Systems and methods of sensor data fusion
Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.
1 . A system for sensor data fusion for sensor management and utilization in satellite command and control, comprising:
at least one computer processor including a memory;
at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine;
at least one first radio frequency (RF) power sensor operable to capture a first power measurement data of at least one RF signal sent or received by a satellite; and
at least one second RF power sensor operable to capture a second power measurement data of the at least one RF signal sent or received by the satellite;
wherein the at least one computer processor is operable to analyze the first power measurement data and the second power measurement data;
wherein the at least one computer processor is operable to receive at least one query;
wherein the at least one curation engine is operable to curate the first power measurement data and the second power measurement data, the at least one link engine is operable to link the curated first power measurement data and the curated second power measurement data, the at least one fusion engine is operable to fuse the curated first power measurement data and the curated second power measurement data, the at least one inference engine is operable to determine at least one inference from the curated first power measurement data and the curated second power measurement data, and the at least one validation engine is operable to validate the curated first power measurement data and the curated second power measurement data;
wherein the at least one inference engine is operable to determine a second inference;
wherein the at least one validation engine is operable to use artificial intelligence to compare the at least one inference to the second inference;
wherein the at least one validation engine validates the at least one inference as valid when the comparison between the at least one inference and the second inference exceeds a predefined threshold; and
wherein the at least one computer processor is operable to instruct the satellite to change attitude from a first orientation to a second orientation based on the at least one valid inference.
2 . The system of claim 1 , wherein the predefined threshold includes the at least one inference being within about 7.5% or less of the second inference.
3 . The system of claim 1 , wherein the system is operable to store the curated first power measurement data and the curated second power measurement data after the at least one validation engine validates the at least one inference as valid.
4 . The system of claim 1 , wherein the at least one validation engine is operable to validate the at least one inference as valid passively and/or actively.
5 . The system of claim 4 , wherein passive validation includes not modifying a parameter of the at least one RF signal.
6 . The system of claim 4 , wherein active validation includes modifying at least one parameter of the at least one RF signal.
7 . The system of claim 1 , wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.
8 . A method for sensor data fusion for sensor management and utilization in satellite command and control, comprising:
providing at least one computer processor including a memory;
providing at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine;
at least one first radio frequency (RF) power sensor capturing a first power measurement data of at least one RF signal sent or received by a satellite;
at least one second RF power sensor capturing a second power measurement data from the at least one RF signal sent or received by a satellite;
analyzing by the at least one computer processor the first power measurement data and the second power measurement data;
receiving by the at least one computer processor at least one query;
curating by the at least one curation engine the first power measurement data and the second power measurement data, linking by the at least one link engine the curated first power measurement data and the curated second power measurement data, fusing by the at least one fusion engine the curated first power measurement data and the curated second power measurement data, determining at least one inference by the at least one inference engine from the curated first power measurement data and the curated second power measurement data, and validating by the at least one validation engine the curated first power measurement data and the curated second power measurement data;
determining by the at least one inference engine a second inference;
comparing by the at least one validation engine via artificial intelligence the at least one inference to the second inference;
validating by the at least one validation engine the at least one inference as valid when the comparison between the at least one inference and the second inference exceeds a predefined threshold; and
instructing by the at least one computer processor the satellite to change attitude from a first orientation to a second orientation based on the at least one valid inference.
9 . The method of claim 8 , wherein the predefined threshold includes the at least one inference being within about 7.5% or less of the second inference.
10 . The method of claim 8 , further comprising validating the at least one inference as valid passively and/or actively.
11 . The method of claim 10 , wherein validating passively includes not modifying a parameter of the at least one RF signal.
12 . The method of claim 10 , wherein validating actively includes modifying at least one parameter of the at least one RF signal.
13 . The method of claim 8 , further comprising adjusting via the at least one validation engine using artificial intelligence the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.
14 . The method of claim 8 , further comprising storing the curated first power measurement data and the curated second power measurement data after the at least one validation engine validates the at least one inference as valid.
15 . A system for sensor data fusion for sensor management and utilization in satellite command and control, comprising:
at least one computer processor including a memory;
at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine; and
at least two sensors, each of the at least two sensors operable to measure a first power of at least one radio frequency (RF) signal sent or received by a satellite and a second power of the at least one RF signal sent or received by the satellite;
wherein the at least one computer processor is operable to analyze the first power and the second power;
wherein the at least one computer processor is operable to receive at least one query;
wherein the at least one curation engine is operable to curate the first power and the second power, the at least one link engine is operable to link the curated first power and the curated second power, the at least one fusion engine is operable to fuse the curated first power and the curated second power, the at least one inference engine is operable to determine at least one inference from the curated first power and the curated second power, and the at least one validation engine is operable to validate the curated first power and the curated second power;
wherein the at least one inference engine is operable to determine a second inference;
wherein the at least one validation engine is operable to use artificial intelligence to compare the at least one inference to the second inference;
wherein the at least one validation engine validates the at least one inference as valid when the comparison between the at least one inference and the second inference exceeds a predefined threshold;
wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine; and
wherein the at least one computer processor is operable to instruct the satellite to change attitude from a first orientation to a second orientation based on the at least one valid inference.
16 . The system of claim 15 , wherein the predefined threshold includes the at least one inference being within about 7.5% or less of the second inference.
17 . The system of claim 15 , wherein the at least one validation engine is operable to validate the at least one inference as valid passively and/or actively.
18 . The system of claim 17 , wherein passive validation includes not modifying a parameter.
19 . The system of claim 17 , wherein active validation includes modifying at least one parameter.
20 . The system of claim 15 , wherein the system is operable to store the curated first power and the curated second power after the at least one validation engine validates the at least one inference.