To solve the problems of insufficient bimodal feature fusion and low quality of feature fusion in multispectral pedestrian detection, a multispectral pedestrian detection algorithm based on multistage cross information fusion is proposed. Firstly, the algorithm extracts the features of visible and infrared images through the dual stream backbone network; The cross information fusion module is designed and embedded in the dual stream backbone network in multiple stages to guide the bimodal feature fusion, so as to achieve full fusion of bimodal feature information; Conditional convolution is introduced to dynamically process the fused feature information to improve the quality of the fused information and ultimately improve the detection performance of the algorithm. Experimental results show that the missing rate of the algorithm is only 1041%, which is 10% lower than the original algorithm, and the detection performance of the algorithm is significantly improved.