Abstract
Passive synthetic aperture radar (SAR) using Global Navigation Satellite System (GNSS) signals as the illuminators of opportunity has a relative coarse range resolution due to the narrow bandwidth of the navigation signals and the bi-static acquisition geometry, limiting its application for high-resolution requirement. In this paper, an image formation algorithm for range resolution improvement is investigated. A modified second order differentiation based method is applied on the range compressed signal of reference channel and surveillance channel, improving range resolution and keeping side-lobes at a lower level simultaneously, and the phase of processed signal is preserved by phase multiplication compensation for the following azimuth compression processing. To validate the effectiveness and benefits of the proposed algorithm in terms of range resolution and targets side-lobes, point targets simulation under different situations and real field experiment with strong scatters are conducted and discussed. Compared with the traditional GNSS-based passive SAR imaging algorithm, the results of the proposed method show that the imaging performance can be improved for better range resolution and lower side-lobes, benefitting for better distinguishing nearby targets and recognizing weak targets.
Highlights
Over the last few years, passive bistatic synthetic aperture radar (SAR) (Bi-SAR) has attracted much attention from the research community
The k-space support was derived for bistatic SAR images, and the spatial resolution was improved after coherently combination
The improvement of range resolution is based on a multistatic configuration system, and multistatic signals are collected to be processed for the improvement of resolution
Summary
Over the last few years, passive bistatic SAR (Bi-SAR) has attracted much attention from the research community. The k-space support was derived for bistatic SAR images, and the spatial resolution was improved after coherently combination For this strategy, the improvement of range resolution is based on a multistatic configuration system, and multistatic signals are collected to be processed for the improvement of resolution. As for the other strategy, many researchers concentrate on the signal processing of passive GNSS-based bistatic SAR to improve the range resolution. The existence of high side lobes will increase false alarm probability, and affect the weak target image formation For this second strategy for improving range resolution, it is based on the signal processing of individual passive bistatic SAR, and only one bistatic pair is required compared with the first strategy. Only a certain target scattering information can be obtained in this strategy, it guarantees an improved individual passive bistatic SAR imaging resolution, contributing to a better imaging foundation for multistatic image fusion.
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