US 12,452,713 B2
Systems, methods, and devices for electronic spectrum management
Ronald C. Dzierwa, Baltimore, MD (US); Gabriel R. Garcia, Severna Park, MD (US); and Daniel Carbajal, Severna Park, MD (US)
Assigned to DIGITAL GLOBAL SYSTEMS, INC, Tysons Corner, VA (US)
Filed by Digital Global Systems, Inc., Tysons Corner, VA (US)
Filed on Apr. 2, 2025, as Appl. No. 19/098,423.
Application 19/098,423 is a continuation of application No. 17/956,966, filed on Sep. 30, 2022.
Application 17/956,966 is a continuation of application No. 17/244,375, filed on Apr. 29, 2021, granted, now 11,463,898, issued on Oct. 4, 2022.
Application 17/244,375 is a continuation of application No. 16/719,066, filed on Dec. 18, 2019, granted, now 10,999,752, issued on May 4, 2021.
Application 16/719,066 is a continuation of application No. 16/371,527, filed on Apr. 1, 2019, granted, now 10,517,005, issued on Dec. 24, 2019.
Application 16/371,527 is a continuation of application No. 15/587,853, filed on May 5, 2017, granted, now 10,257,728, issued on Apr. 9, 2019.
Application 15/587,853 is a continuation in part of application No. 15/412,982, filed on Jan. 23, 2017, granted, now 10,122,479, issued on Nov. 6, 2018.
Application 15/587,853 is a continuation in part of application No. 15/236,524, filed on Aug. 15, 2016, abandoned.
Application 15/412,982 is a continuation of application No. 14/788,842, filed on Jul. 1, 2015, granted, now 9,420,473, issued on Aug. 16, 2016.
Application 14/788,842 is a continuation of application No. 14/504,770, filed on Oct. 2, 2014, granted, now 9,094,975, issued on Jul. 28, 2015.
Application 14/504,770 is a continuation of application No. 14/329,815, filed on Jul. 11, 2014, granted, now 8,885,696, issued on Nov. 11, 2014.
Application 14/329,815 is a continuation of application No. 14/082,930, filed on Nov. 18, 2013, granted, now 8,824,536, issued on Sep. 2, 2014.
Application 14/082,930 is a continuation of application No. 13/913,013, filed on Jun. 7, 2013, granted, now 9,622,041, issued on Apr. 11, 2017.
Claims priority of provisional application 61/789,758, filed on Mar. 15, 2013.
Prior Publication US 2025/0234223 A1, Jul. 17, 2025
This patent is subject to a terminal disclaimer.
Int. Cl. H04W 24/08 (2009.01); G06N 5/022 (2023.01); G06N 20/00 (2019.01); H04B 17/23 (2015.01); H04B 17/27 (2015.01); H04B 17/309 (2015.01); H04B 17/318 (2015.01); H04B 17/391 (2015.01); H04W 16/14 (2009.01); H04W 64/00 (2009.01)
CPC H04W 24/08 (2013.01) [G06N 5/022 (2013.01); G06N 20/00 (2019.01); H04B 17/23 (2015.01); H04B 17/27 (2015.01); H04B 17/309 (2015.01); H04B 17/318 (2015.01); H04W 16/14 (2013.01); H04W 64/006 (2013.01); H04B 17/3911 (2015.01); H04W 64/00 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for automatic signal detection in a radio-frequency (RF) environment, comprising:
learning the RF environment, including power level measurements of one or more frequency bins within the RF environment;
forming a knowledge map of the RF environment based on the power level measurements;
scrubbing a real-time spectral sweep against the knowledge map to create an alert for a spike in power and/or bandwidth for the one or more frequency bins;
calculating a first derivative of the power level measurements and a second derivative of the power level measurements;
smoothing the real-time spectral sweep with a correction vector;
applying a gradient detection algorithm to the smoothed real-time spectral sweep to create matched positive and negative gradients;
detecting at least one signal in the RF environment based on the matched positive and negative gradients;
averaging the real-time spectral sweep, removing areas identified by the matched positive and negative gradients, and connecting points between removed areas to determine a baseline;
calculating and storing signal degradation data for the at least one signal based at least in part on noise figure parameters, hardware parameters, and environmental parameters; and
creating a reconstructed signal using compressed data for deltas and the baseline;
wherein the deltas are differentials from the baseline;
wherein the detecting the at least one signal in the RF environment comprises automatically fine-tuning a threshold of power level on a segmented basis while extracting at least one temporal feature from the knowledge map;
wherein determining the baseline is based on averaging past power level measurements and subtracting at least one signal of interest based on the matched positive and negative gradients;
wherein a pre-recognition delay parameter sets a minimum number of consecutive scans of the RF environment to determine if the at least one signal is a signal of interest; and
wherein the hardware parameters comprise antenna position, antenna type, orientation, and/or effective isotropic radiated power (EIRP).