To solve the difficult problem about fine association of tracks of various objects in a group under the system error, based on the characteristics of group tracks and in combination with an error estimation technology and a track association technology, the invention provides an error compensation-based group track fine association algorithm. The algorithm is characterized in that first, group identification is carried out on tracks obtained by various sensors based on a circulating threshold model, and overall pre-association is carried out on the group tracks based on a group center track, then, a pre-association group track most approximate to a resolution state is searched or established based on a group track state identification model, afterwards, the final error estimated value is obtained based on a group track system error model and an error confirmation model, and the error compensation is completed, and finally, fine association is carried out on the group tracks by utilizing a traditional track association algorithm. Compared with a fuzzy track alignment association algorithm based on unchanged-object information amount, a track alignment association algorithm based on track iteration and a corrected weighting method, the error compensation-based group track fine association algorithm provided by the invention has the advantages that the comprehensive performance is more excellent, and the requirements of engineering for precise association of tracks of objects in a group under the system error are well met.