Abstract
This study discusses a smart radar antenna scanning mode that combines features of both the sector-scan mode used for conventional radar and the line-scan mode used for synthetic aperture radar (SAR) and achieves an application of the synthetic aperture technique in the conventional sector-scan (mechanically scanned) radar, and we refer to this mode as sector-scan synthetic aperture radar (SSAR). The mathematical model is presented based on the principle of SSAR, and a signal processing algorithm is proposed based on the idea of two-dimensional (2D) matched filtering. The influences of the line-scan range and speed on the SSAR system are analyzed, and the solution to the problem that the target velocity is very high is given. The performance of the proposed algorithm is evaluated through computer simulations. The simulation results indicate that the proposed signal processing algorithm of SSAR can gather the signal energy of targets, thereby improving the ability to detect dim targets.
Highlights
When the radar detects the target remotely, the target is normally assumed to be a point located in a resolution cell, and the energy of the target echo is assumed to be evenly distributed in the resolution cell
The method of Chen et al cannot significantly increase the signal-to-noise ratio (SNR) by accumulating adjacent range profiles, and this method is limited to low-acceleration cases and is less effective for scan synthetic aperture radar (SSAR) signal processing
Inspired by the idea of 2D matched filtering [13,14,15], the present study proposes a signal processing algorithm based on the principles of SSAR
Summary
When the radar detects the target remotely, the target is normally assumed to be a point located in a resolution cell, and the energy of the target echo is assumed to be evenly distributed in the resolution cell. Chen et al [6] proposed a method that eliminates the linear range migration caused by the target velocity using the keystone transform and increases the SNR by accumulating adjacent range profiles using the envelopecorrelation algorithm [7] or the phase gradient autofocus (PGA) algorithm [8] to compensate for higher-order motion These methods are effective when the acceleration is not high and the SNR is not low. Li et al [12] proposed a fast algorithm to process the result of the generalized keystone transform This algorithm performs a fast Fourier transform (FFT) in the transverse direction rather than pulse compression to eliminate range migration, and this method does not increase the SNR. The performance of this algorithm is verified through computer simulations, and this study lays a solid foundation for the practical application of SSAR
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