A method for locating a communication device borne by a user in proximity to a vehicle in order to trigger at least one function of said vehicle, the method especially including, in a locating phase, steps of detection of a set of obstacles, called “current” obstacles, of identification of the communication device in the set of current obstacles and of location of the identified communication device among the obstacles of the set of obstacles.

A device obtains at least one characteristic of at least one radio signal detected at a mobile device that is located at a particular site and a representation of a radio environment for the site and a definition of at least one specified path section for the site. The at least one path section has been specified by a person in a map presented on a display. The device determines a location estimate for the mobile device based on the at least one characteristic of the at least one radio signal and based on the representation of the radio environment for the site and adjusts the determined location estimate based on the definition of at least one specified path section.

A wireless communication device including a processor; a memory, coupled to the processor, to store instructions, which when executed by the processor, cause the processor to: connect an antenna to an energy harvesting (EH) circuit, wherein the antenna is configured to capture a Wi-Fi radio frequency (RF) signal; send the Wi-Fi RF signal to the EH circuit; determine a RF signal strength of the Wi-Fi RF signal; and determine a location of the wireless communication device based on the RF signal strength.

A system and method for measuring a location are provided. The system for measuring a location comprises a receiving device comprising a directional antennam the receiving device being configured to receive a signal from a mobile device in a path at a signal sensing direction side of the directional antenna, and a server configured to receive from the receiving device, information on the signal, determine a location of the mobile device based on the information on the signal, and determine a degree of congestion of the path using the location.

Embodiments disclose a method and an apparatus for locating a wireless access point. M APs are deployed in a physical area, the M APs include N first reference APs and L to-be-located APs, and physical locations of the first reference APs and a first distance between any two first reference APs are determinate. The method includes obtaining a first electromagnetic wave signal received by a first to-be-located AP of the L to-be-located Aps, where the first electromagnetic wave signal includes an electromagnetic wave signal sent by each first reference AP. The method also includes determining a second distance between the first to-be-located AP and each first reference AP according to the first electromagnetic wave signal, and determining a physical location of the first to-be-located AP according to the first distance, the second distance, and the physical locations of all the N first reference APs.

One or more processors obtain (a) first radio data and a first horizontal position corresponding to a mobile apparatus at a first time and (b) second radio data and a second horizontal position corresponding to the mobile apparatus at a second time. Responsive to determining that the first horizontal position and the second horizontal position are substantially similar, the one or more processors identify differences between the first radio data and the second radio data. Based at least in part on the differences between the first radio data and the second radio data and one or more threshold criteria, the one or more processors determine whether the mobile apparatus changed floors between the first time and the second time.

Methods, systems, computer-readable media, and apparatuses for autonomous lane detection are presented. One example method includes the steps of receiving a signal from a first device; responsive to a comparison of a measured received frequency of the signal to a source frequency of the signal and to one or more thresholds, determining a distance to the first device; and determining a lane in which the vehicle is operating based on the distance and a lane map. Another example method further includes the steps of determining a location and a heading of the first vehicle; and outputting, to a crowdsourcing server, the location, the heading, and the distance to the first device.

A method being for facilitating positioning determination of a UE includes: obtaining motion information indicative of motion of the UE; obtaining positioning information based on positioning signals received by the UE; determining a validity status of map data based on whether the positioning information, the motion of the UE, and the map data, that include locations of physical environmental features, are consistent, wherein the validity status is determined to be valid in response to the positioning information, the motion of the UE, and the map data being consistent; and determining at least one of a position estimate for the UE, or a direction of motion of the UE, based on the map data and based on the validity status being valid.

A method for determining geo-position of a target by an aircraft includes: receiving navigation data related to the aircraft including aircraft attitude information; receiving multilateration information related to the target including an angle to the target; calculating an axis for a cone fixed to the aircraft, based on the received aircraft attitude information; calculating a central angle for the cone from the received angle to the target; generating two vectors orthogonal to the cone axis; calculating a cone model from the axis, the central angle and the two vectors; and intersecting the cone model with an earth model to obtain a LEP curve, wherein the LEP curve is used to determine the geo position of the target.

A method of localizing a mobile body (MB) in a known environment, includes the following steps: a) defining an occupancy grid (G) modeling the environment; b) defining a set of position grids (Π) each position grid being associated to a heading of the mobile body; c) receiving a time series of measurements (z.sub.1, z.sub.2, . . . ) from a distance sensor carried by the mobile body; and d) upon receiving a measurement of the time series, updating the pose probabilities of the position grids as a function of present values of the occupancy probabilities and of the received measurement; wherein step d) is carried out by applying an inverse sensor model to the received measurement, while considering the distance sensor co-located with a detected obstacle and by applying Bayesian fusion to update the pose probabilities of the position grids.