Systems, devices, methods, and computer-readable media for improved location determination of an orbiting device. A method can include receiving, at a transceiver of a device, measurement data from a monitor device, the measurement data representative of a physical state of a mobile object, filtering, using a first of a plurality of first filters of the device, the measurement data based on a character parameter of a state transition matrix representative of the physical state resulting in filtered measurement data, filtering, using a Kalman filter, the filtered measurement data resulting in further filtered measurement data, and providing, by the transceiver, the further filtered measurement data.

Disclosed are techniques for calculating a predicted location of a location tracking device. In an aspect, a wireless communications device detects a breach of a geofence made by the location tracking device, receives data representing a state of the location tracking device, the state of the location tracking device comprising at least a current location of the location tracking device and a velocity of the location tracking device, and determines, based on the data representing the state of the location tracking device, the predicted location of the location tracking device.

A method and system for positioning an indoor autonomous mobile robot is disclosed in this application, which includes: indoor layout of moving paths and indoor relative position information of the moving path are obtained by a vision sensor; visual positioning is performed by a visual locator on indoor image data collected by the visual sensor to obtain the first position information; and second position information of a UWB location tag is obtained and solved by an UWB locator; the first position information and the second position information are fused by an adaptive Kalman filter, to obtain final positioning information of the autonomous mobile robot. After fusion, the UWB locator can correct the accumulated error caused by visual positioning, and at the same time, visual positioning can smooth measured data of the UWB locator to make up for deficiencies.

A method and system for estimation of the current location of a remote radio beacon, at a mobile device, based on two historical positions thereof provided via at least two satellite relays and one base station, particularly usable for Search and Rescue. A beacon is configured to periodically transmit short RF signals, relayed by a first satellite payload to a base station, at which the position of the beacon is resolved; then, the base station transmits a message, relayed by a second satellite payload and detectable by a mobile device, encoding two previous positions of the beacon, stamped with time tags. Finally, the mobile device decodes the information about said two previous positions of the beacon, and accordingly estimates the current position of the beacon, accounting for possible different time references.

A method of monitoring a kinematic state of an unmanned aerial vehicle (UAV) is provided. The method comprises obtaining one or more predicted pathlosses between a UAV and one or more base stations at a first time instance, wherein the predicted pathlosses are determined using an estimate of a kinematic state of the UAV at the first time instance and one or more pathloss models developed using a machine-learning process. The method further comprises obtaining one or more measurements of a pathloss between each of the one or more base stations and the UAV at the first time instance, and re-determining the estimate of the kinematic state of the UAV at the first time instance based on the one or more predicted pathlosses and the one or more measurements of the pathloss.

The invention relates to a locating method for localizing at least one object using wave-based signals, wherein a wave field emanates from the object to be localized and the wave field emanating from the object is received by a number N of receivers, at least one measurement signal is formed in every receiver, said measurement signal being dependent on the spatial and temporal distribution of the wave field and the phase progression of said measurement signal being characteristically influenced by the signal propagation time from the object to the receiver, wherein, for position locating, phase values for each of the at least two measurement signals are taken as measured phase values, and wherein the current position (P(k)) of the object to be located at the time k is determined by a comparison of at least one linear combination of the measured phase values with at least one linear combination of the associated hypothetical phase values, which result from the transmitter-receiver distance(s), and using a recursive filter/estimator.

A power supply device includes a plurality of battery cells each including an outer covering can in a prismatic shape, a pair of end plates that cover both end surfaces of a battery stack in which the plurality of battery cells are stacked, a plurality of bind bars each formed into a plate shape extending in a stacking direction of the plurality of battery cells, the plurality of bind bars being respectively disposed on opposite side surfaces of the battery stack to fasten end plates to each other, heat radiation plate placing the battery stack on its upper surface side for releasing heat from the battery stack, and heat transfer sheet interposed between an upper surface of heat radiation plate and a lower surface of the battery stack to bring heat radiation plate and the battery stack into a thermally coupled state, wherein low friction slide layer with a friction resistance smaller than a friction resistance of the upper surface of heat transfer sheet is provided between heat transfer sheet and the plurality of battery cells.

A method for preprocessing data for device operations can include preprocessing measurement data using a machine learning technique, determining, by a Kalman filter and based on (1) the preprocessed measurement data or the measurement data and (2) prediction data from a prediction model predicting a measurement associated with the measurement data, corrected measurement data, and providing the corrected measurement data based on the predicted measurement and the preprocessed measurement data.

Disclosed herein are systems and methods related to a wireless tracking system: The wireless tracking system having a plurality of beacons, each of the plurality of beacons having at least one antenna and at least one power source. When the at least one antenna is supplied with power via the power source, a local ping is transmitted from the beacon. A wireless tracking device then receives the ping via its own antenna. Once the wireless tracking device has received a locational ping from at least two of the plurality of beacons, it can then calculate a direct connection path between the at least to beacons. Based on this known path, the wireless tracking device can then determine a distance between the wireless tracking device and connection path. Based on the determined distance, the wireless tracking device may then issue a corrective measure.

Tracking devices can be associated with safe zones, smart zones, and high risk zones. Safe zones correspond to regions where a likelihood that a tracking device is lost within the safe zone is lower than outside the safe zone. High risk zones correspond to regions where a likelihood that a tracking device is lost within the high risk zone is higher than outside the high risk zone. Smart zones correspond to an expected tracking device, mobile device, or user behavior. Home areas are geographic regions in which a user resides, and travel areas are geographic regions in which a user does not reside. A tracking device can be configured to operate in a mode selected based on a presence of the tracking device within a safe zone, a smart zone, a high risk zone, a home area, or a travel area.