Optimizing Trajectory of Unmanned Aerial Vehicles for Efficient Data Acquisition: A Matrix Completion Approach

In this paper, unmanned aerial vehicles (UAVs) are used to efficiently collect information in an areas of interest. Based on the matrix completion, an optimal UAV data collection trajectory (OUDCT) scheme is proposed for improving energy efficiency and reducing redundant data by optimizing the trajectory of the UAV. With the proposed scheme, the backbone sampling points can be selected as follows. First, sampling points with higher degrees are selected as dominator sampling points. Second, sampling points with lower degrees are selected as virtual dominator sampling points to ensure that the information in all rows and columns is collected. Third, sampling points with lower degrees are selected as follower sampling points until the total number of selected sampling points satisfies the minimum requirement of the matrix completion. Thus, all the information in the monitoring area can be recovered by using the matrix completion. Finally, the optimal simulated annealing algorithm is used to plan the path of UAV based on the selected sampling points. The experimental results indicate that the performance of the OUDCT scheme is better than those in previous studies. Extensive simulation results are provided, which demonstrate that the OUDCT scheme can reduce data redundancy by 50%-52% and increase the lifetime by 17% compared with the random selection sampling points scheme.