Reduced-Dimension MUSIC for Angle and Array Gain-Phase Error Estimation in Bistatic MIMO Radar

• Published in: IEEE communications letters Vol. 17; no. 3; pp. 443 - 446
• Main Authors: Li, Jianfeng, Zhang, Xiaofei, Cao, Renzheng, Zhou, Ming
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antennas; Applied sciences; Arrays; Detection, estimation, filtering, equalization, prediction; Error analysis; Errors; Estimation; Exact sciences and technology; gain-phase error; Information, signal and communications theory; Linear arrays; MIMO radar; multiple signal classification; Multiple-input multiple-output radar; Radar; Radiocommunications; Radiolocalization and radionavigation; reduced-dimension; Robustness; Sensor arrays; Signal and communications theory; Signal classification; Signal representation. Spectral analysis; Signal, noise; Telecommunications; Telecommunications and information theory; US Department of Defense; Performance evaluation; MIMO system; Parameter estimation; Phase measurement; Error estimation; Measurement sensor; reduced-dimension; Two dimensional model; Multiple-input multiple-output radar; Algorithm; Signal classification; Joint detection; Simulation; multiple signal classification; Phase estimation; gain-phase error; One dimensional model; Bistatic radar; Robustness; Linear antenna arrays
• ISSN: 1089-7798; 1558-2558
• DOI: 10.1109/LCOMM.2013.012313.122113

In this letter, the problem of joint angle and array gain-phase error estimation for bistatic multiple-input multiple- output (MIMO) radar is investigated, and an algorithm for joint estimation with the characteristics of multiple signal classification (MUSIC) is proposed. Through reduced-dimension transform, the angles can be obtained via two one-dimensional peak searches, and the array gain-phase error can be estimated by utilizing the estimated angles. The proposed algorithm can achieve automatically paired estimations of the angles, and is suitable for non-uniform linear array. For the case of separately-located ca-librated sensors, the algorithm can also work well. Furthermore, it has better angle and array gain-phase error estimation performance than the ESPRIT-like algorithm. The simulation results verify the algorithmic effectiveness and robustness of our proposed algorithm.