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This paper present a superresolution algorithm for forward-looking imaging of scanning radar based on weighted least squares method. This algorithm utilized the weighted vectors to structure the objective function, and introduced the diagonal loading technique to obtain more robust superresolution result. Simulation results verified the performance of our algorithm.
The high azimuth angular resolution problem of real-beam scanning radar is significant to targets detection and location. ML iterative adaptive approach(ML-IAA) has been used in array signal processing to realize high angular resolution. In order to improve the azimuth angular resolution of real-beam scanning radar, we introduce this algorithm to real-beam radar system, called real-beam ML iterative...
The traditional Richardson-Lucy (R-L) algorithm has a strong ability to realize super-resolution. However, it always suffers from noise amplification. In this paper, an improved R-L algorithm is proposed to solve the real-beam scanning radar angular super-resolution problem, which relies on both the traditional R-L deconvolution algorithm and the regularization term. We first describe the angular...
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