The　RGBT　target　tracking　method　has　recently　gained　popularity　owing　to　the　complementarity　of　RGB　images　and　thermal　images　information.　Although　numerous　RGBT　tracking　methods　have　been　proposed,　effectively　utilizing　dual-modality　information　is　still　challenging.　To　solve　this　problem,　we　design　a　dual-modality　feature　extraction　network　to　extract　common　and　specific　modality　features.　For　specific　modality　features,　we　design　two　unique　feature　extraction　networks　to　learn　the　independent　dual-modality　information　respectively.　For　common　modality　features,　we　propose　a　common　feature　extraction　network　based　on　the　graph　attention　method,　which　could　learn　the　shared　modality　information　of　dual-modality　images.　According　to　experiments　on　the　RGBT234　and　LasHeR　datasets,　our　suggested　method　performs　sufficiently.　©　2022　ACM.