A Non-fuzzy Parameter Pairing Method Based on Estimating Signal Parameter via Rotational Invariance Techniques

JIE Yunkang; YE Xiaodong; WANG Hao; LI Li; TAO Shifei

doi:10.11999/JEIT210942

Volume 44 Issue 12

Dec. 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(12): 4144-4150

JIE Yunkang, YE Xiaodong, WANG Hao, LI Li, TAO Shifei. A Non-fuzzy Parameter Pairing Method Based on Estimating Signal Parameter via Rotational Invariance Techniques[J]. Journal of Electronics & Information Technology, 2022, 44(12): 4144-4150. doi: 10.11999/JEIT210942

Citation:

JIE Yunkang, YE Xiaodong, WANG Hao, LI Li, TAO Shifei. A Non-fuzzy Parameter Pairing Method Based on Estimating Signal Parameter via Rotational Invariance Techniques[J]. Journal of Electronics & Information Technology, 2022, 44(12): 4144-4150. doi: 10.11999/JEIT210942

Citation:

PDF( 3173 KB)

A Non-fuzzy Parameter Pairing Method Based on Estimating Signal Parameter via Rotational Invariance Techniques

doi: 10.11999/JEIT210942

School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

Funds: The National Natural Science Foundation of China (61701240), The Fundamental Reasearch Funds for the Central Universities (30918011317), The State Key Laboratory Foundation of CEMEE (CEMEE2022K0102B)

Received Date: 2021-09-06
Accepted Date: 2021-11-18
Rev Recd Date: 2021-11-15

Available Online: 2021-11-20

Publish Date: 2022-12-16

Abstract

Abstract

There are some mismatches for the estimation of signal parameters in mult-dimention Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT) algorithm. In this paper, a parameter pairing method based on eigenvalue fractal dimension is proposed. By linearly combining the eigenvalues and constructing a judgment matrix, the parameters are paired according to the corresponding relationship of matrix dimension. In contrast to other pairing algorithms, the proposed algorithm can achieve automatic pairing with low complexity, non-fuzzy parameters and higher robustness. Several examples are given to demonstrate the effectiveness of the proposed algorithm.
- Frequency estimation,
- Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT),
- Parameter pairing,
- Non-fuzzy

FullText(HTML)

References(20)

References

[1]	BOURI M. A novel fast high resolution MUSIC algorithm[C]. 2012 IEEE Workshop on Signal Processing Systems, Quebec City, Canada, 2012: 237–242.
[2]	王伟, 王晓萌, 李欣, 等. 基于MUSIC算法的L型阵列MIMO雷达降维DOA估计[J]. 电子与信息学报, 2014, 36(8): 1954–1959. doi: 10.3724/SP.J.1146.2013.01281 WANG Wei, WANG Xiaomeng, LI Xin, et al. Reduced-dimensional DOA estimation based on MUSIC algorithm in MIMO radar with L-shaped array[J]. Journal of Electronics &Information Technology, 2014, 36(8): 1954–1959. doi: 10.3724/SP.J.1146.2013.01281
[3]	姚昕彤, 王玉文, 刘奇, 等. 基于MUSIC及其改进算法的DOA估计研究[J]. 通信技术, 2021, 54(6): 1363–1369. doi: 10.3969/j.issn.1002-0802.2021.06.012 YAO Xintong, WANG Yuwen, LIU Qi, et al. Research on DOA estimation based on MUSIC and its improved algorithm[J]. Communications Technology, 2021, 54(6): 1363–1369. doi: 10.3969/j.issn.1002-0802.2021.06.012
[4]	ROUQUETTE S and NAJIM M. Estimation of frequencies and damping factors by two-dimensional ESPRIT type methods[J]. IEEE Transactions on Signal Processing, 2001, 49(1): 237–245. doi: 10.1109/78.890367
[5]	CHENG Qian. A simple modification of ESPRIT[J]. IEEE Signal Processing Letters, 2018, 25(8): 1256–1260. doi: 10.1109/LSP.2018.2851385
[6]	DONG Yangyang, DONG Chunxi, XU Jin, et al. Computationally efficient 2-D DOA estimation for L-shaped array with automatic pairing[J]. IEEE Antennas and Wireless Propagation Letters, 2016, 15: 1669–1672. doi: 10.1109/LAWP.2016.2521785
[7]	梁浩, 崔琛, 代林, 等. 基于ESPRIT算法的L型阵列MIMO雷达降维DOA估计[J]. 电子与信息学报, 2015, 37(8): 1828–1835. doi: 10.11999/JEIT141295 LIANG Hao, CUI Chen, DAI Lin, et al. Reduced-dimensional DOA estimation based on ESPRIT algorithm in MIMO radar with L-shaped array[J]. Journal of Electronics &Information Technology, 2015, 37(8): 1828–1835. doi: 10.11999/JEIT141295
[8]	张小宽, 郑舒予, 奚之飞, 等. 基于改进LS-ESPRIT算法的GTD模型参数估计与RCS重构[J]. 电子与信息学报, 2020, 42(10): 2493–2499. doi: 10.11999/JEIT190747 ZHANG Xiaokuan, ZHENG Shuyu, XI Zhifei, et al. GTD model parameters estimation and RCS reconstruction based on the improved LS-ESPRIT algorithm[J]. Journal of Electronics &Information Technology, 2020, 42(10): 2493–2499. doi: 10.11999/JEIT190747
[9]	HUA Y. Estimating two-dimensional frequencies by matrix enhancement and matrix pencil[J]. IEEE Transactions on Signal Processing, 1992, 40(9): 2267–2280. doi: 10.1109/78.157226
[10]	王秀, 常青, 王耀力. 基于L型阵列酉变换矩阵重构的二维DOA估计[J]. 电信科学, 2018, 34(7): 110–117. WANG Xiu, CHANG Qing, and WANG Yaoli. Two-dimensional DOA estimation of unitary transformation matrix reconstruction based on L-shaped array[J]. Telecommunications Science, 2018, 34(7): 110–117.
[11]	CHEN Weiyang, ZHANG Xiaofei, and JIANG Chi. Two-dimensional DOA estimation for planar array using a successive propagator method[J]. Journal of Circuits, Systems and Computers, 2019, 28(10): 1950161. doi: 10.1142/S0218126619501615
[12]	AHMED T and ZHANG Xiaofei. Higher-order unitary propagator method for 2D-DOA estimation of non-circular sources via uniform rectangular array[J]. Digital Signal Processing, 2020, 100: 102700. doi: 10.1016/j.dsp.2020.102700
[13]	CHEN Fangjiong, FUNG C C, KOK C W, et al. Estimation of two-dimensional frequencies using modified matrix pencil method[J]. IEEE Transactions on Signal Processing, 2007, 55(2): 718–724. doi: 10.1109/TSP.2006.885813
[14]	林俊发. 自动配对的二维矩阵束信号频率参数估计[J]. 电子元器件与信息技术, 2020, 4(7): 32–34,61. doi: 10.19772/j.cnki.2096-4455.2020.7.016 LIN Junfa. Two dimensional signal parameter estimation with automatic pairing by matrix pencil method[J]. Electronic Component and Information Technology, 2020, 4(7): 32–34,61. doi: 10.19772/j.cnki.2096-4455.2020.7.016
[15]	ZOLTOWSKI M D, HAARDT M, and MATHEWS C P. Closed-form 2-D angle estimation with rectangular arrays in element space or beamspace via unitary ESPRIT[J]. IEEE Transactions on Signal Processing, 1996, 44(2): 316–328. doi: 10.1109/78.485927
[16]	杨力强, 刘声, 杨力生, 等. 二维ESPRIT类算法中参数配对的新方法[J]. 无线电工程, 2014, 44(11): 23–25,33. doi: 10.3969/j.issn.1003-3106.2014.11.07 YANG Liqiang, LIU Sheng, YANG Lisheng, et al. A new parameter matching method for 2D ESPRIT algorithm[J]. Radio Engineering, 2014, 44(11): 23–25,33. doi: 10.3969/j.issn.1003-3106.2014.11.07
[17]	SAHNOUN S, USEVICH K, and COMON P. Multidimensional ESPRIT for damped and undamped signals: Algorithm, computations, and perturbation analysis[J]. IEEE Transactions on Signal Processing, 2017, 65(22): 5897–5910. doi: 10.1109/TSP.2017.2736512
[18]	ZHENG Shuyu, ZHANG Xiaokuan, ZHAO Weichen, et al. Parameter estimation of GTD model and RCS extrapolation based on a modified 3D-ESPRIT algorithm[J]. Journal of Systems Engineering and Electronics, 2020, 31(6): 1206–1215. doi: 10.23919/JSEE.2020.000065
[19]	GU Pengfei, HE Z, XU Juan, et al. Design of wide scanning sparse planar array using both matrix-pencil and space-mapping methods[J]. IEEE Antennas and Wireless Propagation Letters, 2021, 20(2): 140–144. doi: 10.1109/LAWP.2020.3039995
[20]	刘玲, 曾孝平, 曾浩. 基于奇异值的信源数估计方法[J]. 计算机工程, 2009, 35(12): 34–37. doi: 10.3969/j.issn.1000-3428.2009.12.012 LIU Ling, ZENG Xiaoping, and ZENG Hao. Signal source number estimation method based on singular value[J]. Computer Engineering, 2009, 35(12): 34–37. doi: 10.3969/j.issn.1000-3428.2009.12.012