Developing an Affordable Fighter for the Future

Stevens, Donald; Davis, Bruce; Stanley, William D.; Norton, Daniel M.; Starr, Stan; Raymer, Dan; Gibson, John; Hagen, Jeff; Liberson, Gary

doi:10.7249/rb35-1

Cited by 1 publication

(2 citation statements)

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“…This assumption comes from the fact 28,29 that, frequent maneuvers at different altitude levels introduce energy waste and may severely increase RCS value of LO UCAV and thus possibility of DTE by hostile radars; the mass of LO UCAV is taken as a constant value. Since typical penetration missions for LO UCAV are generally accomplished within a time less than 0.5 or 1 h 30 (this time is calculated when LO UCAV flies from penetration ingress to egress), the fuel burn during this time is relatively small in comparison with its empty weight. Besides of that, fuel burn is not considered in priority for military penetration.…”

Section: Adaptive Scheduling Paradigm and Modeling Of Real‐time Route...mentioning

confidence: 99%

“…The battlefield for penetration in this paper is a 400 by 400 km square area, which can cover typically horizontal range scenarios for LO UCAV to implement an “one‐way” penetration mission 30 . The ingress point, which is the position of LO UCAV first entering the battlefield, is selected at top of the lower‐left corner of this square region with altitude

z

as 30,000 m; its horizontal position values aligned with east and north are set to zero.…”

Section: Numerical Testsmentioning

confidence: 99%

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Real‐time route planning for low observable unmanned combat aerial vehicle

Yang

2024

Adv Control Appl

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The next generation of low observable (LO) unmanned combat aerial vehicle (UCAV) with highly autonomy to implement a penetration mission requires advanced methods for flyable and safe route planning (i.e., respecting physical capability of vehicle and threat coverage by hostile air defense radars) at a real‐time manner. Currently, the main challenge of real‐time route planning for LO UCAV is to achieve computationally efficiency under dynamic (pop‐up/moving) threats by air defense radars. In this paper, a real‐time planning paradigm in compliance with complex penetration requirements is proposed, and a complete modeling of route planning for LO UCAV's penetration as an optimal control problem is designed. The paper at first devises a direct method to transform the optimal control problem into a nonlinear programming (NLP) problem and then solves the formulated NLP problem under a moving planning horizon. The proposed method can give computationally efficient route planning results for LO UCAV's penetration under multiple kinds of radar threats. Numerical test results based on F‐16 uninhabited platform demonstrate the effectiveness of the proposed method.

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Section: Adaptive Scheduling Paradigm and Modeling Of Real‐time Route...mentioning

confidence: 99%