It is difficult to distinguish the intensity between dim moving targets and background noise in the case of extremely Low Signal-to-Noise Ratio (LSNR). In order to solve the problem, a new extremely dim target search algorithm based on detection and tracking mutual iteration was proposed with a new strategy for combining and iterating the process of temporal domain detection and spatial domain tracking. Firstly, the difference between the signal segment in the detection window and the extracted background estimated feature was calculated during the detection process. Then, the dynamic programming algorithm was adopted to remain the trajectories with the largest trajectory energy accumulation in the tracking process. Finally, the threshold parameters of the detector of the remained trajectory were adaptively adjusted in the next detection process, so that the pixels in this trajectory were able to be retained to the next detection and tracking stage with a more tolerant strategy. Experimental results show that, the dim moving targets with SNR as low as 0 dB can be detected by the proposed algorithm, false alarm rate of 1% - 2% and detection rate of about 70%. It can be seen that the detection ability for dim targets with extremely LSNR can be improved effectively by the proposed algorithm.