Reliable Data Aggregation in Internet of ViSAR Vehicles Using Chained Dual-Phase Adaptive Interpolation and Data Embedding
Mohammad R. Khosravi, Sadegh Samadi · IEEE Internet of Things Journal · 2019
Recently, the use of industrial synthetic aperture radar (SAR) sensors for unmanned aerial vehicles (UAVs) has received more attention. Despite the recent growth in the use of SAR, the connection bandwidth and the low data rate communications among networked UAVs in an Internet of Things (IoT) environment is a challenge, specifically, for exchanging big data such as remote sensing videos. To this end, we propose a lossless data aggregation technique to reduce redundant information of industrial sensing and embed managerial and control data. The proposed method uses reversible watermarking through a dual-phase interpolation-based embedding with a greedy network of weights, which can be updated under an unsupervised statistical procedure. Our method is reversible with respect to enhanced embedding capacity for reliable wireless payload communications. The simulation results on the benchmarks of video synthetic aperture radar confirm the theoretical analysis and demonstrate that the proposed approach outperforms the past works.