Abstract
Stepped-frequency waveforms (SFWs) can use the digital signal processing method to obtain high-range resolution with relatively narrow instantaneous bandwidth, which has been used in synthetic aperture radar (SAR). However, SFWs have the disadvantages of poor antijamming capability and a long period of transmission. Also, in the coherent integration time, some echo data are frequently lost. A two-dimensional sparse imaging method in the space and frequency domains for SAR is proposed based on compressed sensing (CS) theory. A sparse SFW for SAR imaging is formed and analyzed first, which has the advantages of better antijamming capability and a shorter time period of transmission. The range compression is completed by using CS theory. As to the sparse echo data in the space domain, the imaging operator and the CS-based imaging scheme are constructed to simultaneously implement the range cell migration correction and azimuth compression. Compared with the conventional SAR imaging method of SFWs, a much smaller number of frequencies and a smaller amount of imaging data are required for SAR imaging by using the proposed method. Finally, the effectiveness of the proposed method is proven by simulation and experimental results.
Highlights
Synthetic aperture radar (SAR) can realize imaging for the ground targets all day and under all weather conditions, and can achieve a high resolution in range direction due to the use of high transmitted-pulse bandwidth and in azimuth direction due to the storage of data over a certain observation time.[1,2] along with the improvement of range resolution, the bandwidth of the transmitted signal will increase sharply, which is a huge challenge for sampling at the receiver using analog-to-digital technology.[3]
The Stepped-frequency waveforms (SFWs) is a kind of synthesized bandwidth signals which can use a sequence of singlefrequency pulses to achieve an ultrawide bandwidth, and the frequency of each pulse is increased in steps
If there exists a basis matrix Ψ 1⁄4 fψ[1]; ψ2; : : : ; ψN1 g satisfying h 1⁄4 ΨΘ, where Θ 1⁄4 fθig is a K-sparse vector, h can be reduced from N1-dimension to M1-dimension {M1 ≥ OðK logðN1ÞÞ7}, which is expressed as uM1×1 1⁄4 ΦM1×N1 hN1×1 1⁄4 ΦM1×N1 ΨN1×N1 ΘN1×1; (9)
Summary
Synthetic aperture radar (SAR) can realize imaging for the ground targets all day and under all weather conditions, and can achieve a high resolution in range direction due to the use of high transmitted-pulse bandwidth and in azimuth direction due to the storage of data over a certain observation time.[1,2] along with the improvement of range resolution, the bandwidth of the transmitted signal will increase sharply, which is a huge challenge for sampling at the receiver using analog-to-digital technology.[3]. In Ref. 11, a random-frequency SAR imaging scheme based on CS is put forward The advantage of this method is that only a small number of random frequencies are needed to reconstruct the image of the targets. 2. Even if some of the echo data are contaminated or lost in the space domain, the range cell migration correction and azimuth compression can be achieved by constructing the imaging operator and the CS-based imaging scheme.
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