# US 2018/0321328 A1 · Interference Mitigation In Magnetometers > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0321328 A1 - Document ID: US20180321328A1 - Status: Published application - Kind: A1 - Application number: 15/584,576 - Filed: 2017-05-02 - Published: 2018-11-08 - Earliest claimed: 2017-05-02 - Assignees: QUALCOMM Incorporated - Applicants: QUALCOMM Incorporated - Inventors: Aleksandr KUSHLEYEV; Daniel Warren Mellinger, III; Travis Van Schoyck - Web page: https://patentgrep.com/patent/US20180321328A1 ## CPC - G01R 33/0029: {Treating the measured signals, e.g. removing offset or noise} - B64U 20/80: Arrangement of on-board electronics, e.g. avionics systems or wiring - G01C 17/28: Electromagnetic compasses (with north seeking magnetic elements and having electric pick-offs G01C17/26) - G01C 17/38: Testing, calibrating, or compensating of compasses - G01R 33/0017: {Means for compensating offset magnetic fields or the magnetic flux to be measured; Means for generating calibration magnetic fields} - G01R 33/02: Measuring direction or magnitude of magnetic fields or magnetic flux (G01R33/20 takes precedence) - B64U 10/13: Flying platforms - B64U 20/87: Mounting of imaging devices, e.g. mounting of gimbals - B64U 30/20: Rotors; Rotor supports - B64U 50/19: using electrically powered motors - B64U 50/30: Supply or distribution of electrical power - B64U 2201/10: autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS] - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) ## Abstract Various embodiments include devices and methods for mitigating the bias of a magnetometer resulting from operating various hardware components on a device such as a drone or a computing device. Various embodiments may improve the accuracy of magnetometer output by estimating the bias or magnetic interference caused by the hardware components based on a utilization or operating state of each hardware component, and adjusting the magnetometer output to compensate for the estimated bias. ## Claims ### Claim 1 A method of mitigating bias of a magnetometer generated by hardware components, comprising: obtaining, by a processor, operation information from hardware components in proximity to the magnetometer; executing, by a processor, a magnetic interference model using the obtained operation information to produce an estimated magnetometer bias; and adjusting an output of the magnetometer based, at least in part, on the estimated magnetometer bias. ### Claim 2 (depends on 1) The method of claim 1, wherein obtaining operation information from hardware components in proximity to the magnetometer comprises obtaining operation information from hardware components included on the same computing device as the magnetometer. ### Claim 3 (depends on 2) The method of claim 2, wherein the computing device comprises a drone. ### Claim 4 (depends on 1) The method of claim 1, wherein the operation information is at least one of a utilization measurement, an electrical input, an operating frequency, an operating mode, and a temperature for each of the hardware components. ### Claim 5 (depends on 1) The method of claim 1, wherein the magnetic interference model comprises a function of the operation information or a data table correlating magnetic interference to operation information of the hardware components. ### Claim 6 (depends on 1) The method of claim 1, further comprising generating the magnetic interference model by: measuring changes or bias in the output of the magnetometer resulting from operating or energizing the hardware components across operation levels of the hardware components; and correlating the measured changes or bias in the output of the magnetometer and obtained operation information to produce the magnetic interference model. ### Claim 7 (depends on 6) The method of claim 6, wherein the magnetic interference model is generated prior to initial operation of a computing device including the hardware components and the magnetometer. ### Claim 8 (depends on 6) The method of claim 6, wherein the magnetic interference model is generated during initial operation of a computing device including the hardware components and the magnetometer. ### Claim 9 (depends on 6) The method of claim 6, wherein: generating the magnetic interference model further comprises measuring changes or bias in the output of the magnetometer resulting from operating or energizing external payload hardware components and the combined changes or bias in the output of the magnetometer resulting from the external payload hardware components and the hardware components in proximity to the magnetometer across operation levels of the external payload hardware components and the hardware components in proximity to the magnetometer; and correlating the measured changes or bias in the output of the magnetometer and the obtained operation information to produce the magnetic interference model comprises correlating the measured changes or bias in the output of the magnetometer and the operation levels of the external payload hardware components and the hardware components in proximity to the magnetometer to produce the magnetic interference model. ### Claim 10 (depends on 9) The method of claim 9, wherein obtaining, by the processor, operation information from hardware components further comprises obtaining, by the processor, operation information from the external payload hardware components. ### Claim 11 A magnetometer system, comprising: a magnetometer; and a processor coupled to the magnetometer and configured with processor-executable instructions to: obtain operation information from hardware components in proximity to the magnetometer; execute a magnetic interference model using the obtained operation information to produce an estimated magnetometer bias; and adjust an output of the magnetometer based, at least in part, on the estimated magnetometer bias. ### Claim 12 (depends on 11) The magnetometer system of claim 11, wherein the operation information is at least one of a utilization measurement, an electrical input, an operating frequency, an operating mode, and a temperature for each of the hardware components. ### Claim 13 (depends on 11) The magnetometer system of claim 11, wherein the magnetic interference model comprises a function of the operation information or a data table correlating magnetic interference to operation information. ### Claim 14 (depends on 11) The magnetometer system of claim 11, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model by: measuring changes or bias in the output of the magnetometer resulting from operating or energizing the hardware components across operation levels of the hardware components; and correlating the measured changes or bias in the output of the magnetometer and obtained operation information to produce the magnetic interference model. ### Claim 15 (depends on 14) The magnetometer system of claim 14, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model prior to initial operation of a computing device including the hardware components and the magnetometer system. ### Claim 16 (depends on 14) The magnetometer system of claim 14, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model during initial operation of a computing device including the hardware components and the magnetometer system. ### Claim 17 (depends on 14) The magnetometer system of claim 14, wherein the processor is further configured with processor-executable instructions to: generate the magnetic interference model further by measuring changes or bias in the output of the magnetometer resulting from operating or energizing hardware components of an external payload and the hardware components in proximity to the magnetometer across a range of operation levels; and correlate the measured changes or bias in the output of the magnetometer and the obtained operation information to produce the magnetic interference model by correlating the measured changes or bias in the output of the magnetometer and the range of operation levels of the hardware components of an external payload and the hardware components in proximity to the magnetometer to produce the magnetic interference model. ### Claim 18 (depends on 17) The magnetometer system of claim 17, wherein the processor is further configured with processor-executable instructions to obtain operation information from external payload hardware components. ### Claim 19 (depends on 11) The magnetometer system of claim 11, wherein the magnetometer is a component of a drone and the processor is a processor on the drone. ### Claim 20 A drone, comprising: a magnetometer; and a processor coupled to the magnetometer and configured with processor-executable instructions to: obtain operation information from hardware components of the drone in proximity to the magnetometer; execute a magnetic interference model using the obtained operation information to produce an estimated magnetometer bias; and adjust an output of the magnetometer based, at least in part, on the estimated magnetometer bias. ### Claim 21 (depends on 20) The drone of claim 20, wherein the operation information is at least one of a utilization measurement, an electrical input, an operating frequency, an operating mode, and a temperature for each of the hardware components. ### Claim 22 (depends on 20) The drone of claim 20, wherein the magnetic interference model comprises a function of the operation information or a data table correlating magnetic interference to operation information. ### Claim 23 (depends on 20) The drone of claim 20, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model by: measuring changes or bias in the output of the magnetometer resulting from operating or energizing the hardware components of the drone in proximity to the magnetometer across a range of operation levels of the hardware components; and correlating the measured changes or bias in the output of the magnetometer and obtained operation information to produce the magnetic interference model. ### Claim 24 (depends on 22) The drone of claim 22, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model prior to initial operation of the drone. ### Claim 25 (depends on 22) The drone of claim 22, wherein the processor is further configured with processor-executable instructions to generate the magnetic interference model during initial operation of the drone. ### Claim 26 (depends on 20) The drone of claim 20, wherein the processor is further configured with processor-executable instructions to: generate the magnetic interference model further by measuring changes or bias in the output of the magnetometer resulting from operating or energizing hardware components of an external payload of the drone and the hardware components of the drone in proximity to the magnetometer across a range of operation levels; and correlate the measured changes or bias in the output of the magnetometer and the obtained operation information to produce the magnetic interference model by correlating the measured changes or bias in the output of the magnetometer and the range of operation levels of the hardware components of an external payload of the drone and the hardware components of the drone in proximity to the magnetometer to produce the magnetic interference model. ### Claim 27 (depends on 20) The drone of claim 20, wherein the processor is further configured with processor-executable instructions to obtain operation information from hardware components of an external payload of the drone. ### Claim 28 A drone having a magnetometer, comprising: means for obtaining operation information from hardware components in proximity to the magnetometer wherein the operation information is at least one of a utilization measurement, an electrical input, an operating frequency, an operating mode, and a temperature for each of the hardware components; means for executing a magnetic interference model using the obtained operation information to produce an estimated magnetometer bias; and means for adjusting an output of the magnetometer based, at least in part, on the estimated magnetometer bias.