Convex Optimization of Low Observability Hypersonic Vehicles

In this paper, we propose an approach to the conceptual design of high speed aerospace vehicles that addresses the coupled behavior of hypersonic aerodynamics and radar cross section. Our approach employs convex optimization, a branch of optimization theory that guarantees global optima for problems expressed with convex objective functions and constraints, combined with cubic splines as cross sectional representations. We demonstrate the process of creating convex surrogates using piecewise linear functions and apply these objective functions to useful test cases, employing a mixture of convex constraints on geometry. We also provide comparisons on the ability to converge to global optima between this type of convex optimization problem to a nonconvex, sequential quadratic programming solver.