| Due to the high installed platform and strong maneuverability,airborne radar can solve these problems that the ground radar have limited visibility,easily to be blocked and prone to blind areas.However,ground clutter is widely distributed,and its intensity is large,and the airborne platforms' motion leads to the broadening of the clutter spectrum,which makes the targets easily to be submerged in the clutter.Therefore,the primary task of achieving target detection in airborne radar system is clutter suppression.For airborne radar system,space-time adaptive processing(STAP)is a crucial technology to realize clutter suppression and moving target detection.Most of the existing STAP algorithms are proposed for the conventional pulsed Doppler radar,which is under the assumption that Nyquist sampling is used in the spatialtemporal domain.However,the Nyquist sampling method will bring the following the problems: 1)It may lead to angle-Doppler ambiguity of the clutter and target,which has a terrible influence on moving target detection;2)Radar waveforms are regularly transmitted and easily intercepted,the capabilities of electronic counter-countermeasures(ECCM)is limited;3)For the high-band radars,two array elements with half-wavelength spacing can not to be installed,and there is a mutual effect between elements.This paper based on clutter suppression in airborne radar system,intended to solve the existing problems of STAP with Nyquist sampling,presents a clutter suppression technique for compressive STAP airborne radar with random pulse repetition frequency(RPRF)and random arrays(RA).The contents are as follows:1)Two different random compressive sampling modes for signal model has been proposed,which are random selected sampling and sparse sampling.Because of the random compressive sampling,the clutter rank estimation method for the conventional phased array radar is not suitable.In this paper,we present a clutter rank estimation method for airborne radar system with RPRF and RA.In addition,the design criterion of random compressive sampling from the two aspects of the clutter rank and the Restricted Isometry Property(RIP)is proposed.Finally,combined with the theoretical analysis and experimental results,the paper analyzes the ability of solving ambiguity of clutter or target in random compressive sampling airborne radar.2)In order to investigate the portability problem of the traditional STAP for airborne radar with random compressive sampling,the full-dimension and reduced-dimension STAP algorithm based on direct compressive sampling are studied.Simulation results show that the performance degradation of full-dimension STAP due to the numbers of degree of frees(DoFs)is decreased;the detection performance of slow speed target is improved,it provide cost saving by reducing the number of elements;the output performances of mDT-STAP and JDL-STAP degrade;to maintain a better output performance,we need to choose more Doppler channels and spatial beams to design the reduced-dimension matrix.3)Based-on the above random compressive sampling signal models,the signal models for spatial-temporal spectrum are established.Sparsity-aware STAP methods can achieve better spatial-temporal spectrum estimation under the condition of the low system DoFs,and have better clutter suppression performance under low training snapshots,the clutter suppression algorithm based on sparsity-aware STAP is studied in this paper.The experimental results show that the sparsity-aware STAP can improve the convergence performance of the airborne radar system,and has better detection performance of slow speed target.In summary,the clutter suppression technology for random compressive sampling airborne radar studied in this paper provides technical support for actual radar system design and clutter suppression and motion target detection. |
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