This paper studies the collaborative unmanned aerial vehicle (UAV) sensing in integrated sensing and communication (ISAC) networks. By equipping sensing and communication units on UAVs, they can execute sensing tasks and transmit the sensing information to the base station (BS) for environment sensing. Due to the mobility and dense deployment of UAVs, they can sense the environment with much lower cost compared to the BS sensing. We aim to minimize the network sensing cost by optimizing the UAV deployment and task assignment collaboratively. For this joint optimization problem, we propose an iterative mechanism to optimize the UAV deployment and task assignment iteratively. UAV deployment problem is modeled as a cluster problem and we utilize a K-means cluster algorithm to solve it efficiently. For task assignment problem, we propose a greedy algorithm to solve it with low complexity. Simulation results validate the effectiveness of our proposed method in different scenarios.
In this paper, a novel method of heterologous image registration method based on feature inertial following is proposed, which can perform high-precision and rapid registration of SAR image and optical image. The first image pair in the sequence is registered based on improved SURF feature to achieve high-precision registration. Based on this registration result, the other image pairs in the sequence are registered by the method of feature inertia following to achieve rapid registration. The proposed method makes full use of the correlation and gradient properties between image sequence frames. It maintains the registration accuracy of the preceding images, improves the registration speed greatly.
With the advantage of fast imaging speed, video synthetic aperture radar (ViSAR) is able to monitor small targets in key areas continuously. W-band is relatively high band to realize video imaging, the Bragg scattering characteristics also create conditions for the imaging and detection of shadows for power lines. This paper reports the video imaging results of a small UAV-borne W-band SAR on power lines and analyzes the relationship to incident angles.
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