Bionic camouflage covert underwater acoustic communication has recently attracted great attention. However, we have not found relevant methods or literature to recognize these bionic camouflage communication signals (BCCSs) in the area of anti-reconnaissance. Focused on recognizing the BCCSs, this article proposes a recognition method based on the statistics of inter-click intervals to recognize the camouflaged click communication train (CCCT), which is modulated by time delay difference (TDD). We first analyze the characteristics of TDD distributions of CCCT and real click train (RCT). According to the coding principle, the TDDs of CCCTs present a ladder-like distribution with a fixed time step, and the TDDs are equal to the integral multiple of the fixed time step. On the contrary, the TDDs of RCTs are approximately random distribution within a certain time range. Therefore, based on the different TDD distributions, this article classifies CCCTs and RCTs by utilizing the statistical property of TDD distributions. To measure the TDDs of diverse cetacean clicks accurately, a new click location scheme based on the dynamic window energy ratio is proposed. Next, based on the statistics of TDD distribution, the influences of the TDDs that are caused by multipath interferences are eliminated by iteration. Simulations demonstrate the accuracy of the recognition method under different conditions.