Abstract
In this article, we propose a space–time adaptive processing scheme via a generalized sidelobe canceler (GSC) architecture for airborne multiple-input multiple-output (MIMO) radar. This scheme employs the waveforms extracted by the matched filter bank that is cascaded at the receive end and utilizes digital beamforming technique to synthesize a certain number of transmit–receive beams, therefore, the operation of target detection in clutter environment can be conducted in all the directions of the formed beams in parallel. The GSC architecture is derived to implement adaptive reduced-rank (RR) clutter mitigation in a localized angle-Doppler space based on a novel RR multistage Wiener filter algorithm. The number of iterative stages in this algorithm is automatically selected in terms of a rank decision methodology. Meanwhile, beamforming and beam selecting methods are provided for this scheme, aiming at adaptively suppressing the clutter in localized domain. This scheme reverses the unavailability of the PA-efficient joint domain localized algorithm for MIMO radar. Moreover, it adapts to MIMO radar with arbitrary transmit–receive array space ratio. Even better, the proposed scheme has lower computation complexity than the traditional sample matrix inversion algorithm. The simulation results show that the proposed algorithm provide a signal-to-interference-plus-noise ratio improvement than traditional algorithms.
Highlights
Multiple-input multiple-output (MIMO) radar [1,2] has become an active area of radar research and application in recent years
MIMO radar is divided into two basic types: one is referred to as statistical MIMO radar in which the transmit/receive array elements are broadly spaced, providing independent scattering responses for each antenna pair; the other is referred to as coherent MIMO radar in which the transmit/receive array elements are closely spaced, assuming that the target is in the far field of the transmit–receive array
We exploit all the signals extracted by the matched filter (MF) bank to form a certain number of joint transmit–receive beams; the receiving data are projected into angleDoppler domain, clutter mitigation and target detection can be conducted in all the directions of the synthesized beams in parallel
Summary
Multiple-input multiple-output (MIMO) radar [1,2] has become an active area of radar research and application in recent years. In [12], the MIMO radar clutter subspace was reconstructed with orthogonal prolate spheroidal wave function by fully utilizing the geometry of MIMO radar It has lower computational complexity and formulates the data-independent clutter rank, it depends too much on the ideal case and is not robust to the clutter mismatch. We exploit all the signals extracted by the matched filter (MF) bank to form a certain number of joint transmit–receive beams; the receiving data are projected into angleDoppler domain, clutter mitigation and target detection can be conducted in all the directions of the synthesized beams in parallel This scheme has reversed the impracticability of the noted JDL algorithm when applied to MIMO radar, and adapts to MIMO radar with arbitrary ratio of transmit and receive element space.
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