Robust Beamforming Based on Covariance Matrix Reconstruction in FDA-MIMO Radar to Suppress Deceptive Jamming

Wan, Fuhai; Xu, Jingwei; Zhang, Zhenrong

doi:10.3390/s22041479

Cited by 12 publications

(7 citation statements)

References 42 publications

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“…Compared with conventional phased array (PA), FDA possesses an additional degrees-of-freedom (DOFs) in range dimension, thereby substantially enhancing the flexibility of array beamforming [ 2 , 3 , 4 ]. Specifically, FDA can provide potential superiority in precise target location [ 5 , 6 ], and range-dependent anti-jamming [ 7 , 8 ] over conventional PA which can only perform the beamforming in an angle dimension [ 9 ]. At present, enormous investigations have been conducted on the potential applications of FDA [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

Huang

Wang

2023

Sensors

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Unlike conventional phased array (PA), frequency diversity array (FDA) can perform the beampattern synthesis not only in an angle dimension but also in a range dimension by introducing an additional frequency offset (FO) across the array aperture, thus greatly enhancing the beamforming flexibility of an array antenna. Nevertheless, an FDA with uniform inter-element spacing that consists of a huge number of elements is required when a high resolution is needed, which results in a high cost. To substantially reduce the cost while almost maintaining the antenna resolution, it is important to conduct a sparse synthesis of FDA. Under these circumstances, this paper investigated the transmit–receive beamforming of a sparse-fda in range and angle dimensions. In particular, the joint transmit–receive signal formula was first derived and analyzed to resolve the inherent time-varying characteristics of FDA based on a cost-effective signal processing diagram. In the sequel, the GA-based low sidelobe level (SLL) transmit–receive beamforming of the sparse-fda was proposed to generate a focused main lobe in a range-angle space, where the array element positions were incorporated into the optimization problem. Numerical results showed that 50% of the elements can be saved for the two linear FDAs with sinusoidally and logarithmically varying frequency offsets, respectively termed as sin-FO linear-FDA and log-FO linear-FDA, with only a less than 1 dB increment in SLL. The resultant SLLs are below −9.6 dB, and −12.9 dB for these two linear FDAs, respectively.

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Section: Introductionmentioning

confidence: 99%

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

Huang

Wang

2023

Sensors

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“…Wan proposed an anti-jamming robust adaptive beamforming algorithm in FDA-MIMO radar. This algorithm utilizes covariance matrix reconstruction and spatial power spectrum estimation methods to improve the estimation accuracy of the signal covariance matrix and the desired target steering vector, thus calculating the optimal weights vector for the adaptive beamformer [22]. Liu proposed a transmit beamforming model for a dual-function multiple-input-multiple-output (MIMO) radar and a multiuser MIMO communication transmitter, which provided more degrees of freedom for MIMO radar and was, thus, able to obtain improved performance [23].…”

Section: Introductionmentioning

confidence: 99%

A Software-Defined Radar for Low-Altitude Slow-Moving Small Targets Detection Using Transmit Beam Control

et al. 2023

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Low-altitude slow-moving small (LSS) targets are defined as flying at altitudes less than 1000 m with speeds less than 55 m/s and a radar crossing-section (RCS) less than 2 m2. The detection performance of ground-based radar using the LSS target detection technique can be significantly deteriorated by the diversity of LSS targets, background clutter, and the occurrence of false alarms caused by multipath interference. To address the LSS target detection problem, we have devised a novel two-dimensional electronic scanning active phased array radar system that is implemented in the software-defined radar architecture and propose a transmit beam control algorithm based on the low peak-to-average ratio (PAPR). Meanwhile, we devised a flexible arbitrary radar waveform generator to adapt to complex environmental situations. Field experiment results effectively demonstrate that our radar can be used to detect LSS targets. Moreover, an ablation experiment was conducted to verify the role played by transmit beam control and adaptive waveform optimization and generation in improving the system performance.

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“…Adaptive beamforming [ 1 , 2 , 3 ] is widely used for anti-jamming in wireless communications, which suppresses interferences by forming array beam nulls in the directions of the interferers. The power inversion (PI) algorithm [ 4 , 5 , 6 ] is one of the known adaptive beamforming algorithms that has been found to have abundant applications in wireless communication and navigation systems.…”

Section: Introductionmentioning

confidence: 99%

Impacts of Phase Noise on the Anti-Jamming Performance of Power Inversion Algorithm

Zhou

Wang

et al. 2022

Sensors

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Power inversion (PI) is a known adaptive beamforming algorithm that is widely used in wireless communication systems for anti-jamming purposes. The PI algorithm is typically implemented in a digital domain, which requires the radio-frequency signals to be down-converted into base-band signals, and then sampled by ADCs. In practice, the down-conversion circuit will introduce phase noises into the base-band signals, which may degrade the performance of the algorithm. At present, the impacts of phase noise on the PI algorithm have not been studied, according to the open literature, which is, however, important for practical design. Therefore, in this paper, we present a theoretical analysis on the impacts, provide a new mathematical model of the PI algorithm, and offer a closed-form formula of the interference cancellation ratio (ICR) to quantify the relations between the algorithm performance and the phase noise level, as well as the number of auxiliary antennas. We find that the ICR in decibel decreases logarithmically linearly with the phase noise variance. In addition, the ICR improves with an increasing number of auxiliary antennas, but the increment is upper-bounded. The above findings are verified with both simulated and measured phase noise data.

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Robust Beamforming Based on Covariance Matrix Reconstruction in FDA-MIMO Radar to Suppress Deceptive Jamming

Cited by 12 publications

References 42 publications

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

A Software-Defined Radar for Low-Altitude Slow-Moving Small Targets Detection Using Transmit Beam Control

Impacts of Phase Noise on the Anti-Jamming Performance of Power Inversion Algorithm

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