With the continuous advancement of underwater full-duplex communication technology, in the co-frequency simultaneous transmit-and-receive mode, high-power transmitter signals can easily couple into the receiver through multiple paths, generating strong self-interference (SI) that overwhelms the desired signal and significantly degrades communication quality. Particularly in complex underwater acoustic channels, this SI phenomenon becomes more severe, posing a critical bottleneck for improving the performance of underwater communication systems. Therefore, effective suppression of co-located self-interference has become a crucial technical challenge that must be addressed in underwater transceiver systems. To overcome the limitations of traditional digital-domain SI cancellation methods—where the least mean squares (LMS) algorithm suffers from insufficient estimation accuracy and the recursive least squares (RLS) algorithm exhibits high computational complexity—this paper proposes a digital-domain self-interference suppression method based on the stable fast transversal recursive least squares (SFTRLS) algorithm. By introducing forward and backward prediction structures, the proposed algorithm transforms the complex matrix operations in conventional RLS into one-dimensional vector operations, effectively reducing computational complexity from O(N2) to O(N). This approach significantly lowers computational overhead while maintaining excellent SI suppression performance. Extensive simulations under varying signal-to-noise ratios (SNRs) and channel orders demonstrate the proposed algorithm′s advantages in convergence speed, SI channel estimation accuracy, and computational efficiency. Furthermore, real-world lake experiments validate the method′s engineering feasibility. The results show that, under the given test conditions, the algorithm achieves an SI suppression ratio of up to 30 dB. Comparative evaluations with existing methods further confirm that the SFTRLS algorithm exhibits strong applicability and practical value in complex underwater environments. This research not only addresses a key technical challenge in underwater communications but also provides a valuable reference for self-interference suppression in other domains.