters that have transmitted signals received by the mobile device. In some implementations, locations are weighted with coefficients and the average is a weighted average. In some implementations, the locations of the wireless signal transmitters are determined based on identification information encoded in the wireless signals received by the mobile device. The identification information can include an identifier for a wireless signal transmitter. The identification information can include characteristics of the received wireless signal that can be used to identify wireless signal transmitters. In some implementations, identification information from one signal can be combined with identification information from another signal to determine a location of a wireless transmitter.
摘要:
Methods, program products, and systems of location estimation using multiple wireless access gateways are disclosed. In general, in one aspect, a mobile device can scan and detect multiple wireless access gateways. The mobile device can determine an initial estimate of distance between the mobile device and each wireless access gateway. The mobile device can receive, from a server, location data of the detected wireless access gateways. The location data can include an estimated location of each wireless access gateway, an uncertainty of the estimated location, and a reach of each wireless access gateway. The mobile device can assign a weight to each estimated location using the uncertainty, the reach, and the initial estimate. The mobile device can estimate the location of the mobile device using the weighted locations.
摘要:
Methods, program products, and systems of location estimation using a probability density function are disclosed. In general, in one aspect, a server can estimate an effective location of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. The server can calculate an effective location of the wireless access gateway using a probability density function of the harvested data. The probability density function can be a sufficient statistic of the received set of location coordinates for calculating an effective location of the wireless access gateway. The server can send the effective location of the wireless access gateway to other mobile devices for estimating locations of the other mobile devices.
摘要:
Methods, program products, and systems of location estimation using multiple wireless access gateways are disclosed. In general, in one aspect, a mobile device can scan and detect multiple wireless access gateways. The mobile device can determine an initial estimate of distance between the mobile device and each wireless access gateway. The mobile device can receive, from a server, location data of the detected wireless access gateways. The location data can include an estimated location of each wireless access gateway, an uncertainty of the estimated location, and a reach of each wireless access gateway. The mobile device can assign a weight to each estimated location using the uncertainty, the reach, and the initial estimate. The mobile device can estimate the location of the mobile device using the weighted locations.
摘要:
Techniques for estimating the current state (e.g., position, velocity) of a mobile device based on motion context and multiple input observation types are disclosed. In some implementations, an Extended Kalman Filter (EKF) formulation is used to combine multiple input observations received from a variety of sources (e.g., WiFi, cell, GPS) to compute a minimum error state estimate. In some implementations, the EKF is updated using position estimates from an active cell and/or a candidate active cell during a cell-hopping event.
摘要:
Techniques for estimating the current state (e.g., position, velocity) of a mobile device based on motion context and multiple input observation types are disclosed. In some implementations, an Extended Kalman Filter (EKF) formulation is used to combine multiple input observations received from a variety of sources (e.g., WiFi, cell, GPS) to compute a minimum error state estimate. In some implementations, the EKF is updated using position estimates from an active cell and/or a candidate active cell during a cell-hopping event.