針對(duì)具有多個(gè)特征指標(biāo)的模糊多傳感器目標(biāo)識(shí)別問(wèn)題，提出一種新的模糊多傳感器數(shù)據(jù)融合方法。該方法根據(jù)信息熵理論，引入不均衡度定義熵權(quán)矢量，通過(guò)求解數(shù)學(xué)規(guī)劃問(wèn)題，得到各目標(biāo)類(lèi)別的優(yōu)屬度，并給出目標(biāo)識(shí)別規(guī)則。實(shí)驗(yàn)結(jié)果表明，該方法能提高目標(biāo)識(shí)別結(jié)果的客觀(guān)性和可信度，具有可操作性。
關(guān)鍵詞：模糊傳感器；數(shù)據(jù)融合；目標(biāo)識(shí)別；熵權(quán)；優(yōu)屬度

【Abstract】Aiming at the object recognition problem with multiple characteristic indexes for the fuzzy multi-sensor, a new fusion method for the
fuzzy multi-sensor data is proposed. According to the theory of information entropy, the method introduces the disequilibrium index to define the
vector of entropy weight. By solving the mathematical programming, the optimal membership degree for each target type is obtained, and the rule of
object recognition is given. The method improves the objectivity and trustworthy degree of recognition result. The applied example proves that the
method is exercisable.
【Key words】fuzzy sensor; data fusion; object recognition; entropy weight; optimal membership