The development of multimedia and deep learning technology bring new challenges to steganography and steganalysis techniques. Meanwhile, robust steganography, as a class of new techniques aiming to solve the problem of covert communication under lossy channels, has become a new research hotspot in the field of information hiding. To improve the communication reliability and efficiency for current real-time robust steganography methods, a concatenated code, composed of Syndrome-Trellis Codes (STC) and Cyclic Redundancy Check (CRC) codes, is proposed in this manuscript. Using its strong error detection capability, high coding efficiency and low embedding costs, an enhanced robust adaptive steganography framework and three adaptive steganographic methods resisting JPEG compression and detection are proposed. On this basis, to provide a theoretical reference for message extraction integrity, the fault tolerance of the proposed steganography methods is analyzed using the residual model of JPEG compression, thus obtaining the appropriate coding parameters. Experimental results show that the proposed methods have a significantly stronger robustness against compression, and are more difficult to be detected by statistical based steganalytic methods comparing with existing robust steganography methods.