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- W2313367286 abstract "This work addresses the problem of adaptive multiple-input multiple-output (MIMO) radar detector in heterogeneous clutter. We first derive the generalized likelihood ratio test (GLRT) based on the two-step design procedure. Then, considering with the Bayesian framework and the prior knowledge about the clutter, we adopt the Maximum A Posteriori (MAP) estimator to the clutter covariance matrix and extend the knowledge-aided Bayesian technique to MIMO radar detection. Finally, various simulation results and comparison with respect to other conventional technique are presented to demonstrate the effectiveness of the knowledge aided Bayesian technique, especially in presence of a small amount of secondary data. (4 pages)" @default.
- W2313367286 created "2016-06-24" @default.
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- W2313367286 date "2012-01-01" @default.
- W2313367286 modified "2023-09-24" @default.
- W2313367286 title "Knowledge-aided Bayesian MIMO radar detector in heterogeneous clutter" @default.
- W2313367286 doi "https://doi.org/10.1049/cp.2012.1588" @default.
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