Disclosed is an approach to enable radio map download for Global Navigation Satellite System (GNSS)-denied areas. In particular, processor(s) (e.g., of positioning server(s)) could identify GNSS-denied area(s) in an initial radio map, the GNSS-denied area(s) being (i) one or more areas in which at least one GNSS signal is or was unavailable and (ii) a subset of a plurality of areas represented by the initial radio map. Subsequently, the processor(s) could generate a partial radio map representing radio data only for the GNSS-denied area(s) identified in the initial radio map, and could then transmit the partial radio map to a mobile device for storage at the mobile device. In this way, the mobile device could optimize resource usage and perform radio-based position estimations at least in the GNSS-denied area(s) that were identified.

An indoor target positioning method based on an improved convolutional neural network (CNN) model includes acquiring and preprocessing target camera serial interface (CSI) data of a to-be-positioned target and matching the preprocessed target CSI data with fingerprints in a positioning fingerprint database to obtain coordinate information of the to-be-positioned target. The generation method of the positioning fingerprint database includes: collecting indoor WiFi signals by a software defined radio (SDR) platform to obtain indoor CSI data corresponding to the WiFi signals, and preprocessing the indoor CSI data; partitioning the preprocessed indoor CSI data into a plurality of data subsets through a clustering algorithm; training an improved CNN model by the data subsets to obtain a trained improved CNN model; and generating the positioning fingerprint database by the trained improved CNN model and the preprocessed indoor CSI data.

An example method of determining geolocations of objects based on information retrieved from heterogeneous data sources comprises: receiving, from a first data source associated with an object by an ontology-defined relationship, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the object; receiving, from a second data source associated with an object by an ontology-defined relationship, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the object and a corresponding time identifier.

Various embodiments disclosed herein enable a mobile device to accurately locate where the mobile device is located indoors by measuring geomagnetic fields, and tracing relative changes in the magnetic fields as the mobile device is moved. The relative changes can be compared to a fingerprint signal map, and a trace of a portion of the path can be determined by matching the relative changes in the magnetic fields to relative changes in the fingerprint signal map. A collection of the path portions can then be connected by determining a shortest path that connects each of the path portions. In another embodiment, a step counter can also be used to constrain possible locations, and fuse the geomagnetic field and step counter information for joint indoor localization.

A method for generating a wireless signal fingerprint database includes: obtaining an initial atmospheric pressure value, in which the initial atmospheric pressure value is an atmospheric pressure value collected when a terminal enters indoors; obtaining periodically a current wireless signal fingerprint and a current atmospheric pressure value collected by the terminal; and determining a floor corresponding to the current wireless signal fingerprint based on the initial atmospheric pressure value and the current atmospheric pressure value, to obtain the wireless signal fingerprint database.

Techniques are disclosed for predictive media streaming using microlocation. Microlocations of a mobile device can be determined by measuring one or more sensor values at one or more times, the one or more sensor values are determined from one or more signals emitted by a corresponding one or more signal sources. Streaming events can be stored at the mobile device. Each streaming event may include a destination device for playing media and a cluster location, the cluster location corresponding to sensor values that are spatially near each other. A selection of a media item is detected and one or more current sensor values are measured. A current cluster location can be identified using the one or more current sensor value. The current cluster location and the streaming events can identify a particular destination device for playing the selected media item.

A system and method for detection of an aerial drone in an environment includes a baseline of geo-mapped sensor data in a temporal and location indexed database formed by (i) using at least one sensor to receive signals from the environment and converting into digital signals for further processing; (ii) deriving time delays, object signatures, Doppler shifts, reflectivity, and/or optical characteristics from the received signals; (iii) geo-mapping the environment using GNSS and the sensor data; and (iv) logging sensor data over a time interval, for example 24 hours to 7 days. Live sensor data can be then be monitored and signature data can be derived by computing at least one parameter such as direction and signal strength. The live data is continuously or periodically compared to the baseline data to identify a variance, if any, which may be indicative of a detection event.

A method is provided that includes obtaining one or more pieces of crowd-sourced information. A respective crowd-sourced information is at least indicative of a location at which the respective crowd-sourced information was gathered. The method determines a set of tiles at least partially based on the one or more geographical areas. For at least one tile, the method obtains one or more pieces of fingerprint information comprised by the one or more pieces of crowd-sourced information that were gathered within the respective area of the respective tile and determines an area type and/or context information indicative of a type of venue located within the respective tile and/or context the respective area of the respective tile is used for. The area type and/or context information is determined at least partially based on the one or more pieces of fingerprint information. A corresponding apparatus and computer program product are also provided.

Systems and methods of radio frequency data mapping are provided. An exemplary method includes moving a mobile mapping system through the environment, the mobile mapping system comprising a location detection element and a radio frequency (RF) instrument which receives data from an antenna of the mobile mapping system; collecting data from the RF instrument at one or more collection locations within the environment, the collected data including received signal strength indicator (RSSI) data; mapping the collected data at least in part based on data received from the location detection element and the RF instrument to form an RF fingerprint of the environment; and using the mapped data to confirm an anticipated environmental RF fingerprint associated with the environment, adjust one or more RF components associated with the environment, or both.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first device may receive, from a second device, perception information for an environment of the first device based at least in part on a perception capability of the second device. The first device may generate a perception associated with a communication by the first device based at least in part on the perception information from the second device, where the perception indicates characteristics of the environment. The first device may adjust a parameter associated with the communication based at least in part on the perception. Numerous other aspects are described.