BSDP: Big Sensor Data Preprocessing in Multi-Source Fusion Positioning System Using Compressive Sensing

A multi-source fusion positioning system (MFPS) adopts a data fusion technique for hybrid positioning. This technique fully utilizes several types of positioning sources in contrast to the conventional positioning methods, which use a single positioning source. Sensor data collection and processing are essential components in MFPSs. A framework for a practical center-server-based MFPS is proposed in this paper. A big sensor data preprocessing (BSDP) scheme, which is composed of data extraction (DE-BSDP), data gathering (DG-BSDP), and data transmission (DT-BSDP), is further proposed under this framework. DE-BSDP attempts to remove useless positioning data from fusion sources. The big sensor data are further compressed in DG-BSDP, in which a compressive sensing technique is adopted to realize data compression before data transmission. After the data gathering phase, the compressed data are transmitted to the fusion center for reconstruction in DT-BSDP. The proposed BSDP method can reduce the data collection amount significantly and improves the data transmission efficiency with a slight reduction on positioning accuracy. Experiments and simulations verify the effectiveness of the proposed BSDP scheme.