CAJ | 학술논문

针对无线传感器网络能量有限等特点，将路由策略考虑到投影矩阵的设计中，该文提出了基于数据融合树的压缩感知算法(Compressed Sensing algorithm based on Data Fusion Tree, CS-DFT)。该算法采用稀疏投影矩阵最小化通信消耗，在生成数据融合树的同时减小投影矩阵与稀疏基之间的相关度以保证数据的重构质量。仿真结果表明，该文提出的算法不仅在重构质量和能量消耗之间做到了很好的平衡，同时对于不同稀疏基下的数据也有较高的适应性。
침대무선전감기망락능량유한등특점，장로유책략고필도투영구진적설계중，해문제출료기우수거융합수적압축감지산법(Compressed Sensing algorithm based on Data Fusion Tree, CS-DFT)。해산법채용희소투영구진최소화통신소모，재생성수거융합수적동시감소투영구진여희소기지간적상관도이보증수거적중구질량。방진결과표명，해문제출적산법불부재중구질량화능량소모지간주도료흔호적평형，동시대우불동희소기하적수거야유교고적괄응성。
For the characteristic of energy-constrained in wireless sensor networks, considering routing strategy into the designing of the projection matrix, a Compressed Sensing algorithm based on Data Fusion Tree (CS-DFT) is proposed. It minimizes communication consumption by means of sparse random projection, and relevance between projection matrix and sparse basis is decreased in order to guarantee the data reconstruction quality while data fusion tree is generating. Simulation results show that, the proposed algorithm not only achieves a balance between reconstruction quality and energy consumption, but also has high adaptability to operate on a variety of data originated from different sparse basis.