Joint Angle and Gain-Phase Error Estimation for Nested Bistatic MIMO Radar via Tensor Decomposition

To suppress the performance degradation in nested bistatic multiple-input multiple-output radar caused by gain-phase error, we propose a tensor-based angle and gain-phase error estimation algorithm. First, we construct a three-way tensor model using the virtual aperture of the nested array, which is derived from the distribution characteristics of gain-phase error. Then, we employ the position distribution of calibration and virtual sensors for angle and gain-phase error estimation. The results indicate that the proposed algorithm has better performance compared to the state-of-the-art methods. Numerical simulations verify the theoretical analysis and superiority of the proposed algorithm. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper proposes a tensor-based algorithm to suppress the performance degradation in nested bistatic multiple-input multiple-output radar caused by gain-phase error. The algorithm constructs a three-way tensor model using the distribution characteristics of gain-phase error and employs the position distribution of calibration and virtual sensors for error estimation. Experimental results demonstrate that the proposed algorithm exhibits superior performance.