Guojun Jiang

Dr. Guojun Jiang


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2020 in IEEE Signal Processing Letters
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Journal Article
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GJGuojun Jiang
Guojun Jiang
XMXingpeng Mao
Xingpeng Mao
YLYong-Tan Liu
Yong-Tan Liu

29 December 2021 in IEEE Systems Journal
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Journal Article
Closed access
YYYunlong Yang
Yunlong Yang
GJGuojun Jiang
Guojun Jiang
To obtain a larger aperture for improving parameter estimation performance, we present a novel polarization sensitive array with dual-polarization synthetic nested structure, and then propose a low-complexity method for direction of arrival (DOA) and polarization estimation with two steps. There is a systematic procedure to determine the number and positions of antennas in each single-polarization subarray used for the synthetic nested array, in order to achieve more degrees of freedom (DOFs) and larger aperture for difference coarray with limited physical antennas. The increased DOFs of cross- and self-difference coarrays are quantitatively provided. To handle underdetermined parameter estimation with the resulting DOFs, the proposed method first estimates initial DOA and polarization state by using root-MUSIC and oblique projection operator, based on hole-free cross-difference coarray from cross-correlation matrix between subarrays. In the second step, holes in self-difference coarray, which is from autocorrelation matrix of single-polarization subarray, are filled with initial estimation. By exploiting both hole-free self- and cross-difference coarrays, an efficient search-based algorithm with initially estimated parameters is explored for refined estimation. The Cramér–Rao bound for the array and computational complexity of the method are provided. Simulation results are given to demonstrate the superior performance of the proposed array and method.

10 May 2024 in AEU - International Journal of Electronics and Communications
Verified
Journal Article
Closed access
GJGuojun Jiang
Guojun Jiang
JHJiacheng Huang
Jiacheng Huang
YYYunlong Yang
Yunlong Yang

5 November 2022 in Signal Processing
Verified
Journal Article
Closed access
GJGuojun Jiang
Guojun Jiang
YYYunlong Yang
Yunlong Yang

17 July 2024 in Electronics
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Journal Article
Open access
PDF file
JZJin Zeng
Jin Zeng
HXHang Xu
Hang Xu
ZSZerui Song
Zerui Song
JZJia-Le Zhou
Jia-Le Zhou
GJGuojun Jiang
Guojun Jiang
HWHui-Feng Wang
Hui-Feng Wang
Digital microfluidics is a novel technique for manipulating discrete droplets with the advantages of programmability, small device size, low cost, and easy integration. The development of droplet sensing methods advances the automation control of digital microfluidics. Impedance measurement emerges as a promising technique for droplet localization and characterization due to its non-invasive nature, high sensitivity, simplicity, and cost-effectiveness. However, traditional impedance measurement approaches in digital microfluidics based on the high-voltage actuating signal are limited in sensing accuracy in practical applications. In this paper, we propose a novel droplet impedance sensing system for digital microfluidics by introducing a low-voltage and addressable measurement circuit, which enables impedance measurement over a wide frequency range. The proposed measurement system has also been used for detecting the droplet composition, size, and position in a digital microfluidic chip. The improved impedance sensing method can also promote the applications of the digital microfluidic, which requires high accuracy, real-time, and contactless sensing with automatic sample pretreatment.

16 August 2024 in Remote Sensing
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Journal Article
Open access
PDF file
YYYunlong Yang
Yunlong Yang
MSMengru Shan
Mengru Shan
GJGuojun Jiang
Guojun Jiang
For target detection and recognition in a complicated electromagnetic environment, the two-dimensional direction-of-arrival and polarization estimation using a polarization-sensitive array has been receiving increased attention. To efficiently improve the performance of such multi-parameter estimation in practice, this paper proposes a parallel synthetic coprime array with reduced mutual coupling and hardware cost saving and then presents a dimension-reduction compressive sensing-based estimation method. For the proposed array, the polarization types, numbers, and positions of antennas in each subarray are jointly considered to effectively mitigate mutual coupling in the physical array domain and to both enhance degrees of freedom and extend the aperture in the difference coarray domain with the limited physical antennas. By exploring the array configuration, the parameter estimation can be formulated as a block-sparse signal reconstruction problem, and then the one-dimensional sparse reconstruction algorithm is only used once to achieve multi-parameter estimation with automatic pair-matching. The theoretical analysis and simulation results are provided to demonstrate the superior performance of the proposed array and method over the existing techniques.