Data matching and association based on the arc-segment difference method 后印本

摘要: In  response  to  the  issue  of  fuzzy  matching  and  association  when  optical  observation  data  are  matched  with the  orbital  elements  in  a  catalog  database,  this  paper  proposes  a  matching  and  association strategy  based  on  the  arcsegment  difference  method.  First,  a  matching  error  threshold  is  set  to  match  the  observation  data  with  the  known catalog  database.  Second,  the  matching  results  for  the  same day  are  sorted  on  the  basis  of  target  identity  and observation  residuals.  Different  matching  error  thresholds  and  arc-segment  dynamic  association  thresholds  are  then applied  to  categorize  the  observation residuals  of  the  same  target  across  different  arc-segments,  yielding  matching results  under  various  thresholds.  Finally,  the  orbital  residual  is  computed  through  orbit  determination  (OD),  and  the positional error  is  derived  by  comparing  the  OD  results  with  the  orbit  track  from  the  catalog  database.  The  appropriate matching  error  threshold  is  then  selected  on  the  basis  of  these  results,  leading  to  the  final matching  and  association  of the  fuzzy  correlation  data.  Experimental  results  showed  that  the  correct  matching  rate  for  data  arc-segments  is  92.34% when  the  matching  error  threshold  is  set  to  720″,  with the  arc-segment  difference  method  processing  the  results  of  an average  matching  rate  of  97.62%  within  8  days.  The  remaining  5.28%  of  the  fuzzy  correlation  data  are  correctly matched  and  associated, enabling  identification  of  orbital  maneuver  targets  through  further  processing  and  analysis. This  method  substantially  enhances  the  efficiency  and  accuracy  of  space  target  cataloging,  offering  robust technical support for dynamic maintenance of the space target database.