Kalman　filtering　is　known　as　an　effective　speech　enhancement　technique.　Many　Kalman　filtering　algorithms　for　single　channel　speech　enhancement　were　developed　in　past　decades.　However,　the　Kalman　filtering　algorithm　for　multichannel　speech　enhancement　is　very　less.　This　paper　proposes　a　Kalman　filtering　algorithm　for　distributed　multichannel　speech　enhancement　in　the　time　domain　under　colored　noise　environment.　Compared　with　conventional　algorithms　for　distributed　multichannel　speech　enhancement,　the　proposed　algorithm　has　lower　computational　complexity　and　requires　less　computational　resources.　Simulation　results　show　that　the　proposed　algorithm　is　superior　to　the　conventional　algorithms　for　distributed　multichannel　speech　enhancement　in　achieving　higher　noise　reduction,　less　signal　distortion　and　more　speech　intelligibility.　Moreover,　the　proposed　algorithm　has　a　faster　speed　than　several　multichannel　speech　enhancement　algorithms.　©　2017　Elsevier　B.V.