In this study, a signal fusion-based target detection algorithm for frequency diversity multiple-input-multiple-output radar in the presence of clutter and subspace interference is investigated. Remarkably, the propos...
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In this study, a signal fusion-based target detection algorithm for frequency diversity multiple-input-multiple-output radar in the presence of clutter and subspace interference is investigated. Remarkably, the proposed algorithm can not only ensure a unique solution for the involved optimisations but also get a good detection performance at a low communication cost. Furthermore, the proposed detector processes a constant false alarm rate with respect not only to the unknown spectral properties of the unstructured interference but also to the structured interference distribution. Simulation experiences in several scenarios indicate that the proposed algorithm has significant improvement in detection performance over conventional detection algorithms.
In this study, a constant false alarm rate (CFAR) decision scheme is devised for frequency diversity multiple-input-multiple-output (MIMO) radar. Under the assumption that there exists not only the unstructured distur...
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In this study, a constant false alarm rate (CFAR) decision scheme is devised for frequency diversity multiple-input-multiple-output (MIMO) radar. Under the assumption that there exists not only the unstructured disturbance but also the structured interference, a double threshold detector (DT-MGLRT) based on the modified generalised likelihood ratio test (MGLRT) algorithm is proposed, of which the first stage deals with the unknown parameters and the second stage determines the final decision. It is proved that the proposed detector possesses a CFAR with respect not only to the unknown spectral properties of the unstructured disturbance but also to the structured interference distribution. Finally, some experiment results indicate that the proposed detection algorithm has 2 dB signal-to-interference-plus-noise power ratio improvement on average in detection performance at a low computation and communication cost over conventional detection algorithms.
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