Methods and systems for identifying device positions include measuring radio signal strength information between devices. Inertial information is measured for the devices. The radio signal strength information and the inertial information are fused to determine relative locations between the devices. The relative locations are oriented to a fixed anchor node. Elevation is estimated for the plurality of devices using pressure sensor information.

A method for supporting a user of a first vehicle to follow a second vehicle includes obtaining a picture, by a camera, of at least a part of a surrounding of the first vehicle, detecting vehicles in the obtained picture, displaying a representation of the detected vehicles on a user interface to the user, obtaining input from the user from the user interface of which of the detected vehicles that is the second vehicle and that the user would like to follow, obtaining, via the camera, at least one identification data of the second vehicle, tracking the position of the second vehicle, and transmitting the position of the second vehicle to a navigation system of the first vehicle.

A system and method to verify that the driver or operator of a vehicle or piece of equipment has completed a 360-degree walk-around inspection of the vehicle/equipment. The vehicle/equipment will be equipped with an electronic beacon that detects the direction of the driver/operator via a mobile electronic device that the driver/operator carries. As the operator walks around the vehicle/equipment, the electronic beacon installed on the vehicle/equipment recognizes the location of the mobile electronic device as the driver/operator walks around the vehicle/equipment performing their inspection. In certain embodiments, the electronic beacon and mobile electronic device determine the operator's inspection are Angle of Arrival and Angle of Departure relative to each electronic beacon. The determination may require different combinations of transmitters and receivers. In another embodiment, multiple antennas, mounted on the vehicle/equipment and/or mobile electronic device, provide the location details of the driver/operator in correlation to the vehicle/equipment.

A correlation and track system identifies whether a Radar warning (RW) Track contains one or more emitters by receiving a set of initial Short and Long Baseline Interferometer (SBI) (LBI) detections; receiving inertial navigational data; receiving subsequent LBI detections; determining whether the LBI detections represent one or multiple emitter(s) by designating an initial SBI conic with a multiple of its one sigma conic Direction Finding (DF) accuracy window as containing the emitter; laying down a set of grid points within the SBI conic window as possible emitters' locations; summing real and imaginary values of a residual phase in the form of a unit vector at each grid point for each LBI update; identifying whether there are one or more emitters in RW track based on whether the magnitude of a peak vector is above or below a defined threshold; and invoking geolocation algorithms based on the vector's magnitude.

Methods and systems disclosed herein may include receiving signals from a transmitter in a receiver; determine a bias of the transmitter and receiver; generating expected observations, based on the bias, corresponding to the received signals; and calculate a building height based on a power level of the received signals and a power level of the expected observations.

A machine includes a rotational sensor configured to sense rotation of an upper frame of the machine relative to a lower frame of the machine. The machine also includes a three-dimensional position sensor spaced from an axis of rotation of the upper frame relative to the lower frame. The machine can also include a number of additional sensors including sensors to detect track movement, imaging sensors, ranging sensors, IMUs, linear displacement sensors and/or the like. A computing system receives the various inputs from the sensors and fuses the data to determine state information for the machine.

The present invention relates to a blind area tracking method and apparatus for a directional antenna and a motion tracking system. The method includes: acquiring a position and a velocity of a tracking target relative to the directional antenna; determining, according to the position and the velocity, whether the tracking target is located in a tracking blind area of the directional antenna; and driving, in a preset blind area guidance mode and when the tracking target is located in the tracking blind area, the directional antenna to rotate. The method may help switch to a corresponding blind area guidance mode when an unmanned aerial vehicle enters a tracking blind area, to implement all-the-way tracking of a tracking target without temporarily losing the tracking target within the tracking blind area. In this way, a better tracking effect is ensured.

A mobile computing device includes: a tracking sensor; a proximity sensor; and a controller coupled to the tracking sensor and the proximity sensor, the controller configured to: obtain a sequence of sensor datasets, each sensor dataset including: (i) a location of the mobile computing device, in a local coordinate system, generated using the tracking sensor, (ii) a proximity indicator generated using the proximity sensor, defining a range to a fixed reference device, and (iii) a predefined location of the reference device in a facility coordinate system; determine, from the sequence, an adjusted pose of an origin of the local coordinate system in the facility coordinate system; and generate, using a current location of the mobile device in the local coordinate system and the adjusted pose, a corrected location of the mobile computing device in the facility coordinate system; and execute a control action based on the corrected location.

A switching determination device includes: an input unit configured to receive an input of time-series data obtained by continuously receiving radio signals; a continuity counting unit configured to compare a value of the input time-series data at a first time count with a value of the input time-series data at a second time count just before the first time count, and increment a continuity counter value in a case in which the value of the input time-series data at the first time count and the value of the input time-series data at the second time count conform to each other, or reset the continuity counter value in a case in which the value of the input time-series data at the first time count and the value of the input time-series data at the second time count do not conform to each other; and a retention value output unit configured to set a value of the input time-series data at a time count at which the continuity counter value becomes equal to or greater than a threshold value as a retention value and output the retention value until the next time the continuity counter value becomes equal to or greater the threshold value.

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.