When　partition-based　correlation　filtering　tracking　algorithm　is　applied　to　deal　with　scale　changes　and　target　occlusion　problems,　the　estimation　of　local　sub-block　state　tracking　and　the　relationship　between　local　sub-block　and　scale　change　are　inaccurate.To　address　this　issue,　a　scale-aware　partition-based　cooperative　correlation　filter　tracking　algorithm　is　proposed.　A　method　of　local　sub-block　occlusion　discrimination　based　on　time-sequence　smooth　constraint　is　adopted,　and　the　scoring　strategy　of　the　existing　algorithm　is　improved.　A　cooperative　motion　strategy　for　sub-blocks　is　then　designed　to　make　the　occluded　or　the　deformed　sub-blocks　follow　the　normal　ones　to　their　due　positions.　And　the　ratio　between　target　scale　and　distributed　location　of　sub-blocks　aggregation　and　dispersion　is　discovered　to　perceive　target　scale　changes　and　estimate　sizes.　Experiments　indicate　that　the　proposed　algorithm　achieves　better　performance.　©　2019,　Science　Press.　All　right　reserved.