System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization

A system for spectrum management in an electromagnetic environment comprising:

• at least one monitoring sensor operable to monitor the electromagnetic environment and create measured data based on the electromagnetic environment;
• at least one data analysis engine for analyzing the measured data;
• a semantic engine including a language dictionary and a programmable rules and policy editor, wherein the semantic engine is in network communication with the at least one data analysis engine;
• and
• a tip and cue server;
• wherein the at least one data analysis engine includes a detection engine, an identification engine, a classification engine, a geolocation engine, and a learning engine, wherein the detection engine is operable to automatically detect at least one signal of interest, and wherein the learning engine is operable to learn the electromagnetic environment;
• wherein the learning engine is operable to learn information from the detection engine, the classification engine, the identification engine, and/or the geolocation engine;
• wherein the programmable rules and policy editor includes at least one rule and/or at least one policy, and wherein one or more of the at least one rule and/or the at least one policy is defined by at least one customer;
• wherein the semantic engine is operable to create a semantic map including target data using semantic fingerprinting and a Boolean vector;
• and
• wherein the tip and cue server is operable to use analyzed data from the at least one data analysis engine and information from the semantic engine to create actionable data.

A method for spectrum management in an electromagnetic environment comprising:

• providing a semantic engine including a language dictionary and a programmable rules and policy editor, wherein the programmable rules and policy editor includes at least one rule and/or at least one policy, and wherein one or more of the at least one rule and/or the at least one policy is defined by at least one customer;
• monitoring the electromagnetic environment using at least one monitoring sensor and creating measured data based on the electromagnetic environment;
• analyzing the measured data using at least one data analysis engine, thereby creating analyzed data, wherein the at least one data analysis engine includes a detection engine and a learning engine, wherein the at least one data analysis engine is in network communication with the semantic engine;
• learning the electromagnetic environment using the learning engine;
• automatically detecting at least one signal of interest using the detection engine;
• the semantic engine creating a semantic map including target data using semantic fingerprinting and a Boolean vector;
• creating actionable data using a tip and cue server based on the analyzed data from the at least one data analysis engine and information from the semantic engine.

A method for spectrum management in an electromagnetic environment comprising:

• providing a semantic engine including a language dictionary and a programmable rules and policy editor, wherein the programmable rules and policy editor includes at least one rule and/or at least one policy, and wherein one or more of the at least one rule and/or the at least one policy is defined by at least one customer;
• monitoring the electromagnetic environment using at least one monitoring sensor and creating measured data based on the electromagnetic environment;
• analyzing the measured data using at least one data analysis engine, thereby creating analyzed data, wherein the at least one data analysis engine includes a detection engine, a classification engine, an identification engine, a geolocation engine, and a learning engine, wherein the at least one data analysis engine is in network communication with the semantic engine;
• learning the electromagnetic environment using the learning engine;
• automatically detecting at least one signal of interest using the detection engine;
• classifying the at least one signal of interest using the classification engine;
• identifying the at least one signal of interest using the identification engine;
• determining a location of the at least one signal of interest using the geolocation engine;
• the semantic engine creating a semantic map including target data using semantic fingerprinting and a Boolean vector;
• creating actionable data using a tip and cue server based on the analyzed data from the at least one data analysis engine and information from the semantic engine;
• wherein the learning engine is operable to learn information from the detection engine, the classification engine, the identification engine, and/or the geolocation engine.