Multisensor distributed data fusion has many practical applications , and it is a focus in technological fields . this paper deals with multisensor distributed statistic decision and multisensor distributed estimation fusion . we get some results : in multisensor distributed statistic decision , we consider multisensor distributed neyman - pearson decision with correlated observation data and suggest an efficient algorithm to search for optimum local compression rules for any fixed fusion rule 本文在多傳感器分布式統計判決和多傳感器分布式估計融合方面進行了較為深入的研究,主要取得的成果為:在多傳感器分布式統計判決理論方面,對在相關觀測下,固定融合律的多傳感器分布式二元neyman - pearson判決,給出了最優分站壓縮律的不動點類的必要條件和相應的離散迭代算法,并討論了算法的收斂性。