During a positioning session in which multiple location reports are provided, a user equipment (UE) that has little or no movement may provide an indication to an entity in the wireless network that there is no update for one or more location measurements. The UE may provide the indication to a serving base station in a Physical layer waveform. The base station may bypass the location server and provide an indication to an external client that the UE position has not changed. The UE may provide the indication to a location server in a location information report or by not sending a location information report by an expiration time. The indication of no update may be provided by a bit that indicates no location measurements are updated or that a particular location measurement is not updated.

According to certain embodiments, a method for use in a network node comprises: obtaining range information for a wireless device in communication with the network node; obtaining direction information for the wireless device; and estimating a movement of the wireless device based on the range information, the direction information, and an interactive multiple modeling (IMM) filter. The IMM filter comprises a three-dimensional (3D) constant velocity model, a 3D constant acceleration model, and a 3D constant position model.

A method to identify a problematic 2D position of a mobile device can include: determining a reported 2D position of the mobile device; determining a piece of information about the mobile device; and comparing the reported 2D position and the piece of information about the mobile device. Upon determining that the reported 2D position and the piece of information about the mobile device are consistent with each other, the reported 2D position of the mobile device is used as an estimate of the actual 2D position of the mobile device, or upon determining that the reported 2D position and the piece of information about the mobile device are not consistent with each other, the reported 2D position is determined to be problematic, and the reported 2D position of the mobile device is removed from a list of reported 2D positions of the mobile device.

A hybrid indoor positioning system comprises an electronic label provided with an acceleration sensing module, a first direction sensing module, a second direction sensing module and an operational module, the acceleration sensing module generates an acceleration signal, the operational module receives the acceleration signal and generates a movement data, the first direction sensing module and the second direction sensing module respectively generate a first direction signal, a magnetic force information and a second direction signal, the operational module receives the first direction signal and the second direction signal and generates a direction data, the electronic label is provided with a signal receiving module that generates an ambient wireless signal, the movement data and the direction data of the operational module are transmitted to a signal sending module; and a remote server, the remote server has a central processing unit, a signal receiving unit and a judgment model.

A method and system for combining data obtained by sensors, having particular application in the field of navigation systems, are disclosed. The techniques provide significant improvement over state-of-the-art Markovian methods that use statistical noise filters such as Kalman filters to filter data by comparing instantaneous data with the corresponding instantaneous estimates from a model. In contrast, the techniques disclosed herein use multiple time periods of various lengths to process multiple sensor data streams, in order to combine sensor measurements with motion models at a given time epoch with greater confidence and accuracy than is possible with traditional “single epoch” methods. The techniques provide particular benefit when the first and/or second sensors are low-cost sensors (for example as seen in smart phones) which are typically of low quality and have large inherent biases.

Location polygons are defined along traffic lanes and parking spaces to facilitate determination of the location of a vehicle relative to features associated with the location polygons. The location polygons are used, in one application, to identity entrance and exit of a special toll lane along a roadway, and to ensure that the vehicle properly enters and exits the tolling lane.

A system for recognizing the location of a subject, comprises a server, signal transceivers, and a tracking device. The server transmits a request and stores a map file. The signal transceivers respectively communicate with the server to receive the request, and broadcast a reference signal to the other signal transceivers. The tracking device bidirectionally communicates with the signal transceivers, and periodically sends a tracking signal. After each of the signal transceivers obtains the first received signal strength indicator corresponding to the received reference signal and the second received signal strength indicator corresponding to the received tracking signal, each transmits the first signal strength indicator and the second signal strength indicator to the server. The server determines relative position information for the at least one tracking device within the map file according to the first signal strength indicators, the second signal strength indicators, and location information from the signal transceivers.

System and methods include determining a person's physical location based on analyzing Wi-Fi signal data received from a multiple Wi-Fi access point system as part of a distributed Wi-Fi system; and controlling smart devices based on one or more of predetermined settings, machine learned settings, and the person's physical location. The steps can further include determining the person's physical location based on analyzing Wi-Fi client devices that are mobile in the distributed Wi-Fi system.

Embodiments include methods for determining a movement state of a user equipment (UE) operating in a radio access network (RAN). Such methods include performing positioning measurements on signals received from a plurality of transmission points (TPs) in the RAN, including first measurements of Doppler shift of signals from a first TP, second measurements of Doppler shift of signals from a second TP that is spatially separated from the first TP, and third measurements of signals from a third TP. The third TP can be the same as the first or second TP, or spatially separated from both. Such methods include determining a UE movement state based on the positioning measurements and an interacting multiple-model (IMM) that includes a first almost-constant velocity model, a second maneuver velocity model, and a Doppler shift bias state common to the first and second models. Other embodiments include complementary methods for a RAN node.

A system for providing real-time always-on location is presented for maintaining the current location of a mobile device, while saving the battery by managing the GPS in a power-saving mode while the device is considered to be stationary. The system also provides a real-time location in an indoor environment where a GPS signal may not be available. Additionally, methods for driving detection are also presented.