Systems, methods, and devices having databases 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 in a learning period 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;
creating a profile of the RF environment based on the knowledge map, wherein the profile comprises a highest power level for each frequency detected during the learning period;
scrubbing a real-time spectral sweep against the profile;
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 apparatus are provided for automated identification of baseline data and changes in state in a wireless communications spectrum, by identifying sources of signal emission in the spectrum by automatically detecting signals, analyzing signals, comparing signal data to historical and reference data, creating corresponding signal profiles, and determining information about the baseline data and changes in state based upon the measured and analyzed data in near real time, which is stored on each apparatus or device and/or on a remote server computer that aggregates data from each apparatus or device.
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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 in a learning period 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; creating a profile of the RF environment based on the knowledge map, wherein the profile comprises a highest power level for each frequency detected during the learning period; scrubbing a real-time spectral sweep against the profile; 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 in a learning period 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 create a profile of the RF environment based on the knowledge map, wherein the profile comprises a highest power level for each frequency detected during the learning period; wherein the at least one apparatus is operable to scrub a real-time spectral sweep against the profile; 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