Multidimensional Systems and Signal Processing

, Volume 26, Issue 1, pp 159–178 | Cite as

Unitary dual-resolution ESPRIT for joint DOD and DOA estimation in bistatic MIMO radar

  • Guimei Zheng
  • Baixiao Chen


This paper investigates the problem of joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO radar. A new bistatic MIMO array, both the transmit array and the receive array consist of two separated subarrays with dual baselines is proposed, in contrast to the modeling of both the transmit array and the receive array to be uniform linear array in the existing research literature. And a new joint DOD and DOA estimation algorithm, called unitary dual-resolution ESPRIT, is proposed. First, the short baseline rotational invariance within subarray yields non-ambiguous coarse DOD and DOA estimation. Then the long baseline rotational invariance between subarray yields high accuracy but cyclically ambiguous DOD and DOA estimation. Last, the combination of both estimates yield high accuracy and non-ambiguous DOD and DOA estimation. Moreover, we propose to utilize the properties of centro-Hermitian matrices to transform the complex-valued computations into real-valued computations throughout the whole process. The proposed algorithm gives significant improvement in DOD and DOA estimation performance, with automatic pairing and without extra antennas and computational complexity compared with the conventional algorithms. Simulation results verify the effectiveness of the proposed algorithm.


Bistatic MIMO radar DOD estimation DOA estimation  Unitary ESPRIT Separated subarray 



The authors would like to thank the anonymous reviewers and the Editor for their valuable comments and suggestions, which have greatly improved the quality of this paper. This work is supported by National Natural Science Foundation of China (61001209, 61101244), Program for Changjiang Scholars and Innovative Research Team in University IRT0954 and the Fundamental research Funds for the Central Universities (K5051202038).


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.National Laboratory of Radar Signal ProcessingXidian UniversityXi’anChina

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