1. Rx Beamforming for Long Baseline Multistatic Radar Networks
- Author
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Rudolf Hoffmann, Risto Vehmas, and Nadav Neuberger
- Subjects
Beamforming ,Estimation theory ,Phased array ,business.industry ,Computer science ,020208 electrical & electronic engineering ,Real-time computing ,020206 networking & telecommunications ,02 engineering and technology ,Bistatic radar ,Software ,0202 electrical engineering, electronic engineering, information engineering ,Multistatic radar ,Network performance ,business ,Baseline (configuration management) - Abstract
Distributed phased array radar networks provide an improved target detection and parameter estimation performance due to extended spatial coverage and multiple observation perspectives. By increasing a network’s baseline, these capabilities can be further enhanced. However, the spatial area that the Rx stations need to cover increases with growing baselines, requiring a high number of Rx beams. This poses a challenge, since the number of receiving channels is often limited by hardware or software. Therefore, designing the Rx beamformer is a key factor for baseline extension and network performance. In this paper, we analyze the use of two different beamformers for a bistatic network configuration: a commonly used sum beam method and a recently proposed eigenbeamformer. The numerical results demonstrate the superiority of the eigenbeamformer in parameter estimation accuracy, resource efficiency and baseline extension ability.
- Published
- 2021
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