To address the problems as degradation of algorithm performance because the target is blocked by interference and confusion of target and interference in infrared target recognition,a new airborne infrared target recognition algorithm is proposed based on residual dense connection attention.Firstly,to fuse shallow and deep features across layers,obtain fusion depth features,enhance feature reuse performance and strengthen semantic information,an improved residual dense block is proposed.Secondly,to enhance the adaptive expression ability of the fused depth features,a parallel mixed attention block is designed.Finally,the test on a large quantity of infrared datasets shows that the algorithms average recognition accuracy is increased by 1.9 percentage points compared with that of the GoogLeNet algorithm,which proves the validity of the algorithm.