Analysis of radar sensing coverage of a passive GNSS-based SAR system

Zheng, Yu; Yang, Yang; Chen, Wu

doi:10.1109/icl-gnss.2017.8376246

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…It is concluded from Section 2 that the high-order (higher than second-order) couplings between f τ and η can be neglected as the introduced range migration is smaller than a range resolution. Then, the inverse Fourier transform is applied to (9). For the sake of intuitiveness, α 0 is replaced with R 0 , which denotes the bistatic range at the reference instant.…”

Section: Long-time Optimized Integration For Vessel Target Detectionmentioning

confidence: 99%

“…Thus, GNSS-based passive radar shows its potential for the monitoring of sea areas which are not fully covered by the terrestrial sources [7]. In addition, GNSS provides a relatively large signal bandwidth, which is beneficial for the target detection capability [8][9][10]. Moreover, the most unique feature of GNSS is that any point on the Earth is assured to be simultaneously illuminated by 4-8 satellites in a single GNSS constellation from different angles.…”

Section: Introductionmentioning

confidence: 99%

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BeiDou-Based Passive Radar Vessel Target Detection: Method and Experiment via Long-Time Optimized Integration

Huang

Lou

et al. 2021

Remote Sensing

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The BeiDou navigation satellite system shows its potential for passive radar vessel target detection owing to its global-scale coverage. However, the restrained power budget from BeiDou satellite hampers the detection performance. To solve this limitation, this paper proposes a long-time optimized integration method to obtain an adequate signal-to-noise ratio (SNR). During the long observation time, the range migration, intricate Doppler migration, and noncoherence characteristic bring challenges to the integration processing. In this paper, first, the keystone transform is applied to correct the range walk. Then, considering the noncoherence of the entire echo, the hybrid integration strategy is adopted. To remove the Doppler migration and correct the residual range migration, the long-time integration is modeled as an optimization problem. Finally, the particle swarm optimization (PSO) algorithm is applied to solve the optimization problem, after which the target echo over the long observation time is well concentrated, providing a reliable detection performance for the BeiDou-based passive radar. Its effectiveness is shown by the simulated and experimental results.

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Section: Long-time Optimized Integration For Vessel Target Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BeiDou-Based Passive Radar Vessel Target Detection: Method and Experiment via Long-Time Optimized Integration

Huang

Lou

et al. 2021

Remote Sensing

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“…To validate the proposed scheme for enhancing GNSS radar imaging, field proof-of-concept experiments were carried out on the basis of software defined radio (SDR) GPS C/A code receiver. The same experimental equipment as first author's previous work [32] is employed in this research. The equipments at receiver end are illustrated in Figure 4.…”

Section: Proof-of-concept Field Experimental Confirmationmentioning

confidence: 99%

Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals

Zheng

Zhang

et al. 2020

Sensors

Self Cite

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Weak reflected signal is one of the main problems in a recent developing remote sensing tool—passive GNSS-based radar (GNSS radar). To address this issue, an enhanced GNSS radar imaging scheme on the basis of coherently integrating multiple satellites is proposed. In the proposed scheme, to avoid direct signal interference at surveillance antenna, the satellites that used as transmission of opportunity are in backscattering geometry model. To coherently accumulate echo signal magnitudes of the scene center in the targeted sensing region illuminated by the selected satellites, after performing the paralleled range compressions, a coordinates alignment operator is performed to the respective range domains, in which, pseudorandom noise (PRN) code phases are aligned. Thereafter, the coordinates aligned range compressed signals of the selected satellites are coherently integrated along azimuth domain so that imaging gain is improved and azimuth processing can be accomplished in only one state operation. The theoretical analysis and field proof-of-concept experimental results indicate that compared to both conventional bistatic imaging scheme and the state-of-the-art multi-image fusion scheme, the proposed scheme can provide a higher imaging gain; compared to the state-of-the-art multi-image fusion scheme, the proposed scheme has a less computational complexity and faster algorithm speed.

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Differential Performance of Satellite Navigation in Urban and Rural Andes of Ecuador

Rivas-Lalaleo,

Bautista-Naranjo,

Vayas-Ortega

et al. 2024

Smart Innovation, Systems and Technologies

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Analysis of radar sensing coverage of a passive GNSS-based SAR system

Cited by 5 publications

References 16 publications

BeiDou-Based Passive Radar Vessel Target Detection: Method and Experiment via Long-Time Optimized Integration

BeiDou-Based Passive Radar Vessel Target Detection: Method and Experiment via Long-Time Optimized Integration

Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals

Differential Performance of Satellite Navigation in Urban and Rural Andes of Ecuador

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