Abstract
To obtain exact size of non-cooperative target in ISAR images, an accurate cross-range scaling (CRS) should be performed. To do this, an image based approach, which exploits two sequential ISAR images based on the scale and rotational relationship between them, has been adopted in the existing ISAR CRS methods. However, they have two major problems: 1) unknown effective rotation center (ERC) of non-cooperative target, and 2) performance degradation owing to the scintillation of two ISAR images. To address these issues, in this paper, we propose a new CRS method, mainly consisting of two steps: 1) coarse estimation of rotation velocity (RV) in range-Doppler (RD) domain after feature extraction and matching, and 2) using the estimate in Step1, fine RV estimation via singular value decomposition (SVD) in range/cross-range (RC) domain. Furthermore, experimental results based on simulated and real measured data are provided to demonstrate the effectiveness of the proposed method.
Highlights
Inverse synthetic aperture radar (ISAR) can provide two dimensional (2-D) radar image of non-cooperative targets [1]
Since the principal component analysis (PCA) is generally used to determine the direction of the largest variance of given data, by comparing two directions obtained from two sequential ISAR images, rotational velocity (RV) can be estimated without a priori information of effective rotation center (ERC) of the target
We assumed a monostatic radar in the X-band with a stepped frequency waveform, and its specifications are as follows: carrier frequency 9 GHz, frequency bandwidth 500 MHz (i.e. 0.3 m range resolution), pulse repetition frequency (PRF) 400 Hz, and SNR = 20 dB
Summary
Inverse synthetic aperture radar (ISAR) can provide two dimensional (2-D) radar image of non-cooperative targets [1]. Since the PCA is generally used to determine the direction of the largest variance of given data, by comparing two directions obtained from two sequential ISAR images, RV can be estimated without a priori information of ERC of the target. By using the estimated RV in the previous stage, matched SCs can be scaled into those in RC domain, where two matched SCs have only rotation relationship between them It is well-known that, since SVD successfully works for the estimation of a rigid body rotation of two objects in conventional image processing [30], much precise RV of the target can be obtained via a simple SVD. Upper-case) bold letters denote column vectors (resp. matrices). tr (·), det (·) and · denote the matrix trace, matrix determinant and Frobenius norm operators, respectively. diag [a, b] denotes the diagonal matrix, which has elements of a and b
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