Chaotic Secrecy Communication Key Technique Research

By using chaos' very high complexity and randomness, this thesis studies the theory of chaotic theory in communication and pay attention to the influence of interference in engineering use. This thesis uses chaotic code as PN code and transforms information by using compound chaotic parameters modulation. On one hand this method can encipher information, on the other hand compared with traditional chaotic parameters modulation, this method can transfer information when synchronism precision is low.First of all, directed against that traditional chaotic code can generate period peak in correlation because of limited precision. The thesis raises Serial-fabric chaotic code. By changing the second level chaotic system' s initial condition, the second level' s track will jump randomly. This method can increase the code' s period and improves the complexity. At the same time we find that this Serial-fabric chaotic code have more anti - interference ability than traditional chaotic code.Secondly most of the synchronism is based on the circumstance without noise, but if we want to use chaos in communication noise must to be taken into account. The thesis uses fuzzy neural network' s approach ability to prove that a fuzzy neural network with a finite rule number can optimally predict a chaotic system with noise. On the base of this theory this thesis proposes a T-SK Recurrent fuzzy network (TRFN). For the first time this paper uses the embedded dimensions of chaotic system to decide the number of input and uses Lyapunov functionto prove at what condition this network can constringency.Finally the thesis realizes the chaotic communication system' s digital pat. This system uses TMS320C6701 as processor. Dispatcher realizes chaotic parameters modulation, and receiver realizes chaotic synchronism and demodulation. The author uses FPGA to generate chaotic Spread-spectrum Sequence and despread..