High-resolution imaging with uncertain radar measurement data: A doubly regularized compressive sensing experiment design approach

摘要

The descriptive experiment design regularization (DEDR) paradigm is aggregated with the variational analysis approach that combines the ℓ2 image metric with the ℓ1 sparse image gradient map metric structures in the solution space. The proposed ℓ2 − ℓ1 structured total variation DEDR (TV-DEDR) framework is particularly adapted for enhanced imaging with low resolution side looking airborne radar/fractional SAR sensors putting in a single optimization frame adaptive SAR image despeckling and resolution enhancement that exploits the structured desired image sparseness properties. The TV-DEDR method implemented in an implicit contractive mapping iterative fashion outperforms the competing nonparametric adaptive radar imaging techniques both in the resolution enhancement and computational complexity as verified in the simulations.