Reduced rank detection algorithms for distributed array sensors

Distributed sensing systems provide an inherent spatial diversity by viewing a potential target from different aspect angles. Even though the centralized fully adapted processing scheme provides optimum performance, it is impractical for reasons of computational complexity and the sample support required for weight training. This paper presents two decentralized reduced rank STAP algorithms to overcome the drawbacks of centralized fully adapted processing.

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