Algorithm of sensor management based on information entropy

With information gain obtained by information entropy and evolution of information entropy which characterize uncertainty of target search location, an optimizing algorithm of detection and classification used in multisensors and multitargets is put forward. Namely, information entropy of current sampling time is computed and information entropy of next sampling time is predicted for each detection cell. The detection cell of maximum information gain is the next one to search. The effectiveness of algorithm is testified by simulation results.