| CPC H04W 24/08 (2013.01) [H04B 17/23 (2015.01); H04B 17/26 (2015.01); H04B 17/27 (2015.01); H04B 17/309 (2015.01); H04B 17/318 (2015.01); H04W 4/029 (2018.02); H04W 16/14 (2013.01); H04W 24/10 (2013.01); H04W 64/006 (2013.01); H04B 17/3911 (2015.01)] | 20 Claims |

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1. An apparatus for automatic signal detection in an electromagnetic environment, comprising:
at least one receiver, at least one processor, and at least one memory;
wherein the apparatus is operable to create power level measurements of one or more frequency bins within the electromagnetic environment;
wherein the apparatus is operable to learn a baseline;
wherein the apparatus is operable to automatically detect at least one signal based on the baseline;
wherein the apparatus is operable to create a knowledge map of the electromagnetic environment based on a machine learning (ML) algorithm;
wherein the knowledge map is based on the power level measurements of the one or more frequency bins within the electromagnetic environment;
wherein the apparatus is operable to create deltas that are differentials from the baseline and minimize a data set or sample data required for comparisons and/or analytics;
wherein the apparatus is operable to reconstruct the at least one signal using the deltas and the baseline;
wherein the apparatus is operable to fill gaps during reconstruction of the at least one signal where signal data is absent;
wherein the apparatus is operable to smooth the signal data using a first smoothing filter;
wherein the apparatus is operable to use gradients and a second smoothing filter to the smoothed signal data to create a calibration vector;
wherein the apparatus is operable to use the calibration vector to de-bias raw signal data;
wherein the apparatus includes a Temporal Feature Extraction (TFE) system operable to automatically tune parameters and dynamically adjust sensitivity of the one or more frequency bins within the electromagnetic environment;
wherein the apparatus is operable to calculate signal degradation data for the at least one signal based at least in part on noise figure parameters and hardware parameters; and
wherein the hardware parameters comprise antenna position, antenna type, orientation, and/or effective isotropic radiated power (EIRP).
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