Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotio...Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.展开更多
针对低信噪比条件下,传统的基于旋转不变技术的三维信号参数估计(three-dimensional estimating signal parameter via rotational invariance te chniques,3D-ESPRIT)算法和平方前后向平滑的3D-ESPRIT(quadr atic-forward-backward 3D-...针对低信噪比条件下,传统的基于旋转不变技术的三维信号参数估计(three-dimensional estimating signal parameter via rotational invariance te chniques,3D-ESPRIT)算法和平方前后向平滑的3D-ESPRIT(quadr atic-forward-backward 3D-ESPRIT,Q-FB-3D-ESPRIT)算法对几何绕射理论(geometric theory of diffraction,GTD)模型参数估计精度显著降低的问题,提出改进的极化Q-FB-3D-ESPRIT(polarized-Q-FB-3D-ESPRIT,PQ-FB-3D-ESPRIT)算法。改进算法与上述两种传统算法相比,增加了对目标极化信息的利用,有效延长了可利用电磁散射数据的长度。仿真结果表明,改进算法的参数估计精度要高于其他两种算法,且在低信噪比情况下尤为显著。此外,还对基于散射中心模型的雷达目标识别进行了研究,仿真结果进一步验证了所提算法的可行性。展开更多
基金supported by the National Natural Science Foundation for Young Scientists of China (61101182)
文摘Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.
文摘针对低信噪比条件下,传统的基于旋转不变技术的三维信号参数估计(three-dimensional estimating signal parameter via rotational invariance te chniques,3D-ESPRIT)算法和平方前后向平滑的3D-ESPRIT(quadr atic-forward-backward 3D-ESPRIT,Q-FB-3D-ESPRIT)算法对几何绕射理论(geometric theory of diffraction,GTD)模型参数估计精度显著降低的问题,提出改进的极化Q-FB-3D-ESPRIT(polarized-Q-FB-3D-ESPRIT,PQ-FB-3D-ESPRIT)算法。改进算法与上述两种传统算法相比,增加了对目标极化信息的利用,有效延长了可利用电磁散射数据的长度。仿真结果表明,改进算法的参数估计精度要高于其他两种算法,且在低信噪比情况下尤为显著。此外,还对基于散射中心模型的雷达目标识别进行了研究,仿真结果进一步验证了所提算法的可行性。
