Abstract
Azimuth non-uniform signal-reconstruction is a critical step for azimuth multi-channel high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) data processing. However, the received non-uniform signal has noise in the actual azimuth multi-channel SAR (MCSAR) operation, which leads to the serious reduction in the signal-to-noise ratio (SNR) of the results processed by a traditional reconstruction algorithm. Aiming to address the problem of reducing the SNR of the traditional reconstruction algorithm in the reconstruction of non-uniform signal with noise, a novel signal-reconstruction algorithm based on two-step projection technology (TSPT) for the MCSAR system is proposed in this paper. The key part of the TSPT algorithm consists of a two-step projection. The first projection is to project the given signal into the selected intermediate subspace, spanned by the integer conversion of the compact support kernel function. This process generates a set of sparse equations, which can be solved efficiently by using the sparse equation solver. The second key projection is to project the first projection result into the subspace of the known sampled signal. The secondary projection can be achieved with a digital linear translation invariant (LSI) filter and generate a uniformly spaced signal. As a result, compared with the traditional azimuth MCSAR signal-reconstruction algorithm, the proposed algorithm can improve SNR and reduce the azimuth ambiguity-signal-ratio (AASR). The processing results of simulated data and real raw data verify the effectiveness of the proposed algorithm.
Highlights
As a mature remote-sensing technology, synthetic aperture radar (SAR) can realize all-day and all-weather imaging of the Earth’s surface, and it plays a vital role in Earth observation and remote sensing [1,2,3,4,5]
Due to the limitation of the minimum antenna area, the conventional single-channel SAR systems cannot meet the requirements of simultaneous high resolution and wide swath [6,7]
This paper innovatively proposes the idea of sparse uniform resampling to solve the problem of azimuth multi-channel SAR (MCSAR) non-uniform signal-reconstruction [26]
Summary
As a mature remote-sensing technology, synthetic aperture radar (SAR) can realize all-day and all-weather imaging of the Earth’s surface, and it plays a vital role in Earth observation and remote sensing [1,2,3,4,5]. MCSAR transmits a signal with low PRF toof the apertures sampling in rate equivalently, alleviating the system constraint of the minimum antenna area achieve a wide swath, and at the same time, all the [8,16,17,18]. Non-uniform sampling will cause azimuth Doppler ambiguity in the echo signal reby eachby channel. The improved DBF (IDBF) algorithm proposed in [21] defined the equivalent sampling interval to calculate the equivalent reconstructed Doppler bandwidth (ERDB). This paper innovatively proposes the idea of sparse uniform resampling to solve the problem of azimuth MCSAR non-uniform signal-reconstruction [26]. The proposed method can effectively suppress the ambiguity of the azimuth Doppler spectrum caused by non-uniformity and maintain a good SNR.
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