Systems, methods, and devices for electronic spectrum management
First Claim
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1. A method for automatic signal detection in a radio-frequency (RF) environment, comprising:
- learning the RF environment to a settled percent during a period of time based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment;
forming a knowledge map of the RF environment based on the power level measurements of the RF environment;
automatically extracting at least one temporal feature of the RF environment from the knowledge map;
scrubbing a real-time spectral sweep against the knowledge map;
calculating a first derivative of the power level measurements and a second derivative of the power level measurements;
selecting most prominent derivatives of the first derivative and the second derivative;
performing a squaring function on the most prominent derivatives;
detecting at least one signal in the RF environment based on 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; and
subtracting the baseline from the real-time spectral sweep to reveal the at least one signal.
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Abstract
Systems, methods, and devices enable spectrum management by identifying, classifying, and cataloging signals of interest based on radio frequency measurements. Signal data is compared with stored data to identify the signal of interest. Signal degradation data is calculated based on noise figure parameters, hardware parameters and environment parameters.
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Citations
20 Claims
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1. A method for automatic signal detection in a radio-frequency (RF) environment, comprising:
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learning the RF environment to a settled percent during a period of time based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment; forming a knowledge map of the RF environment based on the power level measurements of the RF environment; automatically extracting at least one temporal feature of the RF environment from the knowledge map; scrubbing a real-time spectral sweep against the knowledge map; calculating a first derivative of the power level measurements and a second derivative of the power level measurements; selecting most prominent derivatives of the first derivative and the second derivative; performing a squaring function on the most prominent derivatives; detecting at least one signal in the RF environment based on 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; and subtracting the baseline from the real-time spectral sweep to reveal the at least one signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for automatic signal detection in a radio-frequency (RF) environment, comprising:
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at least one apparatus for detecting signals in the RF environment; wherein the at least one apparatus is operable to sweep and learn the RF environment to a settled percent during a period of time based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment; wherein the at least one apparatus is operable to form a knowledge map based on the power level measurements of the RF environment; wherein the at least one apparatus is operable to automatically extract at least one temporal feature of the RF environment from the knowledge map; wherein the at least one apparatus is operable to scrub a real-time spectral sweep against the knowledge map; wherein the at least one apparatus is operable to calculate a first derivative of the power level measurements and a second derivative of the power level measurements; wherein the at least one apparatus is operable to select most prominent derivatives of the first derivative and the second derivative; wherein the at least one apparatus is operable to perform a squaring function on the most prominent derivatives; wherein the at least one apparatus is operable to detect at least one signal in the RF environment based on matched positive and negative gradients; wherein the at least one apparatus is operable to average the real-time spectral sweep, remove areas identified by the matched positive and negative gradients, and connect points between removed areas to determine a baseline; and wherein the at least one apparatus is operable to subtract the baseline from the real-time spectral sweep to reveal the at least one signal. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification