A method for estimating the pressure measurement bias of a barometric sensor in a wireless terminal. A location engine using the method generates an enhanced estimate of the measurement bias. The location engine generates the enhanced estimate based in part on relatively coarse estimates of the elevation of the wireless terminal. Each coarse estimate of elevation is often generated from noisy measurements, such as measurements of signals transmitted by Global Positioning System (GPS) satellites, and has an associated uncertainty. The location engine accounts for the uncertainty in these estimates of elevation by applying an optimal estimation technique, such as Kalman filtering, and by compensating for environment-related effects. Compensating Includes filtering across a plurality of lateral locations and imposing a lower bound of bias uncertainty at the lateral locations. Once the location engine generates the enhanced estimate of measurement bias, it can generate improved estimates of elevation of the wireless terminal.

A processing apparatus including one or more processors and memory determines a first context of a first user at a first location in a physical space based on sensor measurements from one or more sensors of a set of one or more devices coupled to the first user and detects movement of the first user to a second location in the physical space based on sensor measurements from one or more sensors of the devices. The processing apparatus determines a second context of the first user at the second location based on sensor measurements from one or more sensors of the devices and generates, based on the first context, the second context, and the movement of the user from the first location to the second location, a first mapping of the physical space that includes information corresponding to a spatial relationship between the first context and the second context.

[Object] To accurately estimate a user's position on the basis of sensor data by preparing absolute criteria in advance.

[Solution] Provided is an information processing apparatus including: a feature extractor configured to extract a feature of first sensor data provided by a sensor carried or worn by a user; a matching unit configured to match the feature of the first sensor data and a feature of second sensor data corresponding to the first sensor data, the feature of the second sensor data being associated with given position information; and a position estimation unit configured to estimate a position of the user on the basis of a result of the matching.

The relation between realization effort for a positioning system on the one hand and positioning accuracy on the other hand is improved by using, for determining the position of a mobile portable device, two sensors within the device, namely one sensor for detecting the movement of the mobile portable device as well as one sensor for detecting the approximation of the mobile portable device to one or several reference beacons, wherein, from a knowledge of a position of the one or several reference beacons by means of data provided by the sensor detecting the movement, the position of the mobile portable device relative to the one or several reference beacons is calculated.

An approach to localization in an indoor environment makes use of a multiple antenna receiver (e.g., in a smartphone, tablet, camera) and knowledge of locations of one or more radio transmitters, which may be part of a data communication infrastructure providing data communication services to devices in the environment. Successive measurements of transmissions from the transmitters are recorded at the receiver as the device is translated and rotated in the environment. Rotation related measurements are also made at the device. The radio frequency and rotation related measurements are used to infer the location and orientation, together referred to as the pose, of the device. Phase synchronization of the transmitters and the receiver are not required. In general, accuracy of the pose estimate far exceeds that achievable using radio frequency measurements without taking into consideration motion of the device, and far exceeds that achievable using the inertial measurements alone.

The present invention discloses a APNT service positioning and integrity monitoring method and system. The method includes the following steps: determining a positioning accuracy requirement in a target scene; when the positioning accuracy requirement is high-accuracy positioning, determining a position of an aircraft by adopting a combined positioning algorithm, and monitoring the integrity of a combined positioning by adopting a multi-solution separation mode; when the positioning accuracy requirement is low-accuracy positioning, judging whether the aircraft is a high-altitude user; if not, adopting an air-to-air positioning algorithm for a high-altitude user and a low-altitude user based on LDACS to determine the position of the aircraft, and adopting a least square residual method to monitor the integrity of the air-to-air positioning. According to different requirements of users on positioning accuracy and actual application conditions, the present invention can provide a variety of APNT alternative solutions for an aircraft.

Examples describe methods, computing devices, and systems for using location provider (LP) processes to accurately identify a proximate location of a computing device, while reducing the power consumption of the computing device. An example method may include executing, on a computing device, both a first LP process and a second LP process simultaneously for at least part of a time period to determine outputs indicative of locations of the computing device for the time period. Further, the method may include determining a motion model of the computing device that indicates expected locations of the computing device. Yet further, the method may include making a comparison of the outputs to the motion model for the time period. In addition, the method may include disabling one of the LP processes based on the comparison.

The disclosure generally relates to a method, apparatus and system to deploy aquatic sensors to obtain oceanographic data. In an exemplary embodiment, a free-floating or untethered sensor receives signals from different transmitters. The signals may be configured to travel through air and/or water. The sensor records each signals' time of arrival and determines its location in relationship to known transmitters based on the signal travel time. The position of each sensor may be determined by triangulation to several devices whose positions are known. The distances from the sensor in question to each device is measured by means of time-of-flight measurements for a wireless signal from the sensor to each known-position device. Other methods such as trilateration or dead-reckoning may also be used. The sensor may additionally collect and record oceanographic or other environmental data.

Methods and systems detect physical locations of vessels. A first satellite includes a first image sensor. A second satellite includes a second image sensor. The processor receives a first image of a target area from the first image sensor, and a second image of the target area from the second image sensor. Both images are taken within a predetermined time frame. The processor performs image recognition to identify a vessel that appears in both the first image and the second image. The processor receives the first satellite's location and orientation when the first image is taken and the second satellite's location and orientation when the second image is taken. Each satellite's location and orientation are determined by the satellite's geographic determination module. The processor determines the vessel's location by performing triangulation based on the first satellite's location and orientation and the second satellite's location and orientation. The processor outputs data representative of the vessel's determined location. The vessel's speed and bearing are also determined by the processor.

A user equipment (UE) in a vehicle (V-UE) broadcasts multi-phased ranging signals with which other entities may determine the range to the V-UE. The multi-phased ranging signals may include a first message, which may be broadcast in the Intelligent Transport System (ITS) spectrum, includes ranging information, such as a source identifier, location information for the broadcasting V-UE, and an expected time of broadcast of the ranging signal. The ranging signal may then be broadcast at the expected time and may include the source identifier. A second message, which be broadcast in the ITS spectrum, may include clock error information for the V-UE. A receiving entity may determine the range to the V-UE based on the time of arrival of the ranging signal and the expected time of transmission, as well as the clock error information. The receiving entity may further generate a position estimate based on the received location information.