A method for location determination in a wireless communications system solves a minimization problem using estimated time-of-arrivals (TOAs) of reference signals [108, 110, 112] received by a receiving node [100] from transmitting nodes [102, 104, 106] and predetermined locations of the transmitting nodes, to produce an estimate of unknown receiving node location and/or an estimate of an unknown time of transmission (t) of the reference signals. The minimization problem is defined in terms of a theoretical system model of time-of-arrivals (TOAs), linearized globally as a function of the unknown receiving node location, the unknown time of transmission (t) of the reference signals, and an additional intermediate variable (u) that defines a non-linear quadratic constraint over position coordinates of the unknown receiving node location and the time of transmission (t) of the reference signals, wherein the minimization problem optimizes the additional intermediate variable (u). The method may also be implemented with the roles of transmitters and receivers interchanged.

An aircraft includes at least one source collecting a set of navigational parameters of the aircraft, the at least one source obtaining flight data for the aircraft and including at least one of a global positioning system, an inertial reference system, or a sensor. The aircraft further includes a flight control computer communicatively coupled to the source and including a first processor and a first memory having a machine-readable medium, as well as a flight management system communicatively coupled to the flight control computer.

A method for detecting communication jamming attacks includes collecting, via a processor associated with a base station, local jamming information from a first vehicle and a second vehicle. The local jamming information having an attack time, an attack localization, and an attack frequency. The method further includes building a global jamming map comprising global jamming information, based on the local jamming information, determining, based on the global jamming map, a location of a communication jamming device, and causing to transmit global jamming information to a third vehicle. The global jamming information is associated with the location of the communication jamming device.

A geolocationing system and method for providing awareness in a multi-space environment, such as a hospitality environment or educational environment, are presented. In one embodiment of the geolocationing system, a vertical and horizontal array of gateway devices is provided. Each gateway device includes a gateway device identification providing an accurately-known fixed location within the multi-space environment. Each gateway device includes a wireless transceiver that receives a beacon signal from a proximate wireless-enabled personal locator device. The gateway devices, in turn, send gateway signals to a server, which determines estimated location of the wireless-enabled personal location device with angle of arrival modeling.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine a plurality of received signal strength indicators or time of flight values for a mobile device from each of a plurality of sensors included in a vehicle, determine a location of the mobile device with respect to the vehicle by processing the received signal strength indicators or time of flight values with a neural network wherein each received signal strength indicator is input to an input neuron included in an input layer of the neural network wherein each input neuron inputs at least one received signal strength indicator or time of flight value, and operate the vehicle using the located mobile device.

The disclosure relates to a detection method and a detection apparatus, the method including: calculating, when a location base station in an ultra-wideband location system receives a pulse response, values of a plurality of specified pulse response characteristics using the received pulse response, and using the calculated values as values of the plurality of specified pulse response characteristics of the location base station; calculating differences between the values of the plurality of specified pulse response characteristics of the location base station and values of the plurality of specified pulse response characteristics of the location base station at a previous time, and using the calculated differences as variations of the plurality of specified pulse response characteristics of the location base station; determining, based on at least the variations of the plurality of specified pulse response characteristics of the location base station and by means of a trained classifier, whether signal propagation in which the location base station participates is non-line-of-sight propagation.

Methods, apparatus and systems for wireless tracking with graph-based particle filtering are described. A described wireless monitoring system comprises a transmitter transmitting a series of probe signals, a receiver, and a processor. The receiver is configured for: receiving the series of probe signals modulated by the wireless multipath channel and an object moving in a venue, and obtaining a time series of channel information (TSCI) of the wireless multipath channel from the series of probe signals. The processor is configured for: monitoring a motion of the object relative to a map based on the TSCI, determining an incremental distance travelled by the object in an incremental time period based on the TSCI, and computing a next location of the object at a next time in the map based on at least one of: a current location of the object at a current time, the incremental distance, and a direction of the motion during the incremental time period.

Methods and apparatus for sensor selection for localization and tracking are provided. A method (300) performed at an access point (101, 101a, 101b, 101c, 901, 902, 903) comprises: determining, a detectability of the access point (101, 101a, 101b, 101c, 901, 902, 903) for localization for a target device (102), based on channel state information of a radio link between the target device (102) and the access point (101, 101a, 101b, 101c, 901, 902, 903) (302); and determining whether the access point (101, 101a, 101b, 101c, 901, 902, 903) is to be used for position estimation of the target device (102) or not based on the detectability (304). A localization server (103) may further eliminate access points (101, 101a, 101b, 101c, 901, 902, 903) at poor positions from position estimation, by using a predefined weighted-kernel approach.

Systems, methods, computer program products, and apparatuses to determine, by a neural network based on training data related to wireless signals exchanged by a device and a plurality of wireless access points in an environment, a respective distance between the device and each wireless access point, receive location data related to a respective location of each wireless access point of the plurality of wireless access points, determine a geometric cost of the neural network based on a geometric cost function, the respective distances, and the received location data, and train a plurality of values of the neural network based on a backpropagation and the determined geometric cost.

Methods are provided for determining a positioning of a portable device including first and second sensor(s) each having a confidence. These methods include: receiving first and second signals from the first and second sensor(s), respectively; generating positional data representing positional conditions of the portable device and including first and second positional data respectively from the first and second signals, by modelling the received signals based on predefined models defining a correspondence between predefined signals and predefined positional data; comparing the first and second positional data to determine a difference between them; adjusting the confidence of the sensors by determining a new confidence depending on a previous confidence and the determined difference between positional data; weighting the generated positional data depending on corresponding confidences; and determining the positioning of the portable device based on the weighted generated positional data. Computer programs and systems suitable for performing such methods are also provided.