Abstract
Spectrum analysis (SA) plays an important role in radar signal processing, especially in radar imaging algorithm design. Because it is usually hard to obtain the analytical expression of spectrum by the Fourier integral directly, principle of stationary phase (POSP)-based SA is applied to approximate this integral. However, POSP requires the phase of the signal to vary rapidly, which is not the case in circular synthetic aperture radar (SAR) and turntable inverse SAR (ISAR). To solve this problem, a new SA method based on time-frequency reversion (TFRSA) is proposed, which utilizes the relationship of the Fourier transform pairs and their corresponding signal phases. In addition, the connection between the imaging geometry and time-frequency relationship is also analyzed and utilized to help solve the time-frequency reversion. When the TFRSA is applied to the linear trajectory SAR, the obtained spectrum expression is the same as the result of POSP. When it is applied to ISAR, the spectrum expressions of near-field and far-field are derived and their difference is found to be position-independent. Based on this finding, an extended polar format algorithm (EPFA) for near-field ISAR imaging is proposed, which can solve the distortion and defocusing problems caused by traditional ISAR imaging algorithms. When it is applied to the circular SAR (CSAR), a new and efficient imaging method based on EPFA is proposed, which can solve the low efficiency problem of conventional BP-based CSAR imaging algorithms. The simulations and real data processing results are provided to validate the effectiveness of proposed method.
Highlights
Radar can realize long distance target detection, localization, imaging, classification and recognition in all-day and all-weather conditions, and has become a significant tool in many applications
From Equation (9) we find that principle of stationary phase (POSP) can simplify the Fourier transform (FT) integral and produce good approximated result, so it is widely used in radar signal processing
In order to solve this problem, we propose a new TFR-based spectrum analysis (TFRSA) method, which utilizes the relationship of the Fourier pairs and their corresponding signal phase
Summary
Radar can realize long distance target detection, localization, imaging, classification and recognition in all-day and all-weather conditions, and has become a significant tool in many applications. Among these applications, Synthetic aperture radar (SAR) [1,2,3]. The resolution of radar image in the range dimension is accomplished by transforming the large signal bandwidth, whereas the fine resolution in azimuth stems from the difference in observation angles. With the development of advanced hardware, the available radar bandwidth is becoming larger, which in turn produces ultrahigh-resolution radar images. The microwave-photonic technique [7,8,9], which combines the advantages of electromagnetic wave and photonics techniques, is applied to the radar system to produce an ultra-large 10 GHz bandwidth radar signal
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