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Systems, methods, and devices for electronic spectrum management

  • US 10,257,728 B2
  • Filed: 05/05/2017
  • Issued: 04/09/2019
  • Est. Priority Date: 03/15/2013
  • Status: Active Grant
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 based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment;

    indexing the power level measurements for each frequency interval in a spectrum section during a period of time to reach the settled percent;

    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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