US 12,000,923 B2
Sensor fusion with alternating correspondence analysis of sensor data
Daniel Spies, Schwaebisch-Gmuend (DE); and Matthias Karl, Königsbronn (DE)
Assigned to Carl Zeiss AG, Oberkochen (DE)
Appl. No. 17/264,476
Filed by Carl Zeiss AG, Oberkochen (DE)
PCT Filed Jul. 31, 2019, PCT No. PCT/EP2019/070633
§ 371(c)(1), (2) Date Jan. 29, 2021,
PCT Pub. No. WO2020/025674, PCT Pub. Date Feb. 6, 2020.
Claims priority of application No. 102018118666.5 (DE), filed on Aug. 1, 2018.
Prior Publication US 2021/0319271 A1, Oct. 14, 2021
Int. Cl. G01S 13/86 (2006.01); G06F 18/2113 (2023.01); G06F 18/25 (2023.01); G06N 20/00 (2019.01); G06V 20/20 (2022.01)
CPC G01S 13/862 (2013.01) [G06F 18/2113 (2023.01); G06F 18/251 (2023.01); G06N 20/00 (2019.01); G06V 20/20 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A computer-implemented sensor fusion method, wherein the method comprises:
receiving sensor data from a multiplicity of sensors, wherein the multiplicity of sensors image a common scene using a multiplicity of measurement modalities, wherein the multiplicity of sensors comprise at least a first sensor providing first sensor data and a second sensor providing second sensor data,
for each sensor of the multiplicity of sensors: determining at least one corresponding feature in the respective sensor data,
for each sensor of the multiplicity of sensors: obtaining corresponding performance specification data,
carrying out a mutual correspondence analysis at least between first features of the first sensor data and second features of the second sensor data taking into account the corresponding performance specification data of the first sensor and the second sensor, the mutual correspondence analysis determining whether, for one or more of the first features that are selected in accordance with the performance specification data, a corresponding one of the second features is present or whether a corresponding one of the second features is absent, and
carrying out the sensor fusion on the basis of a result of the correspondence analysis.