Space-Surface Bistatic SAR Image Enhancement Based on Repeat-Pass Coherent Fusion With Beidou-2/Compass-2 as Illuminators

Zeng, Tao; Zhang, Tian; Tian, Weiming; Hu, Cheng

doi:10.1109/lgrs.2016.2614337

Cited by 25 publications

(38 citation statements)

References 14 publications

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“…The research team from the Beijing Institute of Technology conducted imaging experiments based on Beidou Medium Earth Orbit (MEO) satellites [15,16] to detect corner reflector and transponder with strong scattering coefficients. They also proposed repeat-pass coherent fusion for image enhancement [17] and carried out experiments for China railway High-Speed (CRH) railway bridge imaging based on IGSO satellites, and besides, a new platform for larger scene images has been undergoing construction [18].…”

Section: Introductionmentioning

confidence: 99%

GNSS Imaging: A Case Study of Tree Detection Based on Beidou Geo Satellites

Yan¹,

Zhou²,

Gong³

2018

PIER C

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Abstract-Curved trajectories of traditional navigation satellites limit their performance in bistatic radar imaging system. Instead of using common Inclined Geosynchronous Orbit (IGSO)/Medium Earth Orbit (MEO) satellites in motion, a new global navigation satellite system (GNSS) imaging system based on Beidou geo synchronous orbit (GEO) satellites is presented to deal with this problem. The most prominent feature of GEO satellites is that they are still relative to the earth. This work includes three parts. First, a reasonable parallel assumption is provided to simplify the geometric topology of the imaging system, and the relevant path delay formula is deduced. Second, the principle of imaging based on multiple GEO satellites is proposed, and the simulation result is presented. Third, the entire signal processing, which uses a multi-correlator, is designed to improve the range resolution. Two imaging experiments targeting at the trees are described and conducted in Wuhan University to verify the imaging system. The first experiment is targeted at isolated trees, and the second experiment is focused on groves along the road. Conclusion can be obtained: the imaging result is highly consistent with the imaging area, which validates the feasibility of the method and confirms the potential use of GNSS imaging system in forest monitoring.

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Section: Introductionmentioning

confidence: 99%

GNSS Imaging: A Case Study of Tree Detection Based on Beidou Geo Satellites

Yan¹,

Zhou²,

Gong³

2018

PIER C

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“…In this paper, we focus on image modality in wireless sensor networks. The visibility and contrast of the captured images may be affected and may be degraded by many reasons, such as poor environmental condition, camera sensor noise, and other uncertain factors [3,4]. It is a necessary step before further processing and understanding the images to improve image quality with enhancement and denoising algorithm in many vision applications [5,6].…”

Section: Introductionmentioning

confidence: 99%

Non-linear adaptive image enhancement in wireless sensor networks based on non-subsampled shearlet transform

Tong

Chen

2017

J Wireless Com Network

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Acquiring clear images is a crucial precondition in many image-related applications, such as wireless sensor network, industrial inspection, and machine vision. In this paper, a multi-scale image adaptive enhancement algorithm for image sensors in wireless sensor networks based on non-subsampled shearlet transform is presented. The images are decomposed into different scales of coefficients. Then the coefficients are enhanced by a non-linear enhancement function. We set two thresholds for this function. One is used to classify the coefficients between the set to be denoised and the set to be enhanced; the other is to control the enhanced intensity of the coefficients. The thresholds are selected adaptively according to the decomposition scale and the standard deviation of the coefficients. The performance of the proposed algorithm is evaluated both objectively and subjectively. And the results show that the visibility of the images is enhanced significantly.

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“…Due to the fact that there is no need to construct SAR transmitter, GNSS-SAR has a higher flexibility together with lower expenses than conventional SAR under various applications. However low range resolution is one of the main problems that affects the current development of GNSS-SAR [1,2,13,14,16].…”

Section: Introductionmentioning

confidence: 99%

“…With the conventional GNSS-SAR imaging algorithm which includes both range and azimuth compression, range resolution is determined by signals bandwidth and bi-static angle for sensing while azimuth resolution is determined by Doppler frequency shift [1][2][3][4][5][6][7][8][9][10][11][12]14,15,17]. But in a numbers of typical literature such as [1][2][3][4][5][6][7][8][9][10][11][12]14,15,17], the system is considered as quasi-monostatic case, which means the bi-static angle can be regarded as zero. Thus the range resolution is merely determined by signal bandwidth among these works.…”

Section: Introductionmentioning

confidence: 99%

“…Concerning the value of range resolution, it is proportional to the reciprocal of doubled signal bandwidth value, and for GNSS signals, the bandwidth value is equal to the Pseudo-Random Noise (PRN) code chip rate [1,2]. Because the chip rate of GPS C/A code, P code and GLONASS P code are 1.023MHz, 10.023MHz, and 5.11MHz respectively, the range resolutions can be obtained at the levels 150 m, 15 m and 30 m, respectively; for full band Galileo E5 signal, the PRN code chip rate is 51.150MHz, thus the range resolution is achieved at 3 meters level [1][2][3][4][5][6][7][8][9][10][11][12]14,15,17]. Looking at the azimuth resolution of GNSS-SAR, the level less than 1 meter can be achieved [1,2].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Range Compression Algorithm for The~Resolution Enhancement in GNSS-SAR

Zheng¹,

Yang²,

Wu³

2017

Preprint

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Passive Global Navigation Satellite System (GNSS)-based Synthetic Aperture Radar (SAR), known as GNSS-SAR, is a new passive radar imaging system. However, compared with conventional SAR, range resolution of GNSS-SAR is significantly lower. To improve range resolution of GNSS-SAR is an interested topic for investigation. In this paper, a novel range compression algorithm for enhancing range resolutions of GNSS-SAR is proposed. In the proposed scheme, at first, range compression is conducted by correlating the received reflected GNSS signal of intermediate frequency (IF) with the synchronized direct baseband GNSS signal in range domain. Then spectrum equalization is applied to the compressed results to suppress side lobes. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR can be obtained by the proposed range compression algorithm, compared to the conventional range compression algorithm.

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Space-Surface Bistatic SAR Image Enhancement Based on Repeat-Pass Coherent Fusion With Beidou-2/Compass-2 as Illuminators

Cited by 25 publications

References 14 publications

GNSS Imaging: A Case Study of Tree Detection Based on Beidou Geo Satellites

GNSS Imaging: A Case Study of Tree Detection Based on Beidou Geo Satellites

Non-linear adaptive image enhancement in wireless sensor networks based on non-subsampled shearlet transform

A Novel Range Compression Algorithm for The~Resolution Enhancement in GNSS-SAR

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