Low-observable nonlinear trajectory generation for unmanned air vehicles

Kathleen Misovec, Tamer Inanc, Jerry M. Wohletz, Richard M. Murray

2004 · 38 citations · 8 references

Concepts

TL;DR

Detection probability of an aircraft near radar depends on its attitude, range, and configuration. The paper explores low‑observability flight‑path planning for UAVs in the presence of radar detection systems. The authors couple a detection model to a simplified aircraft dynamics model and use Caltech’s NTG software, a gradient‑descent optimizer that blends B‑splines, output‑space collocation, and nonlinear optimization tools, with temporal constraints enabling alternating high‑ and low‑observability periods. The approach enables strategic avoidance of detection, and illustrative optimized low‑observability routes are presented.

Abstract

This paper explores low observability flight path planning of unmanned air vehicles (UAVs) in the presence of radar detection systems. The probability of detection model of an aircraft near an opponent radar depends on aircraft attitude, range, and configuration. A detection model is coupled with a simplified aircraft dynamics model. The nonlinear trajectory generation (NTG) software package developed at Caltech is used. The NTG algorithm is a gradient descent optimization method that combines three technologies: B-splines, output space collocation and nonlinear optimization tools. Implementations are formulated with temporal constraints that allow periods of high observability interspersed with periods of low observability. This feature can be used strategically to aid in avoiding detection by an opponent. Illustrative examples of optimized routes for low observability are presented.

References

8