Radiance library forecasting for time-critical hyperspectral target detection systems

An automated method of adaptive threshold hyperspectral detection comprising:

• acquiring atmospheric forecast information based on current real time atmospheric measurements;
• selecting at least one surface reflectance library, wherein said surface reflectance library is based on surface reflectance measurements;
• acquiring data collection and sensor parameters;
• inputting said atmospheric forecast information, at least one selected surface reflectance library and said data collection and sensor parameters into a model to produce at least one mission radiance library;
• collecting hyperspectral data;
• comparing said hyperspectral data to said mission radiance library to identify targets;
• adapting threshold of hyperspectral data detection automatically.

An automated system for performing adaptive threshold hyperspectral detection comprising:

• a hyperspectral detection processing unit connected to at least one atmospheric forecast database and at least one reflectance library database;
• a sensor connected to said hyperspectral detection processing unit;
• and
• a comparator connected to said hyperspectral detection processing unit,
• wherein said hyperspectral detection processing unit is adapted to:
• input atmospheric forecast information from said atmospheric forecast database, at least one selected reflectance library from said reflectance library database, and data collection and sensor parameters relating to said sensor;
• process a model to produce at least one mission radiance library;
• and
• automatically assign optimal threshold for detection processing;
• wherein said sensor is adapted to collect hyperspectral data, and
• wherein said comparator is adapted to compare said hyperspectral data to said mission radiance library to identify features.