Research Of A Compressive Sensing-Based Indoor Positioning And Tracking Algorithm Using RSS

Indoor localization is one of the key issues in wireless sensor networks.Locating an unknown node by some locating algorithm should consider the complex indoor environment.Exisiting indoor localization algorithms have many shortcomings,such as distance measurements are effected by complexity environment,low locating accuracy,high energy consumption etc.As the improvement of locating mechanisms and devices,indoor localization is widely applied in all kinds of occasions.Research on indoor localization is meaningful for energy ultilization and real-time locating in wireless sensor networks.Compressive sensing localization combined with Kalman filter can solve locating problems in complex indoor environment effectively.AS indoor compressive sensing based localization algorithm have poor locating accuracy and high energy consumption,the paper focuses on studying energy model of compressive sensing based indoor localization on the premise of better locating accuracy.In addition,the paper proposed the energy threshold of the localization.The main contributions of the paper are as follows:Traditional localization algorithm based on compressive sensing utilizes clustering and cluster matching algorithms in locating process.These make localization have high computing cost and low realtime performance.An energy efficient overlapping localization algorithm based on compressive sensing is proposed by the paper.Instead of using clustering and cluster matching approach,the paper uses a multi-region mechanism to select grids in overlapping region to construct measurement matrix for signal recover.The mechanism has a better realtime performance than traditional algorithm.Moreover,the proposed approach is proved to have lower energy consumption by energy model.Our simulation results show that the proposed approach can effectively reduce the influence of an indoor environment.Its performance outperforms the traditional CS and fingerprint methods on localization accuracy,stability,and energy consumption.Furthermore,as the introducing of overlapping mechanism,an energy confirmable tracking algorithm based on compressive sensing is proposed by the paper.Through the combination of compressive sensing localization and kalman filter,overlapping in every locating process and making the full use of the mobility of targets,the target region is minimized and the tracking accuracy is improved.Moreover,the paper proved that grids in overlapping region have a threshold value.And under a certain condition,energy consumption of the whole tracking is confirmable.Simulation results show that the algorithm have a good tracking performance with confirmable energy consumption.