CAJ | 학술논문

针对压缩感知雷达(Compressive Sensing Radar, CSR)在感知矩阵和目标信息矢量失配时距离-多普勒参数估计性能下降的问题，该文提出一种稳健的盲稀疏度 CSR 目标参数估计方法。首先建立了 CSR 系统模型失配时的距离-多普勒2维参数稀疏感知模型，推导了以最小化感知矩阵相干系数(Coherence of Sensing Matrix, CSM)为准则的波形优化目标函数。其次提出了一种新的盲稀疏度CSR目标参数估计方法，通过发射波形，系统模型失配误差和目标信息矢量的相互迭代，逐步校正系统感知矩阵，最终以较高精度估计目标距离-多普勒参数。与传统CSR目标参数估计方法相比，该方法显著降低了CSR系统距离-多普勒参数的估计误差，改善了CSR目标参数估计的准确性和鲁棒性。计算机仿真验证了该方法的有效性。
침대압축감지뢰체(Compressive Sensing Radar, CSR)재감지구진화목표신식시량실배시거리-다보륵삼수고계성능하강적문제，해문제출일충은건적맹희소도 CSR 목표삼수고계방법。수선건립료 CSR 계통모형실배시적거리-다보륵2유삼수희소감지모형，추도료이최소화감지구진상간계수(Coherence of Sensing Matrix, CSM)위준칙적파형우화목표함수。기차제출료일충신적맹희소도CSR목표삼수고계방법，통과발사파형，계통모형실배오차화목표신식시량적상호질대，축보교정계통감지구진，최종이교고정도고계목표거리-다보륵삼수。여전통CSR목표삼수고계방법상비，해방법현저강저료CSR계통거리-다보륵삼수적고계오차，개선료CSR목표삼수고계적준학성화로봉성。계산궤방진험증료해방법적유효성。
In order to enhance the performance of estimating range-Doppler parameters in presence of mismatch error between sensing matrix and target information vector for Compressive Sensing Radar (CSR), a robust blind sparsity target parameter estimation algorithm is proposed. First, a two-dimensional sparse sensing model for range-Doppler estimation is established when there exists CSR system model mismatch error, and a waveform optimization object function is derived based on minimization Coherence of Sensing Matrix (CSM). Then, a novel blind sparsity CSR algorithm is employed to correct system sensing matrix and estimate the range-Doppler parameters by optimizing iteratively transmit waveform, system mismatch error and target information vector. Compared with traditional CSR algorithm, the proposed method reduces the range-Doppler estimation error, and enhances the accuracy and robustness of CSR target information estimation. The validity of the proposed method is demonstrated with numerical simulation.