Methods and devices useful in performing precise indoor localization and tracking are provided. By way of example, a method includes locating and tracking, via a first wireless electronic device, a plurality of other wireless electronic devices within an indoor environment. The method also includes performing front-back detection, performing stationary node detection, performing angle of arrival (AoA) error correction, and performing field of view (FOV) filtering. Performing indoor localization and tracking of the plurality of other wireless electronic devices includes providing an indication of a physical location of the plurality of other wireless electronic devices within the indoor environment.

A method for determining a location of a vehicle includes a global navigation satellite system (GNSS) location system in a manufacturing environment. The method includes determining, when a key cycle transition condition of the vehicle and a vehicle gear transition condition of the vehicle are satisfied, a location parameter of the vehicle using an auxiliary location detection system, where the location parameter includes a location of the vehicle, identification information of the vehicle, and a timestamp of the vehicle. The method includes determining a vehicle time period based on the location parameter and a previous location parameter of the vehicle and validating a manufacturing routine of the vehicle when the location parameter satisfies a location condition and the vehicle time period satisfies a time condition.

In a general aspect, a set of observed frequency-domain channel responses is filtered to remove noise or distortions that are not related to changes in the physical environment. In some aspects, for each frequency-domain channel response, a time-domain channel response is generated based on the frequency-domain channel response; and a filtered time-domain channel response is generated based on a constraint applied to the time-domain channel response. Additionally, a reconstructed frequency-domain channel response is generated based on the filtered time-domain channel response. An error signal is also generated, and a determination is made as to whether the error signal satisfies a criterion. The error signal can be indicative of a difference between the frequency-domain channel response and the reconstructed frequency-domain channel response. In response to each of the error signals satisfying the criterion, motion of an object in a space is detected based on the set of frequency-domain channel responses.

Methods and apparatus for processing and using signals transmitted by a device, e.g., a low cost beacon transmitter device, to facilitate making location determinations with regard to the transmitting device and/or making a decision of when or how to use location information generated based on received signals are described. In accordance with some features the processing performed on the received signal strength measurements is based on whether or not the device from which the signals are received is in motion. The size of a sample period used as a processing window when determining device location is based, in some embodiments, on the rate of motion. When and/or how to use location determinations are performed is also based on motion in some embodiments. Machine learning updates of location determination parameters, based on received signals, are disabled when the signals are from devices determined to be in motion.

Calibrating an unstable sensor of a mobile device. Systems and methods for calibrating a sensor of a mobile device determine a first estimated position of the mobile device without using any measurement from the sensor of the mobile device, generate a second estimated position of the mobile device using a measurement from the sensor, estimate a sensor error of the sensor using the first estimated position and the second estimated position, and use the sensor error to determine a calibration value for adjusting one or more measurements from the sensor.

A method includes obtaining signal information based on wireless signals communicated between an electronic device and a target device. The method also includes obtaining motion information based on movement of the electronic device. The method further includes identifying first location information based on the signal information, the first location information indicating whether the target device is within a field of view (FoV) of the electronic device. Additionally, the method includes identifying second location information based on the motion information and the signal information, the second location information indicating whether the target device is within the FoV of the electronic device. The method also includes determining that the target device is within the FoV or outside the FoV of the electronic device based on at least one of the first location information or the second location information.

A method for inferring a status asset information from data of a first type gathered by a first asset tracking device is provided. The method includes determining that a first asset tracking device coupled to a first asset and a second asset tracking device coupled to a second asset are travelling together, that the first asset tracking device has a first operating mode, and that the second asset tracking device has a second operating mode, which is different from the first operating mode of the first asset tracking device. In response, the second asset tracking device enters into a low-power mode in which it either does not gather data of the first type or does so at a reduced rate. Status information related to the second asset may be inferred from data of the first type gathered by the first asset tracking device.

Method, apparatus and systems for object tracking are disclosed. In one example, a system for tracking a plurality of objects in a venue is disclosed. The system comprises a transmitter configured for transmitting a series of probe signals in a broadcasting manner through a wireless multipath channel, wherein the wireless multipath channel is impacted by a movement of at least one of the plurality of objects in the venue; and a plurality of heterogeneous target wireless receivers each of which is associated with an object of the plurality of objects in the venue. Each of the plurality of heterogeneous target wireless receivers is configured for: receiving the series of probe signals through the wireless multipath channel between the heterogeneous target wireless receiver and the transmitter, obtaining at least one time series of channel information (TSCI) of the wireless multipath channel based on the series of probe signals received by the heterogeneous target wireless receiver, and tracking the object associated with the heterogeneous target wireless receiver based on the at least one TSCI.

The disclosed embodiments are directed to detecting a user activity based on patterns in location data. In an embodiment, a method comprises: obtaining, by a processor of a computing device, location data; detecting, by the processor, a pattern in the location data; determining, by the processor and based on the detected pattern, an activity associated with a mobile device; and adjusting, by the processor, one or more parameters of a location data filter configured to process the location data.

Disclosed is method of computing a round trip delay between a pair of nodes, the method comprising transmitting at least one beacon at a known transmit time from each of the nodes; measuring the times-of-arrival of the beacons at other of the nodes; and estimating a round trip delay between the nodes from the measured times-of-arrival and the transmit times; and correcting the round trip delay for either or both of a frequency offset between the nodes and relative motion between the nodes.