US 12,207,118 B1
Systems, methods, and devices for automatic signal detection with temporal feature extraction within a spectrum
David William Kleinbeck, Lees Summit, MO (US); Ronald C. Dzierwa, Baltimore, 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 Oct. 17, 2024, as Appl. No. 18/918,772.
Application 18/918,772 is a continuation of application No. 18/644,811, filed on Apr. 24, 2024, granted, now 12,160,763.
Application 18/644,811 is a continuation of application No. 18/525,017, filed on Nov. 30, 2023, granted, now 11,991,547, issued on May 21, 2024.
Application 18/525,017 is a continuation of application No. 18/351,949, filed on Jul. 13, 2023, granted, now 11,838,780, issued on Dec. 5, 2023.
Application 18/351,949 is a continuation of application No. 18/116,620, filed on Mar. 2, 2023, granted, now 11,706,651, issued on Jul. 18, 2023.
Application 18/116,620 is a continuation of application No. 17/387,570, filed on Jul. 28, 2021, granted, now 11,601,833, issued on Mar. 7, 2023.
Application 17/387,570 is a continuation of application No. 16/863,422, filed on Apr. 30, 2020, granted, now 11,082,870, issued on Aug. 3, 2021.
Application 16/863,422 is a continuation of application No. 16/388,002, filed on Apr. 18, 2019, granted, now 10,645,601, issued on May 5, 2020.
Application 16/388,002 is a continuation of application No. 15/681,558, filed on Aug. 21, 2017, granted, now 10,271,233, issued on Apr. 23, 2019.
Application 15/681,558 is a continuation in part of application No. 15/478,916, filed on Apr. 4, 2017, abandoned.
Application 15/681,558 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 15/478,916 is a continuation in part of application No. 14/934,808, filed on Nov. 6, 2015.
Application 14/934,808 is a continuation of application No. 14/504,836, filed on Oct. 2, 2014, granted, now 9,185,591, issued on Nov. 10, 2015.
Application 14/504,836 is a continuation of application No. 14/331,706, filed on Jul. 15, 2014, granted, now 8,977,212, issued on Mar. 10, 2015.
Application 14/331,706 is a continuation in part of application No. 14/086,875, filed on Nov. 21, 2013, granted, now 8,798,548, issued on Aug. 5, 2014.
Application 14/086,875 is a continuation in part of application No. 14/082,873, filed on Nov. 18, 2013, granted, now 8,805,291, issued on Aug. 12, 2014.
Application 14/086,875 is a continuation in part of application No. 14/082,916, filed on Nov. 18, 2013, granted, now 8,780,968, issued on Jul. 15, 2014.
Application 14/086,875 is a continuation in part of application No. 14/082,930, filed on Nov. 18, 2013, granted, now 8,824,536.
Application 14/082,916 is a continuation of application No. 13/912,893, filed on Jun. 7, 2013, granted, now 9,078,162, issued on Jul. 7, 2015.
Application 14/082,873 is a continuation of application No. 13/912,683, filed on Jun. 7, 2013, granted, now 9,288,683, issued on Mar. 15, 2016.
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.
Int. Cl. H04W 24/08 (2009.01); H04B 17/20 (2015.01); H04B 17/23 (2015.01); H04B 17/26 (2015.01); H04B 17/27 (2015.01); H04B 17/29 (2015.01); H04B 17/309 (2015.01); H04B 17/318 (2015.01); H04W 24/10 (2009.01); H04B 17/24 (2015.01); H04W 24/04 (2009.01)
CPC H04W 24/08 (2013.01) [H04B 17/20 (2015.01); H04B 17/23 (2015.01); H04B 17/26 (2015.01); H04B 17/27 (2015.01); H04B 17/29 (2015.01); H04B 17/309 (2015.01); H04B 17/318 (2015.01); H04W 24/10 (2013.01); H04B 17/24 (2015.01); H04W 24/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for signal detection in an electromagnetic environment, comprising:
at least one receiver, at least one processor, and at least one memory;
wherein the system is operable to create power level measurements of the electromagnetic environment;
wherein the system is operable to determine a baseline;
wherein the system is operable to reveal at least one signal based on the baseline to create signal data;
wherein the system is operable to calculate a first derivative of the power level measurements and a second derivative of the power level measurements;
wherein the system is operable to create impressions of the electromagnetic environment-based on a machine learning algorithm, wherein the impressions are determined over time and are interpreted as the at least one signal;
wherein the at least one processor is operable to use a calibration vector, a first smoothing filter, and a second smoothing filter to de-bias raw signal data;
wherein the system is operable to use gradients and the second smoothing filter to create the calibration vector;
wherein the system is operable to process the signal data using compressed data for deltas;
wherein the deltas are differentials from the baseline and minimize data sets or sample data required for comparisons and/or analytics; and
wherein the system is operable to reconstruct the at least one signal using the deltas and the baseline.
 
12. A method for signal detection in an electromagnetic environment, comprising:
creating power level measurements of the electromagnetic environment;
forming a knowledge map of the electromagnetic environment based on the power level measurements of the electromagnetic environment;
determining a baseline;
subtracting the baseline from a spectral sweep to reveal at least one signal to create signal data;
calculating a first derivative of the power level measurements and a second derivative of the power level measurements;
creating impressions of the electromagnetic environment based on a machine learning algorithm, wherein the impressions are determined over time and are interpreted as the at least one signal;
processing the signal data using compressed data for deltas;
de-biasing raw signal data using a calibration vector, a first smoothing filter, and a second smoothing filter; and
reconstructing the at least one signal using the deltas and the baseline;
wherein the deltas are differentials from the baseline and minimize data sets or sample data required for comparisons and/or analytics; and
wherein the system is operable to use gradients and the second smoothing filter to create the calibration vector.
 
15. A method for signal detection in an electromagnetic environment, comprising:
scrubbing a spectral sweep against a knowledge map of the electromagnetic environment;
smoothing the spectral sweep with a correction vector;
detecting at least one signal in the electromagnetic environment;
determining a baseline;
subtracting the baseline from the spectral sweep to reveal the at least one signal to create signal data;
calculating a first derivative of the power level measurements and a second derivative of the power level measurements;
creating impressions of the electromagnetic environment based on a machine learning algorithm, wherein the impressions are determined over time and are interpreted as the at least one signal;
processing the signal data using compressed data for deltas;
de-biasing raw signal data using a calibration vector, a first smoothing filter, and a second smoothing filter; and
detecting a narrowband signal overlapping in frequency with a wideband signal;
wherein the deltas are differentials from the baseline and minimize data sets or sample data required for comparisons and/or analytics; and
wherein the system is operable to use gradients and the second smoothing filter to create the calibration vector.