Cognitive Sparse Beamformer Design in Dynamic Environment via Regularized Switching Network

Wang, Xiangrong; Zhai, Weitong; Greco, Maria; Gini, Fulvio

doi:10.1109/taes.2022.3207706

Cited by 22 publications

(3 citation statements)

References 38 publications

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“…Thereafter, the PCE method is used and the RMSE and AR are calculated through (18) and (21) to quantitatively analyze the advantages of the proposed method. Finally, the real in-phase STEP 2: Calculate W opt according to (14).…”

Section: Resultsmentioning

confidence: 99%

“…However, some researches have shown that the adjacent reflectivity in extreme weather targets varies dramatically and the gradient often ranges from 30 to 40 dBZ within 1 km, sometimes even reaching 55 dBZ/km [12][13][14]. In order to realize the detection of weather targets with high gradient-reflectivity phenomenon, a very effective sidelobe suppression strategy must be adopted to avoid the artifact caused by range sidelobes [15], while the sidelobe performances of NLFM waveform are not enough to meet the accuracy of the quantitative detection of distributed scatterers, and the sidelobe needs to be further suppressed.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Optimization Strategy of Sidelobe Suppression for Pulse Compression Weather Radar

Dong

Tian

et al. 2023

Remote Sensing

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The solid-state transmitters are widely adopted for weather radars, where pulse compression is operated to provide the required sensitivity and range resolution. Therefore, effective sidelobe suppression strategies must be employed, especially for weather observation. Currently, many methods can suppress the sidelobe to a very low level in the case of point targets or uniformly distributed targets. However, in strong convection weather process, the weather echo amplitude lies in a wide dynamic range and the main lobe of weak target is prone to being contaminated by the sidelobe of strong target, causing the degradation of weather fundamental data estimation, even generating artifacts and affecting the quantitative precipitation evaluation. In this paper, we propose a novel strategy which is the further processing of a general pulse compression radar to mitigate the effects of sidelobes. The proposed method is called the predominant component extraction (PCE), in which the re-weighting processing is operated after pulse compression, and then the echo of each bin is optimized and its energy will approach the real targets in each bin. It can improve the estimation of weak signals or even eliminate the artifact at the edge of the scene. Numerical simulation experiments and real-data verifications are implemented to validate the feasibility and superiority. It is noted that the proposed method has no requirement on the transmitted waveform and can be realized only by adding a step after pulse compression in the actual system.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Optimization Strategy of Sidelobe Suppression for Pulse Compression Weather Radar

Dong

Tian

et al. 2023

Remote Sensing

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show abstract

“…Spectrum sensing that simultaneously estimates direction-of-arrival (DOA) and frequency spectrum is an important subject in signal processing [1][2][3][4][5]. The combination of angle and frequency spectrum estimation results is beneficial to radar and communication equipment for target detection or data transmission [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Joint Angle and Frequency Spectrum Estimation Algorithm Using Difference Coarray

Gao

et al. 2023

Electronics

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The spectrum sensing that jointly estimates direction-of-arrival (DOA) and frequency spectrum is an important issue for cognitive radio. Existing off-grid DOA estimation algorithms using difference coarray require a large number of snapshots to guarantee the estimation accuracy. Meanwhile, inaccurate DOA estimation renders inaccurate frequency spectrum estimation due to coupled estimation process. In order to overcome these disadvantages, we propose a joint angle and frequency spectrum estimation algorithm using difference coarray in this work. The proposed algorithm first transforms the received signal into the coarray domain and then adopts an “estimate and subtract” method to separate multiple signals. Subsequently, the DOA estimate of each source is corrected iteratively based on the proposed simple interpolation method. Finally, the frequency spectra are obtained by estimating the frequency response matrix based on the previous estimated DOAs. The shortage of requiring a large number of snapshots are overcome by utilizing the deterministically orthogonal signal model in which the signals are completely uncorrelated. Simulation results demonstrate the effectiveness of the proposed algorithm for off-grid DOA and frequency spectrum estimation using difference coarray with few snapshots.

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Joint optimization of FDA-MIMO antenna selection and frequency offset to maximize SINR

Liu¹,

Wang²,

Gong³

et al. 2023

Digital Signal Processing

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Cognitive Sparse Beamformer Design in Dynamic Environment via Regularized Switching Network

Cited by 22 publications

References 38 publications

A Novel Optimization Strategy of Sidelobe Suppression for Pulse Compression Weather Radar

A Novel Optimization Strategy of Sidelobe Suppression for Pulse Compression Weather Radar

A Joint Angle and Frequency Spectrum Estimation Algorithm Using Difference Coarray

Joint optimization of FDA-MIMO antenna selection and frequency offset to maximize SINR

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