基于频率分集逆合成孔径雷达的多重信号分类目标成像算法

将频率分集的思想应用在逆合成孔径雷达(inverse synthetic aperture radar,ISAR)成像中,通过单频信号合成宽带信号,可解决系统发射接收宽带信号复杂的问题.但窄带的合成可视为宽带信号的稀疏采样,由此带来了旁瓣提高等难点.提出一种基于频率分集ISAR体制的多重信号分类(multiple si...

MUSIC target imaging algorithm based on frequency diversity ISAR

The idea of frequency diversity is applied to inverse synthetic aperture radar (ISAR) imaging, and the complex problem of transmitting and receiving broadband signals can be solved by synthesizing broadband signals through single frequency signals. However, the synthesis of narrow band can be regarded as the sparse sampling of broadband signal, which brings difficulties such as side lobe enhancement. In this paper, a multiple signal classification (MUSIC) target imaging algorithm based on frequency diversity ISAR system is proposed. The eigenvalue decomposition of the echo signal covariance matrix received by the composite array is carried out to obtain the signal subspace and the noise subspace. Then construct a spectral function based on the orthogonality of the two to estimate the target position, and obtain a super-resolution two-dimensional image of the target. In this paper, the MUSIC algorithm is compared with the Back Projection (BP) algorithm. The simulation results show that the former algorithm can still achieve better imaging effect in the environment with strong noise, which proves that the application of this method can effectively solve the problem of high side lobe caused by frequency sparsity.