Adaptive Detection of a Partly Known Signal Corrupted by Strong Interference

Albin Svensson, Andreas Jakobsson

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15 Citeringar (SciVal)

Sammanfattning

In this letter, we consider adaptive detection of a partly known signal corrupted by additive noise and strong interference with support that is only partly known. Assuming a homogeneous environment where the covariance matrix of the additive noise is the same for the primary and secondary data sets, although with the secondary data set also being affected by the interference, we allow for conic uncertainty models for both the signal and interference subspaces, developing a generalized likelihood ratio detector for the signal of interest. Numerical examples indicate that the proposed method offers a notable performance gain as compared to other recent related methods.
Originalspråkengelska
Sidor (från-till)729-732
TidskriftIEEE Signal Processing Letters
Volym18
Utgåva12
DOI
StatusPublished - 2011

Ämnesklassifikation (UKÄ)

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