限制等容性质(restricted isometry property,RIP)在压缩感知的理论研究中占据重要地位.然而,限制等容条件的验证却是一个复杂的组合优化问题.为了克服这一问题,本文将相干性理论引入非凸块稀疏压缩感知理论的研究,得到了块结构信号恢复的两类充分条件.所获结果将基于传统稀疏凸优化问题的相干性理论研究推广至了非凸块稀疏的情形.通过构造一类块相干系数较小的测量矩阵,非凸块稀疏压缩感知策略的有效性得到了数值实验的进一步验证. Restricted isometry property (RIP) occupies an important position in the theoretical research of compressive sensing.However, the verification of restricted isochronism is a complex combinatorial optimization problem.In order to overcome this problem, Two kinds of sufficient conditions for signal restoration of block structure are obtained by introducing the theory of non-bump sparsely compressed sensing. The obtained results extend the research of coherence theory based on the traditional sparse convex optimization problem to non-bump sparse case. By constructing The effectiveness of a non-bump-sparsely-compressed sensing strategy is further verified by numerical experiments for a class of measurement matrices with small coherence coefficients.