Nonlinear optimal model and solving algorithms for platform planning problem in battlefield

Platform planning is one of the important problems in the command and control(C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qualities. Firstly, we take into account the relation among tasks and build the single task nonlinear optimal model with a set of platform constraints. The Lagrange relaxation method and the pruning strategy are used to solve the model. Secondly, this paper presents optimization-based planning algorithms for efficiently allocating platforms to multiple tasks. To achieve the balance of the resource assignments among tasks, the m-best assignment algorithm and the pair-wise exchange(PWE)method are used to maximize multiple tasks completion qualities.Finally, a series of experiments are designed to verify the superiority and effectiveness of the proposed model and algorithms.

Trajectory Optimization for Cellular-Connected UAV Under Outage Duration Constraint

Enabling cellular access for unmanned aerial vehicles(UAVs)is a practically appealing solution to realize their high-quality communications with the ground for ensuring safe and efficient operations.In this paper,we study the trajectory design for a cellular-connected UAV that needs to fly from given initial to final locations,while communicating with the ground base stations(GBSs)subject to a minimum signal-to-noise ratio(SNR)requirement along its flight.However,due to various practical considerations such as GBSs’locations and coverage range as well as UAV’s trajectory and mobility constraints,the SNR target may not be met at certain time periods during the flight,each termed as an outage duration.In this paper,we first propose a general outage cost function in terms of outage durations in the flight,which includes the two commonly used metrics,namely total outage duration and maximum outage duration as special cases.Based on it,we formulate a UAV trajectory optimization problem to minimize its mission completion time,subject to a constraint on the maximum tolerable outage cost.To tackle this challenging(non-convex)optimization problem,we first transform it into a tractable form and thereby reveal some useful properties of the optimal trajectory solution.Based on these properties,we further simplify the problem and propose efficient algorithms to check its feasibility and obtain optimal as well as low-complexity suboptimal solutions for it by leveraging graph theory and convex optimization techniques.Numerical results show that our proposed trajectory designs outperform that by the conventional method of dynamic programming,in terms of both performance and complexity.