Systems, methods, and devices for automatic signal detection based on power distribution by frequency over time within a spectrum
Systems, methods and apparatus for automatic alarm management in a radio-frequency (RF) environment are disclosed. An apparatus calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of FFT data of the RF environment. The apparatus then creates a baseline based on the power distribution by frequency of the RF environment in a period of time, identifies at least one alarm situation based on a multiplicity of alarm triggering conditions by comparing the power distribution in real time or near real time to the baseline of the RF environment, identifies at least one signal based on the first derivative and the second derivative of FFT data in the at least one alarm situation, and sends at least one alarm comprising details of the at least one signal identified in the at least one alarm situation.
1 . A method for automatically detecting at least one signal, comprising:
learning an electromagnetic environment;
detecting the at least one signal based on a power distribution by frequency of the electromagnetic environment;
calculating a noise floor of the electromagnetic environment based on the power distribution by frequency; and
curve fitting the power distribution by frequency using a partial differential equation to reject impulse noise;
periodically reevaluating the electromagnetic environment and updating a learning map associated with the electromagnetic environment after completing the reevaluation of the electromagnetic environment;
wherein the updated learning map provides a percentage of utilization of a frequency of at least one non-constant signal.
2 . The method of claim 1 , wherein the power distribution by frequency of the electromagnetic environment includes a 2-dimensional (2D) array with frequency as a horizontal axis and power as a vertical axis over a set length of time.
3 . The method of claim 1 , further comprising performing direction finding (DF) for the at least one signal.
4 . The method of claim 1 , wherein learning the electromagnetic environment occurs during normal operating conditions for the electromagnetic environment when the electromagnetic environment is stable.
5 . The method of claim 1 , further comprising sending at least one alert comprising data relating to the at least one signal.
6 . An apparatus for automatically detecting at least one signal, comprising:
an analyzer engine comprising a management plane;
wherein the analyzer engine is configured to calculate a noise floor of an electromagnetic environment based on a power distribution by frequency calculated by the analyzer engine;
wherein the analyzer engine is configured to automatically detect the at least one signal based on the power distribution by frequency of the electromagnetic environment based on electromagnetic data;
wherein the apparatus is configured to periodically reevaluate the electromagnetic environment and update a learning map associated with the electromagnetic environment after detecting the at least one signal;
wherein the analyzer engine is configured to curve fit the power distribution by frequency using a partial differential equation to reject impulse noise; and
wherein the updated learning map provides a percentage of utilization of a frequency of at least one non-constant signal.
7 . The apparatus of claim 6 , wherein the power distribution by frequency of the electromagnetic environment includes a 2-dimensional (2D) array with frequency as a horizontal axis and power as a vertical axis over a set length of time.
8 . The apparatus of claim 6 , wherein the apparatus is configured to perform direction finding (DF) for the at least one signal.
9 . The apparatus of claim 6 , wherein the apparatus is configured to send at least one alert comprising data relating to the at least one signal.
10 . A method for automatically detecting at least one signal, comprising:
calculating a power distribution by frequency of an electromagnetic environment;
automatically detecting the at least one signal based on analysis of the electromagnetic environment; and
performing direction finding (DF) for the at least one signal;
wherein calculating the power distribution by frequency of the electromagnetic environment includes calculating at least one derivative of fast Fourier transform (FFT) data of the electromagnetic environment;
identifying movements of the at least one signal based on changes in the second derivative of the FFT data.
11 . The method of claim 10 , further comprising storing data relating to the at least one signal in a signal database, wherein the data includes a date the at least one signal was identified, a power of the at least one signal, and a bandwidth associated with the at least one signal.
12 . The method of claim 10 , further comprising learning the electromagnetic environment.
13 . The method of claim 12 , wherein learning the electromagnetic environment occurs during normal operating conditions for the electromagnetic environment when the electromagnetic environment is stable.
14 . The method of claim 10 , wherein the at least one signal includes an anomalous signal.
15 . The method of claim 10 , wherein the at least one signal is from at least one jammer.
16 . The method of claim 10 , further comprising calculating a noise floor of the electromagnetic environment based on the power distribution by frequency.
17 . The method of claim 10 , wherein the DF uses Time Difference of Arrival (TDOA) to locate an aircraft, vehicle, or stationary emitter of the at least one signal.