Grating-Lobe Clutter Suppression in Uniform Subarray for Airborne Radar STAP

Xue

et al. 2022

Remote Sensing

Due to clutter inhomogeneity, the clutter suppression ability of space–time adaptive processing (STAP) is usually constrained by the insufficient number of independent and identically distributed (IID) clutter training samples and, as a result, is sacrificed to achieve the demanded sample reduction. Moreover, since clutter heterogeneity is exacerbated in the real environment, the IID training sample size can be heavily reduced, leading to the deterioration in clutter suppression. To solve this problem, a novel robust space–time joint sparse processing method with airborne active array is proposed. This method has several outstanding advantages: (1) only the single snapshot cell under test (CUT) data is used for the superior clutter suppression performance; and (2) the proposed method completely removes the dependence of the system processing ability on IID training samples. In this paper, the signal model of uniform transmitting subarray diversity is first established to obtain the single snapshot echo observed CUT data. Then, with the matched reconstruction, the single snapshot data are equivalently converted into multi-frame echo data. Finally, a fast multi-frame echo data joint sparse Bayesian algorithm is used to achieve heterogeneous clutter suppression. Numerous experiments were performed to verify the advantages of the proposed method.

Section: Clutter Suppression Of Stapmentioning

confidence: 99%

“…However, the space-time coupling clutter problem cannot be solved effectively. For this purpose, a kind of space-time adaptive processing (STAP) technique has been proposed for clutter suppression [4][5][6]. In this technique, the space-time two-dimensional echo data are first obtained by different spatial channels and temporal pulses.…”

Section: Introductionmentioning

confidence: 99%

Robust Space–Time Joint Sparse Processing Method with Airborne Active Array for Severely Inhomogeneous Clutter Suppression

Xue

et al. 2022

Remote Sensing

“…The digital beam formation adjusts the weighting coefficient of each array according to certain criteria, so as to ensure the beam direction, so that the radar can set the zero point in the specified direction of the antenna pattern, and suppress the jamming signal in the process. In recent years, the researches on MVDR algorithm has been more abundant, such as the application of SAR [36], [37], spatial filtering [38]- [40], and estimation of beam arrival direction [41]. The MVDR algorithm is based on the principle of maximum output signal-to-noise ratio.…”

Section: Jamming Signal Suppressionmentioning

confidence: 99%

An Antideceptive Jamming Method for Multistatic Synthetic Aperture Radar Based on Collaborative Localization and Spatial Suppression

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Pei

et al. 2020

In recent years, the research of multistatic synthetic aperture radar (SAR) has become a hot spot because of its great potentials in military and civil applications. However, it is inevitably disturbed by electronic countermeasures. In the multistatic SAR image, the false target caused by transmitting deceptive jamming leads to misjudgment of the image information. In this article, a new antideceptive jamming method for multistatic SAR is proposed. This method can locate the deceptive jammer and effectively suppress it. First of all, the echo model of multistatic SAR in the jamming environment is set up. Based on this model, the relationship expression for the location of jammer is derived. Then, we use the maximally stable extremal region method and the Euclideandistance-based method to detect and identify false target in the multistatic SAR image. By using the location information of false target, receivers, and transmitters, the expression of the jammer localization is solved to locate the jammer. Finally, the minimum variance distortionless response beamforming method and image mosaic method are used to effectively suppress the jamming. The simulation results show that the method is effective.

“…For phased MIMO radar with equally overlapped subarrays, (39) is equivalent to (30) in [8] since transmit coherent gain of each subarray is equal. Then the sidelobe of overall beampattern in phased MIMO radar with equal subarrays is…”

Section: B Beampattern Analysismentioning

confidence: 99%

“…In fact, rather than changing the size and the number of sub-arrays [27], the investigation into the structure of subarray partition is not only possible but also necessary. Sparse subarray design divides array aperture into two or more subapertures for dual function radar communication system [28] or multi-task scenarios [29], achieving satisfactory SINR or Spatial Time Adaptive Processing(STAP) performances [30]. However, such partitions for Phased MIMO radar is not reported in the literature.…”

Section: Introductionmentioning

confidence: 99%

Hybrid MIMO Phased Array Radar With Center-Spanned Subarrays

2019

IEEE Access

Hybrid Multiple-Input-Multiple-Output(MIMO) phased array radar, or Phased MIMO radar, is recognized for its capacity to provide trade-off between transmit coherent gain and waveform diversity gain. Such trade-off can be flexibly implemented by changing subarray partition schemes of the system, which in turn enhances system performance. In this paper, a center-spanned subarray configuration is proposed with detailed steps to develop: First, the center element of the whole transmit array is chosen. Next, the surrounding region of center element is determined as the center subarray for subsequent spanning. Finally, the subarray partition is implemented through spanning subarrays around the center subarray. Both theoretical derivations and simulation results reveal that the hybrid MIMO phased array radar with the proposed center-spanned subarray configuration has lower sidelobe beampattern and higher Signal to Interference Noise Ratio(SINR) than that of equally or unequally overlapped subarray partitions. INDEX TERMS Beampattern, center-spanned sub-arrays, phased MIMO radar, SINR.