US 12,353,643 B2
Low profile pointing device sensor fusion
Julien Colafrancesco, Paris (FR); and Nicolas Schodet, Paris (FR)
Assigned to Qorvo US, Inc., Greensboro, NC (US)
Appl. No. 17/794,924
Filed by 7Hugs Labs SAS, Montrouge (FR)
PCT Filed Jan. 28, 2021, PCT No. PCT/IB2021/050688
§ 371(c)(1), (2) Date Jul. 22, 2022,
PCT Pub. No. WO2021/152513, PCT Pub. Date Aug. 5, 2021.
Claims priority of provisional application 62/968,543, filed on Jan. 31, 2020.
Prior Publication US 2023/0195242 A1, Jun. 22, 2023
Int. Cl. G06F 3/038 (2013.01); G06F 3/0346 (2013.01); H04N 21/422 (2011.01)
CPC G06F 3/0346 (2013.01) [G06F 3/0383 (2013.01); H04N 21/4222 (2013.01)] 22 Claims
OG exemplary drawing
 
1. A device providing a calibrated pointing direction comprising:
a set of antennas including a first antenna and a second antenna, wherein the first antenna and the second antenna are aligned with the pointing direction in a line and wherein the line connects a center of the first antenna to a center of the second antenna and is parallel with a pointing direction;
at least one of an inertial measurement unit, a gravity sensor, and a magnetometer; and
one or more computer readable media storing instructions which, when executed on the device, cause the device to:
receive a signal at the first antenna and the second antenna;
determine a difference between: (i) the signal as received by the first antenna; and (ii) the signal as received by the second antenna;
determine, using the difference, an angle between: (i) the pointing direction; and (ii) a signal source direction of the signal wherein the angle is a first estimation of the pointing direction based on the angle;
measure a physical quantity using the at least one of the inertial measurement unit, the gravity sensor, and the magnetometer, wherein the physical quantity is a second estimation of the pointing direction based on the physical quantity; and
determine the calibrated pointing direction of the device by fusing the first estimation and the second estimation using sensor fusion that is performed by using a Kalman filter pipeline, wherein the fusing of the first estimation and the second estimation using the sensor fusion that is performed by using the Kalman filter pipeline further comprises:
implementing a prediction performance model to quantify an error in the angle of the first estimation; and
reduce the error in the angle of the first estimation by performing a functional error analysis using the second estimation.