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This paper proposes a novel robust sparsity-based space-time adaptive processing (STAP) algorithm considering array gain/phase errors for airborne radar. The proposed algorithm builds the sparse signal model considering the array errors, formulates the sparse problem to jointly estimate clutter spatio-temporal profile and the array gain/phase errors, and then designs the space-time adaptive filter...
In this paper, we focus on sparsity-based space-time adaptive processing (STAP) in airborne radar with compressive sampling both in Doppler and spatial domains. Compared with the uniform pluses repetition Frequency (UPRF) and uniform arrays (UA) radar, the designed radar transmits random pulse repetition interval pulses and receives the returns with random arrays, which reduces the number of pulses...
This paper proposes a compressive space-time adaptive processing (CSTAP) airborne radar by reducing the samples in one coherence processing interval with random pulse repetition interval and random arrays, termed as the RPRI-RA radar. We firstly detail the compressive sampling in spatial and Doppler domain and develop a rule for the clutter rank estimation for the RPRI-RA radar. Then, CSTAP using...
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