Dandan Meng

599 total citations
22 papers, 482 citations indexed

About

Dandan Meng is a scholar working on Signal Processing, Aerospace Engineering and Control and Systems Engineering. According to data from OpenAlex, Dandan Meng has authored 22 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Signal Processing, 8 papers in Aerospace Engineering and 6 papers in Control and Systems Engineering. Recurrent topics in Dandan Meng's work include Direction-of-Arrival Estimation Techniques (14 papers), Speech and Audio Processing (6 papers) and Control Systems and Identification (6 papers). Dandan Meng is often cited by papers focused on Direction-of-Arrival Estimation Techniques (14 papers), Speech and Audio Processing (6 papers) and Control Systems and Identification (6 papers). Dandan Meng collaborates with scholars based in China, Singapore and Japan. Dandan Meng's co-authors include Xianpeng Wang, Feng Ding, Ahmed Alsaedi, Mengxing Huang, Tasawar Hayat, Xuebo Jin, Ling Xu, Liangtian Wan, Laurence T. Yang and Kaoru Ota and has published in prestigious journals such as IEEE Access, Journal of the Franklin Institute and IEEE Internet of Things Journal.

In The Last Decade

Dandan Meng

21 papers receiving 478 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dandan Meng China	10	172	153	138	108	106	22	482
Lujuan Dang China	13	132 0.8×	200 1.3×	102 0.7×	129 1.2×	271 2.6×	26	600
Hongxing Zou China	11	85 0.5×	93 0.6×	77 0.6×	234 2.2×	42 0.4×	36	510
Junyi Zuo China	12	179 1.0×	24 0.2×	110 0.8×	72 0.7×	210 2.0×	38	395
Dongliang Peng China	10	55 0.3×	44 0.3×	144 1.0×	74 0.7×	136 1.3×	92	409
Pyung Soo Kim South Korea	12	377 2.2×	53 0.3×	61 0.4×	96 0.9×	306 2.9×	49	641
Yong Fang China	12	55 0.3×	177 1.2×	60 0.4×	181 1.7×	32 0.3×	81	463
Tohid Ardeshiri Sweden	9	196 1.1×	26 0.2×	85 0.6×	68 0.6×	268 2.5×	22	413
Jun-Seok Lim South Korea	8	51 0.3×	113 0.7×	29 0.2×	132 1.2×	90 0.8×	54	342
Won‐Sang Ra South Korea	11	112 0.7×	23 0.2×	161 1.2×	127 1.2×	123 1.2×	61	369
R. Kumar United States	12	101 0.6×	68 0.4×	102 0.7×	143 1.3×	84 0.8×	63	422

Countries citing papers authored by Dandan Meng

Since Specialization

Citations

This map shows the geographic impact of Dandan Meng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dandan Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dandan Meng more than expected).

Fields of papers citing papers by Dandan Meng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dandan Meng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dandan Meng. The network helps show where Dandan Meng may publish in the future.

Co-authorship network of co-authors of Dandan Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Dandan Meng. A scholar is included among the top collaborators of Dandan Meng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dandan Meng. Dandan Meng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Meng, Dandan, et al.. (2025). Deep Learning-Driven DOA Estimation for Distributed Unmanned Systems: Overcoming Direction-Dependent Mutual Coupling Challenges. IEEE Internet of Things Journal. 1–1. 1 indexed citations

Wang, Xianpeng, et al.. (2025). Angle estimation based on coarray tensor completion for bistatic MIMO radar with sparse array. Signal Processing. 239. 110248–110248.

Meng, Dandan, et al.. (2024). DOA estimation of noncircular signals with direction-dependent mutual coupling. Signal Processing. 227. 109688–109688. 2 indexed citations

Meng, Dandan, et al.. (2024). Robust Tensor Decomposition Approach for DOA Estimation With EMVS-MIMO Radar. IEEE Sensors Journal. 24(19). 31262–31271. 1 indexed citations

Luo, Dan, et al.. (2020). Joint sparsity-inducing DOA estimation for strictly noncircular sources with unknown mutual coupling. 1 indexed citations

Meng, Dandan, et al.. (2020). DOA Estimation with Unknown Mutual Coupling for Monostatic MIMO Radar via Weighted Block Sparse Reconstruction. 190–192. 1 indexed citations

Meng, Dandan, Xianpeng Wang, Mengxing Huang, Liangtian Wan, & Bin Zhang. (2019). Robust Weighted Subspace Fitting for DOA Estimation via Block Sparse Recovery. IEEE Communications Letters. 24(3). 563–567. 52 indexed citations

Ding, Feng, Ling Xu, Dandan Meng, et al.. (2019). Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model. Journal of Computational and Applied Mathematics. 369. 112575–112575. 132 indexed citations

Meng, Dandan, Xianpeng Wang, Mengxing Huang, Chunjie Cao, & Kun Zhang. (2019). Block rank sparsity-aware DOA estimation with large-scale arrays in the presence of unknown mutual coupling. Digital Signal Processing. 94. 96–104. 4 indexed citations

10.

Meng, Dandan, et al.. (2018). Reweighted ‐norm minimisation for high‐resolution DOA estimation under unknown mutual coupling. Electronics Letters. 54(23). 1346–1348. 8 indexed citations

11.

Meng, Dandan, et al.. (2018). A Sparse Representation of Array Covariance Vectors for DOA Estimation with Unknown Mutual Coupling. 53. 1022–1026. 1 indexed citations

12.

Meng, Dandan, et al.. (2018). Weighted Block Sparse Recovery Algorithm for High Resolution DOA Estimation with Unknown Mutual Coupling. Electronics. 7(10). 217–217. 9 indexed citations

13.

Ding, Feng, et al.. (2018). Least Squares based Iterative Parameter Estimation Algorithm for Stochastic Dynamical Systems with ARMA Noise Using the Model Equivalence. International Journal of Control Automation and Systems. 16(2). 630–639. 45 indexed citations

14.

Wang, Xianpeng, Dandan Meng, Mengxing Huang, & Liangtian Wan. (2018). Reweighted Regularized Sparse Recovery for DOA Estimation With Unknown Mutual Coupling. IEEE Communications Letters. 23(2). 290–293. 46 indexed citations

15.

Meng, Dandan, et al.. (2018). Reweighted nuclear norm minimisation for DOA estimation with unknown mutual coupling. Electronics Letters. 55(6). 346–347. 4 indexed citations

16.

Meng, Dandan. (2016). Recursive Least Squares and Multi-innovation Gradient Estimation Algorithms for Bilinear Stochastic Systems. Circuits Systems and Signal Processing. 36(3). 1052–1065. 31 indexed citations

17.

Meng, Dandan & Feng Ding. (2016). Identification of stochastic systems with colored noise by the model equivalence theory. 5646–5651. 1 indexed citations

18.

Meng, Dandan & Feng Ding. (2015). Model Equivalence-Based Identification Algorithm for Equation-Error Systems with Colored Noise. Algorithms. 8(2). 280–291. 10 indexed citations

19.

Ding, Feng, Dandan Meng, & Qi Wang. (2015). The model equivalence based parameter estimation methods for Box–Jenkins systems. Journal of the Franklin Institute. 352(12). 5473–5485. 13 indexed citations

20.

Tian, Zhuang, Dongdong Weng, Jianying Hao, Yupeng Zhang, & Dandan Meng. (2013). A data driven BRDF model based on Gaussian process regression. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9042. 904211–904211. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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