基于StOMP算法的WSN压缩感知数据重构

WSN Compressed Sensing Data Reconstruction Based on StOMP Algorithm

分段正交匹配追踪算法(StOMP)运算速度快、计算量小,适用于无线传感器网络(WSN)压缩感知数据重构。为此,分析并研究StOMP算法的门限阈值选取对WSN压缩感知数据重构精度的影响,提出一种StOMP算法门限阈值的自适应调整方法。基于比例-积分-微分方法的思想,根据StOMP算法的当次重构误差计算门限阈值的调整值,并使用调整后的门限阈值重新进行数据重构,重复该过程以提高重构精度。实验结果表明,该方法能快速找到满足误差要求的门限阈值,与采用固定门限阈值的调整方法相比,重构精度更高。

Stagewise Orthogonal Matching Pursuit（ StOMP） algorithm has rapid computing speed and small amount of calculation quantity, and is thus highly suited to the reconstruction of Wireless Sensor Network（ WSN） Compressed Sensing（ CS） data. The influence of threshold selection of StOMP algorithm on the reconstruction accuracy of CS data in WSN is analyzed and studied. And this paper proposes an adaptive adjustment method of threshold value in the StOMP algorithm. Based on the idea of Proportional-Integral-Derivative（ PID） method,the adjustment value of the threshold is calculated according to the reconstruction error. Reconstruct the data with the new threshold, and this process is repeated to improve the accuracy of reconstruction. Experimental result shows that this method can quickly find the threshold value which meets the error requirement and has distinctly improved reconstruction precision compared with the adjustment method of fixed threshold value.