Moving Target Detection With SNR Diversity for Distributed Coherent Aperture Radar on Moving Platforms

Distributed coherent aperture radar (DCAR) on moving platforms offers significant advantages of high mobility, long-range and high-power detection through coherent synthetic processing. However, radars may encounter signal-to-noise ratio (SNR) diversity issues in practice due to the variations in their locations, transmit powers, and time durations. Consequently, the detection performance of the DCAR can be severely degraded when the SNRs in each channel are different. Besides, the dynamic nature of platform motion poses challenges to coherent-on-receive detection due to the inconsistent Doppler frequencies across channels. In this paper, we consider the signal model incorporating the SNR diversity for DCAR on moving platforms. Subsequently, we propose two optimal channel weighting detection schemes for the moving target, including the weighted coherent-on-receive synthesis (W-CoRS) scheme and the weighted coherent-on-transmit/receive synthesis (W-CoT/RS) scheme, with both schemes aiming to maximize the output SNR. Notably, the two-stage W-CoRS scheme reduces communication costs by transmitting only weighted signals from each radar unit to the fusion center. Further, to optimize the detection performance, a high-precision coherent parameters (CPs) estimation algorithm based on the iterative Chirp-Z transform (ICZT) is proposed to address the off-grid issue of the Doppler frequency. At the same time, the proposed algorithm possesses the ability to accurately estimate the Doppler frequency offsets for each channel. Simulations demonstrate that the proposed schemes outperform the conventional DCAR (C-DCAR) in scenarios involving SNR diversity.