Signal, Image and Video Processing

, Volume 13, Issue 8, pp 1549–1557 | Cite as

Object detectability enhancement under weak signals for passive GNSS-based SAR

  • Yu ZhengEmail author
  • Yang Yang
  • Wu Chen
Original Paper


Passive Global Navigation Satellite System (GNSS)-based Synthetic Aperture Radar (SAR), known as GNSS-SAR, is a recently developing SAR imaging system. Due to the restrictions of transmission power and long distance transmission between GNSS satellites and earth surface, the received signals can be very weak after reflections, in which a noisy GNSS-SAR image can be resulted in. In this study, a new imaging algorithm for GNSS-SAR objects signal detectability enhancement is proposed. The main idea of the proposed algorithm is to apply joint coherent and non-coherent integrations for azimuth compression processing for each scattering point. In the proposed algorithm, at first, each azimuth resolution cell is partitioned into multiple non-overlapped consecutive mini-slots. To both effectively average out the remaining noise from range compression and reduce azimuth samples for correlation operation, the azimuthally distributed range-compressed signals with migration corrected in each partitioned mini-slot are added together. Then azimuth correlation for the compression per azimuth cell is carried out based on the result obtained from performing the addition scheme. Both theoretical analysis and experimental study show that the proposed algorithm can result in obviously enhanced imaging signal detectability for object identification. Meanwhile, computation with the proposed imaging algorithm is significantly more efficient than with the conventional GNSS-SAR imaging algorithm.


Passive GNSS-based SAR SAR imaging Weak reflected signal 



The research was funded by Hong Kong Research Grants Council (RGC) Competitive Earmarked Research Grant (Project No: PolyU 152151/17E), the research fund from the Research Institute of Sustainable Urban Development, Hong Kong Polytechnic University, the research grant from Education Department of Hunan Province, China (Project No: 18C0758) and Hunan Natural Science Foundation under Grant (Project No: 2017JJ2291). We are very thankful to the ip-solution company for providing us a GPS receiver RF front end and corresponding open-source MATLAB code for the experiment in this research.

Compliance with ethical standards

Conflict of interest

The authors do not have conflicts of interest.

Human and animal rights statement

This research does not involve human participants and/or animals.


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Electronic Communication and Electrical EngineeringChangsha UniversityChangshaChina
  2. 2.Department of Land Surveying and Geo-informaticsThe Hong Kong Polytechnic UniversityHung HomChina

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