In　this　study,　partial　registration　problem　with　outliers　and　missing　data　in　the　affine　case　is　discussed.　To　solve　this　problem,　a　novel　objective　function　is　proposed　based　on　bidirectional　distance　and　trimmed　strategy,　and　then　a　new　affine　trimmed　iterative　closest　point　algorithm　is　given.　First,　when　bidirectional　distance　measurement　is　applied,　the　ill-posed　partial　registration　problem　in　the　affine　case　is　prevented.　Second,　the　overlapping　percentage　is　solved　by　using　trimmed　strategy　which　uses　as　many　correct　overlapping　points　as　possible.　The　authors＇　method　computes　the　affine　transformation,　correspondence　and　overlapping　percentage　automatically　at　each　iterative　step.　In　this　way,　it　handles　partially　overlapping　registration　with　outliers　and　missing　data　in　the　affine　case　well.　Experimental　results　demonstrate　that　their　method　is　more　robust　and　precise　than　the　state-of-the-art　algorithms.　It　also　has　good　convergence　and　similar　running　time　with　traditional　algorithms.