The utilization of sensing signals from multiple anchors for three-dimensional (3D) spatial localization represents one of the commonly employed wireless localization techniques for unmanned aerial vehicles (UAVs) in global navigation satellite system (GNSS)-denied environments, which has been extensively investigated. However, this methodology typically necessitates more than three anchors with distinct spatial distribution characteristics, coupled with precise alignment between the UAV local coordinate system and the global reference frame. These stringent requirements are often challenging to meet in practical operational scenarios. In this work, we explore an observable UAV 3D self positioning and orientation alignment of local coordinate system supported by only one angle of arrival (AoA) anchor, with significantly reduced implementation cost and complexity. We first proved the observability of designed positioning system with a static anchor which is the new theoretical limit supporting observable UAV positioning on minimal anchor number, and can significantly reduce the requirement for anchor number in practical positioning applications. Then, we develop an efficient two-layer iterative algorithm for the estimation problem which provides real-time positioning estimation with extremely low computing cost. Finally, numerical results confirm that the proposed scheme has high positioning accuracy and strong robustness to measurement noise.

In this paper, we study efficient trajectory and user assignment design for an unmanned aerial vehicle (UAV)-aided covert transmission against cooperative detection from multiple wardens, which is still an open issue in the literature. Starting with analysis on basic principles of cooperative detection, we derive the closed form expression of covertness metric under cooperative detection. Then a joint design of trajectory and user assignment is formulated to maximize the minimum throughput. Although the problem is highly nonconvex with infinite variables, we adopt the optimal successive-hover-and-fly (SHF) structure to reformulated the problem and reduce the complexity without loss of optimality. Then, an efficient algorithm is developed based on a convex approximation to obtain a high-quality solution. Finally, simulations verify the necessity of considering cooperative detection and the performance advantages of proposed design.

Unmanned aerial vehicle (UAV)-enabled communication is recognized as a promising technique in Internet of Vehicles (IoV) to address the issue of ineffective transmission of road condition data and driving instructions caused by obstruction and random fading of ground channels. However, the inherently open channel characteristics in UAV to ground links brings new secure and covert problem in vehicular IoV which largely limit the applications of UAV in IoV. To resolve the issue, this work studies a UAV-enabled covert autonomous vehicular communication network where a UAV is deployed as a relay aided by a jammer to assist the data transmission from the base station to an autonomous vehicle without being detected by a warden whose exact location is unknown. For network performance boosting with transmission covertness consideration, an upload throughput maximization problem is formulated by jointly designing UAV trajectory and resource allocation under a more generally joint covertness constraints. To solve the complicated and highly non-convex problem which contains a large number of variables, we first analyze the detection performance and derives the closed-form expressions of the warden’s minimal detection error probability considering the warden’s location uncertainty. Then, the characterizations on the convexity of minimal detection error probability and the optimal transmission rate are provided, which helps in simplifying original problem and developing an efficient iterative algorithm to solve this problem based on a proposed novel convex approximation method. Simulations are offered to demonstrate the superior convergence, throughput, computation time, and covertness performance of proposed scheme in UAV-enabled vehicular network.

In this paper, we study covert communications in an unmanned aerial vehicle (UAV)-enabled network, where a UAV transmits information to multiple ground users (GUs) without being detected by a hidden detector. Considering fairness issue, we aim at maximizing the minimum throughput among GUs by jointly optimizing the UAV’s trajectory, transmit power and power allocation coefficient, under UAV mobility and covertness constraints. On the one hand, according to the covertness constraint, the maximal transmit power is characterized as a close form expression of UAV’s position. On the other hand, the optimal UAV trajectory structure is characterized as a successive-hover-and-fly (SHF) structure. Following the two fundamental characterizations, we first transform the original problem to a joint trajectory and power allocation design one and then it is reformulated to another one addressing only a limited number of hovering points, corresponding hovering durations, turning points and allocation coefficient. Although being still non-convex, the new problem is efficiently solved via applying the sequential convex programming (SCP) method. Namely, by introducing a series of tight concave function in each iteration, we can solve a series of convex problems iteratively to make the trajectory converge to a high-quality solution. Numerical results confirm the convergence of our approach and show the high performance comparing with benchmark.

In this paper, we investigate an unmanned aerial vehicle (UAV)-enabled covert communication network with multiple ground users (GUs), a warden, and a UAV. The UAV carries directional antenna to communicate with GUs covertly, i.e., without being exposed to the warden. Focusing on task to improve the throughput of all GUs, we provide a joint user assignment and trajectory design aiming to maximize the throughput of GUs with worst condition. In particular, we consider the impact of directional antenna pattern on covertness performance, and derive the expression for maximum allowed transmit power satisfying the covertness and maximum transmit power requirement based on the modified antenna pattern. Following the characterization, the non-convex joint design problem is formulated. For making the highly non-convex problem analysable, we adopt two lemmas to construct the concave approximation function for the throughput which enables us to build up a convex problem. Accordingly, an effectively iterative algorithm is putting forward to settle the problem. Finally, numerical results confirm that our scheme with directional antenna outperforms the benchmarks.

In this paper, we study an unmanned aerial vehicle (UAV)-enabled covert communication network in which a UAV communicates to multiple ground users (GUs) without being detected by a ground detector. Considering the fairness, we aim at a joint UAV trajectory and transmit power design to maximize the minimum throughput among all GUs under constraints including mobility and covertness. By characterizing the covertness constraint, the joint design problem is transformed to a pure trajectory design which is still non-convex and with infinite number of variables. To address the problem, we adopt the optimal successive-hover-and-fly (SHF) trajectory structure to reformulate it to a new one with limited number of variables, and efficiently solve the reformulated problem via introducing a set of tight convex approximations to the problem and applying the successive convex approximation (SCA) method. Simulation results show the high performance with respect to covert communication throughput and the low complexity of proposed design in comparison to the benchmark.