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MST-ID Algorithm for Angular Parameter Estimation of Incoherently Distributed Sources

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Abstract

This paper presents an effective angular parameter estimation method based on the manifold separation technique (MST) for incoherently distributed sources, named as MST-ID algorithm. In the proposed method, at first, a mathematical model is established through the first-order Taylor expansion of the steering vector, in which the nominal direction of arrival (DOA) can be decoupled from the angular spread. Then, the decoupled steering vector is divided into two sub-steering vectors with equal dimensions, and further the nominal DOA is estimated by the shift invariant structure between the sub-steering vectors. Finally, the MST is used to separate the antenna array structure from the nominal DOA in the array steering vector, such that the signal covariance matrix can be easily obtained according to the antenna array structure and the estimated nominal DOA. On this basis, a spectrum search function is given to estimate the angular spread. Compared with the previous works, the presented method can not only improve the angular parameter estimation accuracy but also be suitable for arbitrary line array structures. Theoretical analysis and simulation results confirm the effectiveness of the proposed method.

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References

  1. F. Belloni, A. Richter, V. Koivunen, DOA estimation via manifold separation for arbitrary array structures. IEEE Trans. Signal Process. 55(10), 4800–4810 (2007)

    Article  MathSciNet  Google Scholar 

  2. R.Z. Cao, F. Gao, X.F. Zhang, An angular parameter estimation method for incoherently distributed sources via generalized shift invariance. IEEE Trans. Signal Process. 64(17), 4493–4503 (2016)

    Article  MathSciNet  Google Scholar 

  3. Q. Gu, H. Wang, W. Sun, T. Wu, Y. Xu, A sequential ESPRIT algorithm based on a novel UCSA configuration for parametric estimation of two-dimensional incoherently distributed source. IEEE Trans. Veh. Technol. 70(1), 356–370 (2021)

    Article  Google Scholar 

  4. A. Hassanien, S. Shahbazpanahi, A.B. Gershman, A generalized capon estimator for localization of multiple spread sources. IEEE Trans. Signal Process. 52(1), 280–283 (2004)

    Article  MathSciNet  Google Scholar 

  5. Y.L. Ju, Z.W. Liu, Y.G. Xu, A Nyström-based method for incoherently distributed source localization, in International Conference on Computer and Communication Systems pp. 618–622 (2020)

  6. J. Li, F.J. Chen, Y.D. Wang, C. Pascal, F. Ji, H. Yu, Spatial spectrum estimation of incoherently distributed sources based on low-rank matrix recovery. IEEE Trans. Veh. Technol. 69(6), 6333–6347 (2020)

    Article  Google Scholar 

  7. Y. Liu, H. Chen, Q. Wang, W. Liu, G. Wang, Noncircularity-based generalized shift invariance for estimation of angular parameters of incoherently distributed sources. Signal Process. 183, 107989 (2021)

    Article  Google Scholar 

  8. Y. Meng, P. Stoica, K.M. Wong, Estimation of the directions of arrival of spatially dispersed signals in array processing. Proc. Inst. Elect. Eng. Radar Sonar Navig. 143, 1–9 (1996)

    Article  Google Scholar 

  9. R. Roy, T. Kailath, ESPRIT - estimation of signal parameters via rotational invariance techniques. IEEE Trans. Acoust., Speech, Signal Process. 37(7), 984–995 (1989)

    Article  Google Scholar 

  10. R. Schmidt, R.O. Schmidt, Multiple emitter location and signal parameters estimation. IEEE Trans. Antennas Propag. 34(3), 276–280 (1986)

    Article  Google Scholar 

  11. S. Shahbazpanahi, S. Valaee, A.B. Gershman, A covariance fitting approach to parametric localization of multiple incoherently distributed sources. IEEE Trans. Signal Process. 52(3), 592–600 (2004)

    Article  MathSciNet  Google Scholar 

  12. S. Shahbazpanahi, S. Valaee, M. Bastani, Distributed source localization using esprit algorithm. IEEE Trans. Signal Process. 49(10), 2169–2178 (2001)

    Article  Google Scholar 

  13. L.W. Tian, C.Q. Xu, D. Chen, D. He, T. Truong, Enhancing mmWave DOA estimation by cumulative power gradient at low SNR. IEEE Signal Process. Lett. 27, 1974–1978 (2020)

    Article  Google Scholar 

  14. S. Valaee, B. Champagne, P. Kabal, Parametric localization of distributed sources. IEEE Trans. Signal Process. 43(9), 2144–2153 (1995)

    Article  Google Scholar 

  15. T. Wu, P. Zhang, DOA estimation for 2D incoherently distributed sources with nested array based on matrix reconstruction. Chinese Automation Congress (CAC). 4333–4336 (2020)

  16. X.M. Yang, G.J. Li, C.C. Ko, Z. Zheng, T.S. Yeo, Central DOA estimation of incoherently distributed noncircular sources with cross-correlation matrix. Circuits Syst. Signal Process. 34(11), 3697–3707 (2015)

    Article  MathSciNet  Google Scholar 

  17. Z. Zheng, G.J. Li, Fast DOA estimation of incoherently distributed sources by novel propagator. Multidimens. Syst. Signal Process. 24(3), 573–581 (2013)

    Article  Google Scholar 

  18. Z. Zheng, J. Lu, W.Q. Wang, H.F. Yang, S.S. Zhang, An efficient method for angular parameter estimation of incoherently distributed sources via beamspace shift invariance. Digital Signal Process. 83, 261–270 (2018)

    Article  Google Scholar 

  19. J. Zhuang, C. Duan, W. Wang, Z. Chen, Joint estimation of azimuth and elevation via manifold separation for arbitrary array structures. IEEE Trans. Veh. Technol. 67(7), 5585–5596 (2018)

    Google Scholar 

  20. Z. Zheng, W. Wang, H. Meng, H.C. So, H. Zhang, Efficient Beamspace-Based algorithm for Two-Dimensional DOA estimation of incoherently distributed sources in Massive MIMO systems. IEEE Trans. Veh. Technol. 67(12), 11776–11789 (2018)

    Article  Google Scholar 

  21. J. Zhuang, H. Xiong, W. Wang, Z. Chen, Application of manifold separation to parametric localization for incoherently distributed sources. IEEE Trans. Signal Process. 66(11), 2849–2860 (2018)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61971117) and by the Natural Science Foundation of Hebei Province (Grant No. F2020501007).

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Author notes

  1. Fulai Liu and Xiaodan Chen have contributed equally to this work.

Authors and Affiliations

  1. Institute of Engineering Optimization and Smart Antenna, Northeastern University, Qinhuangdao, 066004, Hebei, China

    Fulai Liu, Kai Tang, Xiaodan Chen, Ruiyan Du & Dongbao Qin

  2. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China

    Fulai Liu, Kai Tang, Xiaodan Chen, Ruiyan Du & Dongbao Qin

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  1. Fulai Liu
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  2. Kai Tang
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  3. Xiaodan Chen
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  4. Ruiyan Du
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  5. Dongbao Qin
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Correspondence to Fulai Liu, Kai Tang or Xiaodan Chen.

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Liu, F., Tang, K., Chen, X. et al. MST-ID Algorithm for Angular Parameter Estimation of Incoherently Distributed Sources. Circuits Syst Signal Process 41, 3798–3810 (2022). https://doi.org/10.1007/s00034-022-01953-4

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