CS-based data collection method for airborne clustering WSN

Abstract

A data acquisition scheme which was suitable for airborne clustering WSN was proposed.On the one hand,this scheme adopts the random compressive sampling could reduce the amount of sampling data of the cluster nodes ef-fectively,and greatly reducing the hardware requirements of the cluster nodes; on the other hand,put forward a MP re-construction method based on composite chaotic-genetic algorithm expressly,which combined the excellent local searching characteristics of chaos theory with the powerful global search ability of genetic algorithm,could improve the signal reconstruction performance of the cluster head or Sink effectively.The experimental results show that,by dimin-ishing the sampling frequency to 1/8 of the original sampling frequency,this random compressive sensing scheme can dramatically reduce the sampling quantity,and the reconstruction precision can reach 10-7magnitude.This random com-pressive sensing scheme provides a useful idea for practical WSN.

Keywords

• wireless sensor networks;compressive sensing;matching pursuit;reconstruction;genetic algorithm;chaos