Data-aided signal-to-noise-ratio estimation for scanning radar angular superresolution based on iterative adaptive approach

Most of ever proposed scanning radar angular superresolution algorithms are iterative, but the optimum iterations are difficult to determine. Since the performance of them is related to the signal to-noise ratio (SNR), an accurate SNR estimation would be of great significance to provide reference for assistance of adaptive iteration termination condition analysis. In this paper, a data-aided (DA) SNR estimation approach is developed. This scheme first utilizes the known antenna pattern and identity matrix to construct the steering matrix of signals and noise. Then we introduce the iterative adaptive approach (IAA) to estimate SNR. Simulation validates that this scheme, termed as IAA-SNR can present an adaptive and effective SNR estimation for scanning radar.