RMOCG: A Riemannian Manifold Optimization-Based Conjugate Gradient Method for Phase-Only Beamforming Synthesis

Zhong, Kai; Hu, Jinfeng; Cong, Yang; Cui, Guolong; Hu, H.

doi:10.1109/lawp.2022.3175963

Cited by 14 publications

(13 citation statements)

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“…For the convenience of subsequent calculation, before designing the phase-only weight vector, we define weight vector w to be a feasible solution to Problem (12) with the following form: w = wt ⊗ wr ,…”

Section: The Proposed Phase-only Weight Vector Design Modelmentioning

confidence: 99%

“…a t r j , θ j and b r θ j are the jth interference transmit and receive steering vectors, respectively. Compared to Problem (12), in Problem ( 14), variable w is replaced with wt and wr . Moreover, to maximize SINR, we expect the left side of (12c) to be as small as possible and set the left-hand side of Constraint (14c) equal to zero.…”

Section: The Proposed Phase-only Weight Vector Design Modelmentioning

confidence: 99%

“…Over the past few decades, numerous beamforming techniques have been investigated [7][8][9][10][11][12][13]. Conventional beamforming techniques require adjusting the amplitude and phase of the receive filter, resulting in higher hardware costs at the receiver.…”

Section: Introductionmentioning

confidence: 99%

“…Conventional beamforming techniques require adjusting the amplitude and phase of the receive filter, resulting in higher hardware costs at the receiver. Therefore, previous works have explored phase-only beamforming techniques for phased array radar [10][11][12][13], which utilize neural networks [10], numerical optimization [11], and other methods [12,13] to obtain phase-only weights. However, these techniques may be limited by computational complexity.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, this method [14] can only rapidly adjust the response at a single point and cannot simultaneously form deep nulls for multiple points. Moreover, it is worth noting that these techniques [7][8][9][10][11][12][13][14] primarily aim to create deep nulls in desired directions, but they are limited in their ability to create deep nulls at specific locations due to the angle-dependent beam pattern of phased array radar systems. From a practical point of view, it is possible to encounter interference signals that have similar angles as the target of interest [15,16].…”

Section: Introductionmentioning

confidence: 99%

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A Fast Phase-Only Beamforming Algorithm for FDA-MIMO Radar via Kronecker Decomposition

Chen,

Wang,

Gong

et al. 2024

Electronics

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This paper proposes a fast phase-only beamforming algorithm for frequency diverse array multiple-input multiple-output radar systems. Specifically, we use the Kronecker decomposition to decompose the desired phase-only weight vector into phase-only transmit and receive weight vectors and to decompose the target steering vector into transmit and receive steering vectors. By using the properties of the Kronecker product, the transmit and receive steering vectors and the transmit and receive weight vectors with the Vandermonde structure are decomposed into Kronecker factors with uni-modulus vectors, respectively. On this basis, in order to maintain the mainlobe gain and form a deep null at the desired position, the Kronecker factors are divided into two parts.The first component, referred to as the interference suppression factors, is responsible for creating deep nulls. The second component, known as the signal enhancement factor, maintains the mainlobe gain. We provide an analytical solution with low complexity for the Kronecker factors. This strategy can obtain the phase-only weights while effectively forming a deep null at the desired position. Numerical experiments are conducted to verify the effectiveness of the proposed algorithm.

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Section: The Proposed Phase-only Weight Vector Design Modelmentioning

confidence: 99%

Section: The Proposed Phase-only Weight Vector Design Modelmentioning

confidence: 99%