Abstract
In this study, the effects of non-sidelooking airborne radar clutter dispersion on space-time adaptive processing (STAP) is considered, and an efficient adaptive angle-Doppler compensation (EAADC) approach is proposed to improve the clutter suppression performance. In order to reduce the computational complexity, the reduced-dimension sparse reconstruction (RDSR) technique is introduced into the angle-Doppler spectrum estimation to extract the required parameters for compensating the clutter spectral center misalignment. Simulation results to demonstrate the effectiveness of the proposed algorithm are presented.
Highlights
Space-time adaptive processing (STAP) [1,2] performs two-dimensional space and time adaptive filtering to suppress colored interferences such as clutter and jammer in airborne radars
The non-stationary nature of non-sidelooking array radars (SLAR) clutter limits the practical implementation of the standard space-time adaptive processing (STAP) approach, which relies for covariance estimation on secondary data obtained from adjacent range cells
We propose a novel approach to significantly reduce the complexity of the compensation parameter estimation used in AADC
Summary
Space-time adaptive processing (STAP) [1,2] performs two-dimensional space and time adaptive filtering to suppress colored interferences such as clutter and jammer in airborne radars. Compensation (AADC) algorithm, which is able to extract the compensating parameters from the data themselves, is fully adaptive and rather robust for both non-SLAR and bistatic STAP applications [8,9,10]. This technique is computationally costly in estimating the whole clutter angle-Doppler spectral trajectory with range. It is shown that the SC can be estimated with good accuracy from the data themselves This makes it possible to obtain an effective technique for non-SLAR STAP, which is fully adaptive and rather robust.
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