Abstract
In this paper, three-dimensional (3-D) multiple-input multiple-output (MIMO) radar accurate localization and imaging method with motion parameter estimation is proposed for targets with complex motions. To characterize the target accurately, a multi-dimensional signal model is established including the parameters on target 3-D position, translation velocity, and rotating angular velocity. For simplicity, the signal model is transformed into three-joint two-dimensional (2-D) parametric models by analyzing the motion characteristics. Then a gridless method based on atomic norm optimization is proposed to improve precision and simultaneously avoid basis mismatch in traditional compressive sensing (CS) techniques. Once the covariance matrix is obtained by solving the corresponding semi-definite program (SDP), estimating signal parameters via rotational invariance techniques (ESPRIT) can be used to estimate the positions, then motion parameters can be obtained by Least Square (LS) method, accordingly. Afterwards, pairing correction is carried out to remove registration errors by setting judgment conditions according to resolution performance analysis, to improve the accuracy. In this way, high-precision imaging can be realized without a spectral search process, and any slight changes of target posture can be detected accurately. Simulation results show that proposed method can realize accurate localization and imaging with motion parameter estimated efficiently.
Highlights
Owing to accurate localization and imaging performance, radar is widely applied in many imaging fields
This paper presents an accurate multiple-input multiple-output (MIMO) radar 3-D localization and imaging method with motion parameter estimation for maneuvering target
In order to verify the feasibility of proposed method, ship target are imaged at two moments t A and t B with different motion parameters, radar parameters are set as Table 1 and motion parameters of t A and t B are set as Table 2
Summary
Owing to accurate localization and imaging performance, radar is widely applied in many imaging fields. The localization errors will increase so the image will be distorted and worsened when target complex motions are taken into account, for slow time-varying motions containing translations and rotations [1,2]. Under this circumstance, relevant studies mostly concentrate on synthetic aperture radar (SAR), inverse synthetic aperture radar (ISAR), and 3-D interference inverse synthetic aperture radar The imaging accuracy and real-time performance will be worse if the synthetic aperture time cannot be optimized reasonably. The platform is usually required to ensure baselines unchanged during synthetic aperture time, which is impractical in actual. The geometric models are usually one or two-dimensional which are insufficient to accurately
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