Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (6): 1459-1465.doi: 10.13229/j.cnki.jdxbgxb20210010

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Beamspace ESPRIT for angle estimation in multiple⁃input multiple⁃output radar

Li-qin XU1,2(),Yong LI1,You-yao LIU2,Jian-guo ZHANG2   

  1. 1.School of Electronics and Information，Northwestern Polytechnical University，Xi'an 710072，China
    2.School of Electronic Engineering，Xi'an University of Posts and Telecommunications，Xi'an 710121，China
  • Received:2021-01-11 Online:2022-06-01 Published:2022-06-02

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Abstract:

In order to obtain better angle estimation performance at less cost， a beamspace conjugate ESPRIT algorithm for direction of arrival （DOA） estimation in multiple-input multiple-output （MIMO） radar is presented. Firstly， the reduced-dimensional transformation is utilized to transform the observed data into a lower-dimensional space. Then an augmented observation data matrix with double number of effective elements is constructed by taking advantage of the property of the noncircular signals and is mapped into beamspace. Finally， the rotational invariance property of the real-valued beamspace array manifold is constructed and exploited to find the directions of the targets. Compared to the conventional ESPRIT， the presented method can obtain greatly improved estimation performance and can achieve a significant reduction in the amount of computation. Numerical examples are presented to illustrate the performance of the presented algorithm.

Key words: multi-input multi-output radar, direction of arrival（DOA） estimation, rotational invariance techniques, non-circular signal

CLC Number: 

  • TN958

Table 1

Computational complexity comparison"

算法运算复杂度
ESPRITO(4M2N2L+4M3N3+8MNP2+12P3)
RD-CESPRITO(4Ne2L+4Ne3+8NeP2+12P3)
C-ESPRITO(16M2N2L+32M3N3+32MNP2+12P3)
RV-ESPRITO(4M2N2L+8M3N3+4MNP2+3P3)
本文O(4MeNbsL+2Nbs2L+Nbs3+2NbsP2+3P3)

Fig.1

Beamforming gain for differentnumbers of beams"

Fig.2

DOAs results in 100 trials"

Fig.3

RMSE versus the SNR"

Fig.4

RMSE versus the number of snapshots"

Fig.5

Resolution probability versus the SNR"

Fig.6

Computational complexity versusthe number of sensors"

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