Traditional passive radar detectors compute cross correlation of the raw data in the reference and surveillance channels. However, there is no optimality guarantee for this detector in the presence of a noisy reference. Here, we develop a new detector that utilizes a test statistic based on the cross correlation of the principal left singular vectors of the reference and surveillance signal-plus-noise matrices. This detector offers better performance by exploiting the inherent low-rank structure when the transmitted signals are a weighted periodic summation of several identical waveforms (amplitude and phase modulation), as is the case with commercial digital illuminators as well as noncooperative radar. We consider a scintillating target. We provide analytical detection performance guarantees establishing signal-to-noise ratio thresholds above which the proposed detection statistic reliably discriminates, in an asymptotic sense, the signal versus no-signal hypothesis. We validate these results using extensive numerical simulations. We demonstrate the “near constant false alarm rate (CFAR)” behavior of the proposed detector with respect to a fixed, SNR-independent threshold and contrast that with the need to adjust the detection threshold in an SNR-dependent manner to maintain CFAR for other detectors found in the literature. Extensions of the proposed detector for settings applicable to orthogonal frequency division multiplexing (OFDM), adaptive radar are discussed.


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    Titel :

    Passive Radar Detection With Noisy Reference Channel Using Principal Subspace Similarity


    Beteiligte:


    Erscheinungsdatum :

    2018-02-01


    Format / Umfang :

    2024264 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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