IP Library › Granted Patent US 12,688,259
Granted Patent B2
US 12,688,259 · App. 19/374,650 · Granted Jul 21, 2026

Systems and methods of sensor data fusion

Inventor: Armando Montalvo (Winter Garden, FL)
Assignee: Digital Global Systems, Inc.
G06F18/256B25J9/163B25J9/1694B60R19/483B60T8/1755B60T8/3275B60W10/18B60W10/184B60W30/085B60W30/09B60W60/00B60W60/0018B60W60/00186B62D15/0285G01C3/00G01C21/1652G01C21/3804G01C21/3811G01C21/3848G01C22/00G01S5/14G01S7/4808G01S11/00G01S13/08G01S13/103G01S13/42G01S15/08G01S15/101G01S15/42G01S17/08G01S17/88G01S17/894G05B13/0205G06F7/14G06F7/16G06F16/24G06F16/245G06F16/2455G06F16/24556G06F16/2456G06F16/33G06F16/334G06F16/43G06F16/53G06F16/903G06F16/90335G06F16/9035G06F17/18G06F18/217G06F18/2431G06F18/25G06F18/251G06N3/02G06N3/0464G06N5/022G06N5/042G06N5/045G06N5/046G06N5/048G06T7/521G06V10/764G06V10/803G06V10/82G06V20/56G08G1/0133G08G1/04G08G1/042H04L67/12H04W4/38B25J9/1664B60T2201/00B60T2201/03B60W2050/0052B60W2050/021B60W2050/0215B60W2050/022B60W2420/00B60W2420/40B60W2420/403B60W2420/408B60W2420/50B60W2510/069B60W2510/18B60W2520/04B60W2540/12B60W2554/801B60W2554/802B60W2556/35B60W2710/18B60W2754/30G01S2013/93185G05D2101/15G05D2111/50G05D2111/67G06F18/213G06N5/04G06N20/00G06T2207/10028G06T2207/20024G06T2207/20084G06T2207/30252G06T2207/30264G06V10/80G08B29/188
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Quick Facts
Patent No.
US 12,688,259
App. No.
19/374,650
Filed
Oct 30, 2025
Granted
Jul 21, 2026
Kind
B2
Examiner
KAY, DOUGLAS
Art Unit
2857
USPC
702/149
Abstract

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.

Claims (58)

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 and at least one fusion engine;

at least one first radio frequency (RF) power sensor operable to capture a first power measurement data of at least one RF signal 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 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, creating a curated first power measurement data and a curated second power measurement data, and the at least one fusion engine is operable to fuse the curated first power measurement data and the curated second power measurement data;

wherein the at least one curation engine is operable to curate the first power measurement data by categorizing the first power measurement data into at least one first power property and/or at least one first power sub-property;

wherein the at least one first power property and/or the at least one first power sub-property includes a first timing value of at least one first data point of the first and/or second power measurement data received by the satellite over time;

wherein the at least one curation engine is operable to curate the second power measurement data by categorizing the second power measurement data into at least one second power property and/or at least one second power sub-property;

wherein the at least one second power property and/or the at least one second power sub-property includes the first timing value of the at least one first data point of the second power measurement data received by the satellite over time and/or at least a second timing value of the second power measurement data received by the satellite over time;

wherein the at least one curation engine is operable to filter the curated first power measurement data and the curated second power measurement data based in part on at least one common power property and/or at least one common power sub-property;

wherein the at least one curation engine is operable to calculate a degree of certainty that the at least one first power property is correlated to the at least one second power property or the at least one first power sub-property is correlated to the at least one second power sub-property;

wherein the at least one fusion engine creates at least one new data set; and

wherein the at least one computer processor is located in a base station and is operable to transmit command signals to the satellite to instruct the satellite to move from a first orientation to a second orientation based on the at least one new data set.

2 . The system of claim 1 , wherein the at least one curation engine is operable to use artificial intelligence to automatically categorize the first power measurement data into the at least one first power property and/or the at least one first power sub-property and the second power measurement data into the at least one second power property and/or the at least one second power sub-property based in part on historical accuracy of previous categorizations by an artificial intelligence engine.

3 . The system of claim 1 , wherein the at least one curation engine is operable to curate heterogeneous, partially heterogeneous, or homogeneous properties and/or sub-properties.

4 . The system of claim 1 , wherein the at least one computer processor is located on or in a machine, an edge device, at least one server, and/or a cloud.

5 . The system of claim 1 , wherein the at least one first RF power sensor and/or the at least one second RF power sensor is operable to include a thermal power sensor, a diode detector, and/or a spectrometer.

6 . The system of claim 1 , wherein the at least one first power property and/or the at least one first power sub-property is operable to include amplitude of the at least one RF signal, a power of the at least one RF signal, a frequency of the at least one RF signal, and/or a signal strength for the at least one RF signal.

7 . 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 and at least one fusion engine;

at least one first radio frequency (RF) power sensor capturing a first power measurement data of at least one RF signal received by a satellite;

at least one second RF power sensor capturing a second power measurement data from the at least one RF signal 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, creating a curated first power measurement data and a curated second power measurement data, and fusing by the at least one fusion engine the curated first power measurement data and the curated second power measurement data;

curating by the at least one curation engine the first power measurement data by categorizing the first power measurement data into at least one first power property and/or at least one first power sub-property;

wherein the at least one first power property and/or the at least one first power sub-property includes a first timing value of at least one first data point of the first and/or second power measurement data received by the satellite over time;

curating by the at least one curation engine the second power measurement data by categorizing the second power measurement data into at least one second power property and/or at least one second power sub-property;

wherein the at least one second power property and/or the at least one second power sub-property includes the first timing value of the at least one first data point of the second power measurement data received by the satellite over time and/or at least a second timing value of the second power measurement data received by the satellite over time;

filtering by the at least one curation engine the curated first power measurement data and the curated second power measurement data based in part on at least one common power property and/or at least one common power sub-property;

calculating by the at least one curation engine a degree of certainty that the at least one first power property is correlated to the at least one second power property or the at least one first power sub-property is correlated to the at least one second power sub-property;

creating by the at least one fusion engine at least one new data set; and

transmitting a command signal by the at least one computer processor located in a base station to the satellite instructing the satellite to move from a first orientation to a second orientation based on the at least one new data set.

8 . The method of claim 7 , wherein the at least one first RF power sensor and/or the at least one second RF power sensor is operable to include a thermal power sensor, a diode detector, and/or a spectrometer.

9 . The method of claim 7 , further comprising the at least one curation engine categorizing the at least one first power property and/or the at least one first power sub-property and the at least one second power property and/or the at least one second power sub-property using artificial intelligence based in part on historical accuracy of previous categorizations by the at least one curation engine.

10 . The method of claim 7 , further comprising curating the first power measurement data and the second power measurement data in real-time.

11 . The method of claim 7 , further comprising curating heterogeneous, partially heterogeneous, or homogeneous properties and/or sub-properties.

12 . 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 and at least one fusion 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 received by a satellite and a second power of the at least one RF signal 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, creating a curated first power and a curated second power, and the at least one fusion engine is operable to fuse the curated first power and the curated second power;

wherein the at least one curation engine is operable to curate the first power by categorizing the first power into at least one first power property and/or at least one first power sub-property based in part on the at least one query;

wherein the first power property and/or the first power sub-property includes a first timing value of at least one first data point of the first and/or second power received by the satellite over time;

wherein the at least one curation engine is operable to curate the second power by categorizing the second power into at least one second power property and/or at least one second power sub-property based in part on the at least one query;

wherein the second power property and/or the second power sub-property includes the first timing value of the at least one first data point of the second power received by the satellite over time and/or at least a second timing value of the second power received by the satellite over time;

wherein the at least one curation engine is operable to filter the curated first power and the curated second power based in part on the at least one query;

wherein the at least one curation engine is operable to calculate a degree of certainty that the at least one first power property is correlated to the at least one second power property or the at least one first power sub-property is correlated to the at least one second power sub-property;

wherein the at least one fusion engine creates at least one new data set; and

wherein the at least one computer processor is located in a base station and is operable to transmit command signals to the satellite to instruct the satellite to move from a first orientation to a second orientation a component of the satellite to adjust based on the at least one new data set.

13 . The system of claim 12 , wherein the at least one curation engine is operable to curate heterogeneous, partially heterogeneous, or homogeneous properties and/or sub-properties.

14 . The system of claim 12 , wherein the at least one curation engine is operable to use artificial intelligence to automatically categorize the curated first power into the at least one first power property and/or the at least one first power sub-property and the curated second power into the at least one second power property and/or the at least one second power sub-property based in part on historical accuracy of previous categorizations by an artificial intelligence engine.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 13, 2025
From: MONTALVO, ARMANDO
To: DIGITAL GLOBAL SYSTEMS, INC.
Reel/Frame 072896/0942 →
Continuity (5)
Continuation 19252795 · Jun 27, 2025
Continuation 19237662 · Jun 13, 2025
Continuation 18990121 · Dec 20, 2024
Continuation 18988120 · Dec 19, 2024
Related Publication 20260057040A1 · Feb 26, 2026
References Cited (235)
US 3924094A · Hansen et al. · 1975 [cited by applicant]
US 6026340A · Corrado et al. · 2000 [cited by applicant]
US 9367683B2 · Kolacinski et al. · 2016 [cited by applicant]
US 9383753B1 · Templeton et al. · 2016 [cited by applicant]
US 10073456B2 · Mudalige et al. · 2018 [cited by applicant]
US 10095230B1 · Hardin · 2018 [cited by applicant]
US 10552691B2 · Li et al. · 2020 [cited by applicant]
US 10748075B2 · Chowdhary et al. · 2020 [cited by applicant]
US 10766137B1 · Porter et al. · 2020 [cited by applicant]
US 10915765B2 · Day et al. · 2021 [cited by applicant]
US 10959371B2 · Zhou et al. · 2021 [cited by applicant]
US 11037320B1 · Ebrahimi Afrouzi et al. · 2021 [cited by applicant]
US 11040444B2 · Cristache · 2021 [cited by applicant]
US 11436429B2 · Jaganathan et al. · 2022 [cited by applicant]
US 11586865B2 · Brahma et al. · 2023 [cited by applicant]
US 11688074B2 · Puri et al. · 2023 [cited by applicant]
US 11966413B2 · Latapie et al. · 2024 [cited by applicant]
US 11983625B2 · Ahuja et al. · 2024 [cited by applicant]
US 12105211B2 · Carcanague et al. · 2024 [cited by applicant]
US 12112174B2 · Sodani et al. · 2024 [cited by applicant]
US 12174301B2 · Hu et al. · 2024 [cited by applicant]
US 12217831B2 · Jaganathan et al. · 2025 [cited by applicant]
US 12287851B1 · Montalvo · 2025 [cited by applicant]
US 12299077B2 · Grau · 2025 [cited by applicant]
US 12488067B2 · Montalvo · 2025 [cited by examiner]
US 12554232B2 · Montalvo · 2026 [cited by applicant]
US 20040019575A1 · Talbot et al. · 2004 [cited by applicant]
US 20050110620A1 · Takeichi et al. · 2005 [cited by applicant]
US 20070239314A1 · Kuvich · 2007 [cited by applicant]
US 20080005075A1 · Horvitz et al. · 2008 [cited by applicant]
US 20080312756A1 · Grichnik et al. · 2008 [cited by applicant]
US 20100164787A1 · Khosravy et al. · 2010 [cited by applicant]
US 20120100799A1 · Tsuchimoto et al. · 2012 [cited by applicant]
US 20120134280A1 · Rotvold et al. · 2012 [cited by applicant]
US 20130325241A1 · Lombrozo et al. · 2013 [cited by applicant]
US 20140070945A1 · Dave et al. · 2014 [cited by applicant]
US 20140114464A1 · Williams et al. · 2014 [cited by applicant]
US 20150306770A1 · Mittal et al. · 2015 [cited by applicant]
US 20160033965A1 · Kopetz · 2016 [cited by applicant]
US 20160185048A1 · Dave et al. · 2016 [cited by applicant]
US 20170004411A1 · Hassan et al. · 2017 [cited by applicant]
US 20170048010A1 · Chowdhery et al. · 2017 [cited by applicant]
US 20170091639A1 · Adams et al. · 2017 [cited by applicant]
US 20170195090A1 · Boidol et al. · 2017 [cited by applicant]
US 20170250751A1 · Kargieman · 2017 [cited by examiner]
US 20180021908A1 · Veittinger · 2018 [cited by applicant]
US 20180032891A1 · Ba et al. · 2018 [cited by applicant]
US 20180284758A1 · Cella et al. · 2018 [cited by applicant]
US 20180343072A1 · Kiannejad · 2018 [cited by examiner]
US 20180372499A1 · Ali et al. · 2018 [cited by applicant]
US 20190049970A1 · Djuric et al. · 2019 [cited by applicant]
US 20190107846A1 · Roy et al. · 2019 [cited by applicant]
US 20190158581A1 · Giannella et al. · 2019 [cited by applicant]
US 20190206400A1 · Cui et al. · 2019 [cited by applicant]
US 20190215338A1 · Baggeroer et al. · 2019 [cited by applicant]
US 20190244309A1 · Ottnad et al. · 2019 [cited by applicant]
US 20190258251A1 · Ditty et al. · 2019 [cited by applicant]
US 20190294999A1 · Guttmann · 2019 [cited by applicant]
US 20190295001A1 · Fusco et al. · 2019 [cited by applicant]
US 20190384865A1 · Jaiswal et al. · 2019 [cited by applicant]
US 20200018605A1 · Kusano · 2020 [cited by applicant]
US 20200026289A1 · Alvarez et al. · 2020 [cited by applicant]
US 20200049511A1 · Sithiravel et al. · 2020 [cited by applicant]
US 20200049837A1 · Werner et al. · 2020 [cited by applicant]
US 20200116837A1 · Aghari et al. · 2020 [cited by applicant]
US 20200219316A1 · Baik et al. · 2020 [cited by applicant]
US 20200265247A1 · Musk et al. · 2020 [cited by applicant]
US 20200300658A1 · Zhang et al. · 2020 [cited by applicant]
US 20200303033A1 · Benz et al. · 2020 [cited by applicant]
US 20200380338A1 · Matsumura · 2020 [cited by applicant]
US 20200391750A1 · Bluvstein et al. · 2020 [cited by applicant]
US 20200405403A1 · Shelton, IV et al. · 2020 [cited by applicant]
US 20210033735A1 · Kleeman · 2021 [cited by applicant]
US 20210063578A1 · Wekel et al. · 2021 [cited by applicant]
US 20210150230A1 · Smolyanskiy et al. · 2021 [cited by applicant]
US 20210157312A1 · Cella et al. · 2021 [cited by applicant]
US 20210181745A1 · Liu et al. · 2021 [cited by applicant]
US 20210194988A1 · Chaysinh et al. · 2021 [cited by applicant]
US 20210246003A1 · Wu et al. · 2021 [cited by applicant]
US 20210278523A1 · Urtasun et al. · 2021 [cited by applicant]
US 20210290311A1 · Fuerst et al. · 2021 [cited by applicant]
US 20210318121A1 · Laroche et al. · 2021 [cited by applicant]
US 20210331695A1 · Ramakrishnan et al. · 2021 [cited by applicant]
US 20210342656A1 · Mittal et al. · 2021 [cited by applicant]
US 20210406560A1 · Park et al. · 2021 [cited by applicant]
US 20220012562A1 · Lazaro-Gredilla et al. · 2022 [cited by applicant]
US 20220035376A1 · Laddah et al. · 2022 [cited by applicant]
US 20220075077A1 · Kato et al. · 2022 [cited by applicant]
US 20220126864A1 · Moustafa et al. · 2022 [cited by applicant]
US 20220146652A1 · Cardei et al. · 2022 [cited by applicant]
US 20220161356A1 · Fujiwara et al. · 2022 [cited by applicant]
US 20220161815A1 · Van Beek et al. · 2022 [cited by applicant]
US 20220163959A1 · Cella et al. · 2022 [cited by applicant]
US 20220163960A1 · Cella et al. · 2022 [cited by applicant]
US 20220179056A1 · Braley et al. · 2022 [cited by applicant]
US 20220261590A1 · Brahma et al. · 2022 [cited by applicant]
US 20220266399A1 · Griffin et al. · 2022 [cited by applicant]
US 20220289175A1 · Kasarla et al. · 2022 [cited by applicant]
US 20220324464A1 · Collin et al. · 2022 [cited by applicant]
US 20220348223A1 · Zhao et al. · 2022 [cited by applicant]
US 20220396281A1 · Brännström et al. · 2022 [cited by applicant]
US 20230038842A1 · Yu et al. · 2023 [cited by applicant]
US 20230079238A1 · Cristache · 2023 [cited by applicant]
US 20230082656A1 · Li et al. · 2023 [cited by applicant]
US 20230089205A1 · Cella et al. · 2023 [cited by applicant]
US 20230092066A1 · Cella et al. · 2023 [cited by applicant]
US 20230098519A1 · Cella et al. · 2023 [cited by applicant]
US 20230110027A1 · Bajpayee et al. · 2023 [cited by applicant]
US 20230111071A1 · Cella et al. · 2023 [cited by applicant]
US 20230112441A1 · Tang et al. · 2023 [cited by applicant]
US 20230135882A1 · Cella et al. · 2023 [cited by applicant]
US 20230149101A1 · Mottram et al. · 2023 [cited by applicant]
US 20230166765A1 · Yoon et al. · 2023 [cited by applicant]
US 20230182768A1 · Oh · 2023 [cited by applicant]
US 20230190204A1 · Helm et al. · 2023 [cited by applicant]
US 20230191608A1 · Horowitz et al. · 2023 [cited by applicant]
US 20230191617A1 · Kim et al. · 2023 [cited by applicant]
US 20230195058A1 · Cella et al. · 2023 [cited by applicant]
US 20230215028A1 · Kim et al. · 2023 [cited by applicant]
US 20230244996A1 · Kumar et al. · 2023 [cited by applicant]
US 20230256618A1 · Park et al. · 2023 [cited by applicant]
US 20230270506A1 · Goodchild et al. · 2023 [cited by applicant]
US 20230288185A1 · Nagasaki et al. · 2023 [cited by applicant]
US 20230331235A1 · Shuman et al. · 2023 [cited by applicant]
US 20230342944A1 · Sullivan et al. · 2023 [cited by applicant]
US 20230347517A1 · Ma et al. · 2023 [cited by applicant]
US 20230394334A1 · Kang et al. · 2023 [cited by applicant]
US 20240038076A1 · Omi · 2024 [cited by examiner]
US 20240045073A1 · Zhang et al. · 2024 [cited by applicant]
US 20240045426A1 · Ditty et al. · 2024 [cited by applicant]
US 20240046612A1 · Panetta et al. · 2024 [cited by applicant]
US 20240058948A1 · Zhai et al. · 2024 [cited by applicant]
US 20240112428A1 · Levi et al. · 2024 [cited by applicant]
US 20240123619A1 · Ning · 2024 [cited by applicant]
US 20240138926A1 · Goodchild et al. · 2024 [cited by applicant]
US 20240142994A1 · Ebrahimi Afrouzi · 2024 [cited by applicant]
US 20240144082A1 · Tarapov et al. · 2024 [cited by applicant]
US 20240152734A1 · Ye · 2024 [cited by applicant]
US 20240159891A1 · Patel · 2024 [cited by applicant]
US 20240175893A1 · Kimishima et al. · 2024 [cited by applicant]
US 20240246559A1 · Agrawal · 2024 [cited by applicant]
US 20240249165A1 · Roche et al. · 2024 [cited by applicant]
US 20240267779A1 · Wu et al. · 2024 [cited by applicant]
US 20240289930A1 · Yang et al. · 2024 [cited by applicant]
US 20240289981A1 · Kuo et al. · 2024 [cited by applicant]
US 20240296044A1 · Day et al. · 2024 [cited by applicant]
US 20240312219A1 · Choi et al. · 2024 [cited by applicant]
US 20240317254A1 · Tran · 2024 [cited by applicant]
US 20240324838A1 · Ebrahimi Afrouzi · 2024 [cited by applicant]
US 20240331403A1 · Shen et al. · 2024 [cited by applicant]
US 20240355151A1 · Arnold · 2024 [cited by applicant]
US 20240378353A1 · Hansen · 2024 [cited by examiner]
US 20240378412A1 · Schrader · 2024 [cited by applicant]
US 20240382216A1 · Hage et al. · 2024 [cited by applicant]
US 20240400100A1 · Harihara Gupta et al. · 2024 [cited by applicant]
US 20240408495A1 · Hibi et al. · 2024 [cited by applicant]
US 20240412494A1 · Balachandran et al. · 2024 [cited by applicant]
US 20240419974A1 · Nehmadi et al. · 2024 [cited by applicant]
US 20250021319A1 · Avedisov et al. · 2025 [cited by applicant]
US 20250026371A1 · Andert et al. · 2025 [cited by applicant]
US 20250053731A1 · Kantimahanti et al. · 2025 [cited by applicant]
US 20250123601A1 · Montalvo · 2025 [cited by applicant]
US 20250124112A1 · Montalvo · 2025 [cited by applicant]
US 20250124114A1 · Montalvo · 2025 [cited by applicant]
US 20250124310A1 · Montalvo · 2025 [cited by applicant]
US 20250130316A1 · Asghari et al. · 2025 [cited by applicant]
US 20250139807A1 · Zou et al. · 2025 [cited by applicant]
US 20250141504A1 · Himmelfarb · 2025 [cited by examiner]
US 20250148054A1 · Montalvo · 2025 [cited by applicant]
US 20250165120A1 · Amitay et al. · 2025 [cited by applicant]
US 20250175779A1 · Eakins et al. · 2025 [cited by applicant]
US 20250200431A1 · Marzban et al. · 2025 [cited by applicant]
US 20250217863A1 · Tunkelang et al. · 2025 [cited by applicant]
US 20250224236A1 · Kabalar et al. · 2025 [cited by applicant]
US 20250237504A1 · Kuhlmann · 2025 [cited by examiner]
US 20250293764A1 · Darabi et al. · 2025 [cited by applicant]
US 20250295461A1 · Brubaker et al. · 2025 [cited by applicant]
US 20250321544A1 · Montalvo · 2025 [cited by examiner]
US 20250334933A1 · Montalvo · 2025 [cited by applicant]
US 20250342176A1 · Tóth et al. · 2025 [cited by applicant]
CA 3032953A1 · 2018 [cited by applicant]
CN 105956290B · 2016 [cited by applicant]
CN 110598299A · 2019 [cited by applicant]
CN 110909762A · 2020 [cited by applicant]
CN 111971633A · 2020 [cited by applicant]
CN 113291493A · 2021 [cited by applicant]
CN 115561795A · 2023 [cited by applicant]
CN 115824203A · 2023 [cited by applicant]
CN 116522279A · 2023 [cited by applicant]
CN 118419285A · 2024 [cited by applicant]
CN 118427205A · 2024 [cited by applicant]
CN 118764836A · 2024 [cited by applicant]
CN 118797559A · 2024 [cited by applicant]
DE 102018220024 · 2020 [cited by applicant]
WO 2010107379A1 · 2010 [cited by applicant]
WO 2018034823A1 · 2018 [cited by applicant]
WO 2022072921A1 · 2022 [cited by applicant]
WO 2023242003A1 · 2023 [cited by applicant]
WO 2024186551A1 · 2024 [cited by applicant]
WO 2024228863A1 · 2024 [cited by applicant]
Allende-Alba, Gerardo, Simone D'Amico, and Oliver Montenbruck. “Radio-frequency sensor fusion for relative navigation of formation flying satellites.” International Journal of Space Science and Engineering 3, No. 2 (201… [cited by examiner]
Vakil, Asad, and et al. “A survey of multimodal sensor fusion for passive RF and EO information integration.” IEEE Aerospace and Electronic Systems Magazine 36, No. 7 (2021): 44-61 (Year: 2021). [cited by examiner]
Reding, Dale F., and Jacqueline Eaton. “Science and Technology Trends 2020-2040: Exploring the S and T Edge.” (2020)) (Year: 2020). [cited by examiner]
Basir, 0. A, and H. C. Shen. “Sensory data fusion: A team consensus approach.” In [Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics, pp. 290-296. IEEE, 1992 (Year: 1992). [cited by applicant]
Basir, Otman A, and Helen C. Shen. “New approach for aggregating multi-sensory data.” Journal of Robotic Systems 10, No. 8 (1993): 1075-1093 (Year: 1993). [cited by applicant]
Brush, “Measurement of microwave power—A review of techniques used for measurement of high-frequency RF power” IEEE Instrumentation & Measurement Magazine Apr. 2007 (Year: 2007). [cited by applicant]
Chen et al., “Track correlation uncertainty evaluation for Multi-sensor Data Fusion System and its application” 2021 IEEE (Year: 2021). [cited by applicant]
Chung et al., “Entropy-Based Markov Chains for Multisensor Fusion” Journal of Intelligent and Robotic Systems 29: 161a189, 2000 (Year: 2000). [cited by applicant]
CN110598299—English translation. [cited by applicant]
CN115561795—English translation. [cited by applicant]
DE-102018220024-B3 machine translation, downloaded Jul. 2025 (Year: 2025). [cited by applicant]
Ebel, Patrick, and et al. “SEN12MS-CR-TS: A remote-sensing data set for multi modal multitemporal cloud removal.” IEEE Transactions on Geoscience and Remote Sensing 60 (2022): 1-14 (Year: 2022). [cited by applicant]
Eenennaam, Providing over-the-horizon awareness to driver support systems by means of multi-hop ad hoc vehicle-to-vehicle communication (thesis); 2008 [retrieved Jul. 25, 2025], University of Twente, 204 pages.https://p… [cited by applicant]
Jin, Xue-Bo, and et al. “Distributed deep fusion predictor for a multi-sensor system based on causality entropy.” Entropy 23, No. 2 (2021 ): 219 (Year: 2021). [cited by applicant]
Kleber et al., “Cooperative Cross-Correlation Algorithm to Optimize Linearity of Fused RF Sensors” IEEE Sensors Journal, vol. 20, No. 7, Apr. 1, 2020 (Year: 2020). [cited by applicant]
Kong, Lingbao, ant et al. “Multi-sensor measurement and data fusion technology for manufacturing process monitoring: a literature review.” International journal of extreme manufacturing 2, No. 2 (2020): 022001 (Year: 20… [cited by applicant]
Lanegger et al., “To Fuse or Not to Fuse: Measuring Consistency in Multi-Sensor Fusion for Aerial Robots” Springer, Aug. 2024 (Year: 2024). [cited by applicant]
Li, Belief Space-Guided Navigation for Robots and Autonomous Vehicles (thesis), May 2021 [retrieved Jul. 24, 2025], Texas A&M University, 123 pages. Retrieved: https://oaktrust.library. tamu.edu/server/api/core/bitstrea… [cited by applicant]
Liu et al., “A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion” Sensors 2015, 15, 7933-7952 (Year: 2015). [cited by applicant]
Long et al., “The Design of Automated Validation System for Satellite Data Transmission System Based on AOS” 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-… [cited by applicant]
Noonan, Colin Anthony. “Measures of effectiveness for data fusion based on information entropy.” PhD diss., Durham University, 2000 (Year: 2000). [cited by applicant]
Peli et al., “Feature Level Sensor Fusion” Part of the SPIE Conference on Sensor Fusion: Architectures. Algorithms, and Applications III. Orlando, Florida, Apr. 1999 (Year: 1999). [cited by applicant]
Rizal, Muhammad, ant et al. “An embedded multi-sensor system on the rotating dynamometer for real-time condition monitoring in milling” Int J Adv Manuf Technol, https://doi.org/10.1007/s00I 70-017-1251-8. [cited by applicant]
Rumfelt et al., “Radio Frequency Power Measurements” Proceedings of the IEEE, vol. 55, No. 6, Jun. 1967 (Year: 1967). [cited by applicant]
Scibelli et al., “Low-cost Stellar Sensor for Attitude Control of Small Satellites” 2019 Photonics & Electromagnetics Research Symposium—Spring (PIERS—SPRING), Rome, Italy, Jun. 17-20, 2019. [cited by applicant]
Shen, Security Challenges and Defense Opportunities of Connected and Autonomous Vehicle Systems in the Physical World (thesis), 2022 (retrieved Jul. 24, 2025), University of California, Irvine, 304 pages. Retrieved: htt… [cited by applicant]
Tan et al., “A New Approach for Small Satellite Gyroscope and Star Tracker Fusion” Indian Journal of Science and Technology, vol. 9(17), May 2016 (Year: 2016). [cited by applicant]
Wei Z, and et al. MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review. Sensors (Basel). Mar. 25, 2022;22(7):2542. doi: 10.3390/s22072542. PMID: 35408157; PMCID: PMC9003130 (Year: 2022). [cited by applicant]
Xiao, Kejiang, Jian Li, and Chunhua Yang. “Exploiting correlation for confident sensing in fusion-based wireless sensor networks.” IEEE Transactions on Industrial Electronics 65, No. 6 (2017): 4962-4972 (Year: 2017). [cited by applicant]
Yang, Guang-Zhong, and et al. “Multi-sensor fusion.” In Body sensor networks, pp. 301-354. London: Springer London, 2014 (Year: 2014). [cited by applicant]
Yeong, D. J., Velasco-Hernandez, G., Barry, J., & Walsh, J. (2021). Sensor and sensor fusion technology in autonomous vehicles: A review. Sensors, 21(6), 2140. (Year: 2021). [cited by applicant]
Zhang, Compiler Support for Robust and High Performance Autonomous Driving Environments (thesis), 2022 (retrieved Jul. 24, 2025], University of Michigan Library, 125 pages. https://dx.doi.org/10. 7302/6919 (Year: 2022). [cited by applicant]
Machine translation for CN-113291493-A, downloaded 2025 (Year: 2025). [cited by applicant]
Machine translation for CN-118419285-A, downloaded 2025 (Year: 2025). [cited by applicant]
International Search Report and Written Opinion dated Feb. 26, 2026 issued by the US Patent Office as International Searching Authority in connection with International Application No. PCT/US2025/058326 (12 pages). [cited by applicant]