CAJ | 학술논문

针对雷达辐射源识别过程中数据信息量大的实际情况，应用多传感器最优组合理论，提出一种对辐射源侦察传感器的优化组合方法，以提高融合效率；此外，将D-S证据理论用于数据融合过程中，结合雷达辐射源识别问题的特点，并借鉴信息论中熵的概念，对基本概率赋值函数( BPAF)进行了建模；仿真结果表明该模型的有效性和融合算法的优良性能。
침대뢰체복사원식별과정중수거신식량대적실제정황，응용다전감기최우조합이론，제출일충대복사원정찰전감기적우화조합방법，이제고융합효솔；차외，장D-S증거이론용우수거융합과정중，결합뢰체복사원식별문제적특점，병차감신식론중적적개념，대기본개솔부치함수( BPAF)진행료건모；방진결과표명해모형적유효성화융합산법적우량성능。
Focusing on the fact that there exists large amount of data during the process of radar emitter recognition, with the application of the theory of multi-sensor optimal combination, a method of the optimal combination of radiation source reconnaissance sensors is put forward in order to improve fusion efficiency;in addition, with the application of the D-S evidence theory for data fusion process, combining the specific characteristic of radar emitter recognition and quoting the concept of entropy in information theory, a new mathematic model for basic probabil-ity assignment function ( BPAF) is proposed;the results of the simulation show the model is ef-fective and the fusion algorithm is robust.