Anti-jitter Beamforming Design for UAV-Assisted Maritime Monitoring Networks

With the wide application of Internet of Things systems in the smart ocean, many unmanned surface vehicles (USVs) have been deployed jointly with unmanned aerial vehicles (UAVs) to monitor the maritime environment. However, conventional means of maritime communication prevent the UAV and the USV from providing high-rate services owing to complex maritime channel conditions and limited bandwidth, which will affect the maritime environment monitoring performance. In this paper, we propose a USV-UAV collaborative patrol scheme for maritime environment monitoring networks. Considering the characteristic of energy concentration in beamforming and the beam deviation caused by UAV jitter due to the harsh ocean condition, we studied an adaptive anti-jitter beamforming problem in UAV-assisted maritime environment monitoring networks. Specifically, we decompose the adaptive anti-jitter beamforming problem into two subproblems. In the first sub-problem, the location deployment of UAV and beam gain allocation is optimized via an iterative search algorithm based on ideal beamforming. In the second sub-problem, anti-jitter beamforming design is solved by an adaptive particle swarm optimization algorithm based on social learning, which effectively improves the average spectral efficiency of the system. Finally, the simulation results show that the proposed algorithm has good adaptability under different jitter amplitudes and effectively improves the spectral efficiency without increasing the complexity.