In　the　6G　environment,　addressing　the　challenges　of　data　loss　and　off-grid　issues　during　target　parameter　estimation　poses　a　significant　challenge　for　the　Integrated　Sensing　and　Communication　(ISAC)　system.　In　the　ISAC　framework,　a　commonly　used　method　for　parameter　estimation　is　compressive　sensing.　However,　compressive　sensing　may　encounter　off-grid　issues　in　continuous　parameter　estimation.　In　contrast,　the　atomic　norm　proves　effective　in　addressing　off-grid　problems,　making　it　more　suitable　for　continuous　parameter　estimation.　We　explore　the　application　of　the　atomic　norm　in　ISAC　and　further　derive　an　ISAC　model　based　on　OFDM　(Orthogonal　Frequency　Division　Multiplexing)　utilizing　the　atomic　norm　under　conditions　of　incomplete　data.　To　ensure　improved　convergence　speed　and　accuracy　of　our　algorithm,　we　employ　the　Alternating　Direction　Method　of　Multipliers　(ADMM)　for　iterative　implementation.　Experimental　results　demonstrate　that　our　proposed　AN　algorithm　accurately　estimates　target　parameters　in　the　presence　of　data　loss,　exhibiting　higher　precision　and　robustness　compared　to　traditional　methods.