Cognitive Antenna Selection in MIMO Imaging Radar

Ding, Shanshan; Tong, Ningning; Zhang, Yongshun; Hu, Xiaowei; Zhao, Xiaopeng

doi:10.1109/tgrs.2020.3047610

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…The selection of the sparse antenna positions is a key technology widely used in MIMO radar systems [36,37]. Since the available antennas are placed in a wider transmit field, an additional DOF is introduced to the system.…”

Section: The Sparse Beampattern Matching Designmentioning

confidence: 99%

“…A greedy search method is developed in this subsection to optimize the problem in (36) efficiently. In the method, we first generate the feasible solutions set, and then we select the fittest solution.…”

Section: The Proposed Greedy Search Frameworkmentioning

confidence: 99%

“…According to the above discussion, the developed method for solving (36) is concluded in Algorithm 2.…”

Section: Updating the Solutionmentioning

confidence: 99%

See 2 more Smart Citations

MIMO Radar Transmit Waveform Design for Beampattern Matching via Complex Circle Optimization

Xiong

Zhong

et al. 2023

Remote Sensing

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In this paper, we study the multiple-input multiple-output (MIMO) radar transmit waveform design method for beampattern matching. The purpose is to design the beampattern to approximate the actual one and minimize the cross-correlation sidelobes under the constant modulus constraint (CMC). Due to the CMC, the problem is non-convex, and the existing methods solve it with relaxation, resulting in performance degradation. Different from these methods, we notice that the CMC is the product of complex circles (CC). Based on this physical characteristic, the direct beampattern matching without relaxation (DBMWR) method is proposed. To be specific, we first formulate the original problem as an unconstrained quartic problem over the CC and then solve it by the proposed method without relaxation. Simulation results show that the proposed method can achieve a balance in terms of accuracy and computation complexity compared with other methods.

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Section: The Sparse Beampattern Matching Designmentioning

confidence: 99%

Section: The Proposed Greedy Search Frameworkmentioning

confidence: 99%