中文摘要：

为了解决无线传感器网络中数据采集过程中的冗余和传输能耗问题，深入分析信号的线性测量过程，提出一种用于压缩感知的测量矩阵设计方法。该方法结合对角矩阵和正交基线性表示原理，采用线性结构化的方法构造，过程简单、速度快、稀疏度高、没有冗余，适合硬件资源有限的传感器节点的实现。仿真结果表明，基于对角矩阵线性表示的测量方法与常见的高斯随机矩阵和部分哈达玛矩阵两种测量方法相比，该方法在相同信号重构精度前提下信号恢复成功率更高，传感节点可以通过压缩观测得到更少的测量数据，从而大大减少网络通信量，节约网络能耗，延长网络生存周期。

英文摘要：

In order to solve the problem of redundancy and transmission energy consumption in the process of data acquisition in wireless sensor networks, a method for designing the measurement matrix of compressive sensing was proposed in this paper. The method is based on the linear representation theory of diagonal matrix orthogonal basis and the process of constructing the matrix is simple with short time, high sparsity and low redundancy, which is very suitable for the nodes with limited hardware resources. The simulation results show the measurement method based on the linear representation theory of diagonal matrix gains higher signal recovery rate compared with Gauss random matrix and part Hadamard matrix under the same signal reconstruction accuracy. This method in the paper greatly reduces the traffic of networks, saves the network energy consumption and prolongs the network life cycle.