【摘要】 针对多传感器的目标识别问题，文中给出并证明了两个传感器 Ｄｅｍ ｐｓｔｅｒ Ｓｈａｆｅｒ （ Ｄ Ｓ）融合识别同一目标时的若干结论及其归纳的结论，同时推出了多（＞ ２）传感器 Ｄｅｍ ｐｓｔｅｒ Ｓｈａｆｅｒ 融合识别同一目标时的递推式，并分析了它们的性质。这些研究是多传感器目标识别系统中不同类传感器的选择及其信息的有效 Ｄ Ｓ融合的理论依据，且融合识别的递推式不仅可减少计算的复杂度，增强多传感器分布识别的可调性，而且可用作多传感器实时融合识别的递推式，这对解决机器人及其军事等领域的目标识别问题有重要价值更多还原

【Abstract】 Several results of Dempster Shafer (D S) method applied to target fusion identification of two sensors and conclusions drawn from them were given and proved. The recurrence formula of multisensor (>2) D S fusion identification were derived and their properties were shown clearly. The study provides theoretical basis for selecting various sensors and effectively fusing information from them in multisensor target identification systems. Furthermore, the recurrence formula of fusion identification can reduce computational load, enhance adjustability of distributed multisensor identification systems, and they can be used in the case of real time. These results have great value for solve problem of robot and military target identification.更多还原