Unmanned vehicle recognition and threat management

An apparatus for signal classification in a radio frequency (RF) environment, comprising:

• at least one node device comprising a classification engine;
• wherein the at least one node device is operable to receive RF data;
• wherein the at least one node device is operable to average Fast Fourier Transform (FFT) data derived from the RF data into at least one tile;
• wherein the at least one tile is represented as at least one waterfall image;
• wherein the classification engine is operable to classify at least one signal emitting device by comparing at least one signal emitted from the at least one signal emitting device to classification data stored in a classification library in real time;
• and
• wherein the at least one node device is operable to create at least one analyzed waterfall image based on identification of the at least one signal.

A method for signal classification in a radio frequency (RF) environment, comprising:

• at least one RF receiver capturing RF data in the RF environment, deriving Fast Fourier Transform (FFT) data from the RF data, and transmitting the FFT data to at least one node device;
• the at least one node device averaging the FFT data derived from the RF data into at least one tile represented as at least one waterfall image;
• and
• the at least one node device creating at least one analyzed waterfall image for identification of at least one signal;
• wherein the at least one analyzed waterfall image includes a visual indication of the at least one signal.