Year: 2024
Type: conference-paper
Abstract: In the face of increasingly sophisticated and diverse jamming technologies, the electromagnetic environment presents a growing threat to radars. Radars must continuously elevate their level of intelligence and anti-jamming capabilities to effectively counter the challenges posed by complex electromagnetic environments. The Multi Radar System (MRS) leverages the features of diverse radar architectures, enabling intelligent switching between them. It is capable of dynamically reconfiguring multiple sub-radar nodes to form distinct radar array configurations and possesses real-time situational awareness against enemy jamming. In this context, this paper delves into the study of a joint anti-jamming decision-making model for the MRS across the spatial-temporal-frequency, system, and mechanical domains, with a focus on a typical radar countermeasure scenario. An Anti-Jamming Bandit (AJB) algorithm is advanced to facilitate intelligent decision-making for the combination of anti-jamming actions across multiple domains. To address the issue of the rapid expansion of the anti-jamming strategy selection space following combination, a Pruned AJB (PAJB) algorithm is introduced, which is grounded in a pruning algorithm. This algorithm discards anti-jamming elements with inferior jamming suppression and retains those with superior returns, thereby condensing the space for anti-jamming strategy selection.
Authors: Shasha Shi, Qingsong Zhou, Shujie Shi, Jialong Qian
Institution: National University of Defense Technology
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407774122