高误码条件下线性分组码的盲识别

针对信息截获领域中线性分组码的盲识别问题，依据分组码的线性构造、校验性质及码重分布特征，提出了一种在信息熵高误码条件下基于矩阵秩信息熵与码重分布盲识别线性分组码的方法. 首先通过数据矩阵的秩信息熵识别出码长并由码重分布的信息熵函数准确计算出码字起始点，再根据系统与非系统线性分组码生成矩阵的特点，采用不同的计算方法正确求解生成矩阵，从而盲识别出线性分组码. 仿真结果表明，该盲识别方法在较高的误码条件下具有良好的识别效果.

Blind Recognition of Linear Block Codes under High Error Rate Condition

For blind recognition of binary linear block codes in information interception, with the linear structure and checkout properties of block codes and characteristic weight distribution, this paper proposes a method of blind recognition of linear block codes under a high bit error rate condition based on matrix rank and the information entropy function of the weight distribution. The method can recognize code length using the information entropy of rank and precisely compute codes start bit based on the information entropy function of the weight distribution. According to the characteristic of systematic or non-systematic linear block codes,the generator matrix is accurately obtained using different calculation methods, and blind recognition of linear block codes is achieved. Simulation results show that this blind recognition method has good performance in the case of high BER.