The Real-Time Framework of the Push-to-Talk (PTT) Synchronization Scheme for Distributed SAR

Zhang, Yanyan; Zhang, Ruwei; Wang, Robert; Zhang, Heng

doi:10.1109/lgrs.2022.3173727

Cited by 6 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Time synchronization (TS) is a key pillar of maintaining the secure and stable functioning of the distribution power Internet of Things (IoT), which enables all devices in the network to keep the same logical clock [1,2]. With the development of new power systems, massive intelligent devices, renewable energy devices, and other distributed devices are integrated to the distribution power IoT [3][4][5][6], resulting in an stringent requirement for TS.…”

Section: Introductionmentioning

confidence: 99%

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Lu,

Zhao,

et al. 2024

CMC

View full text Add to dashboard Cite

Time synchronization (TS) is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things (IoT). Multi-clock source time synchronization (MTS) has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales, and the coupling of synchronization latency jitter and pulse phase difference. In this paper, the multi-timescale MTS model is conducted, and the reinforcement learning (RL) and analytic hierarchy process (AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference. Specifically, the multi-clock source selection is optimized based on Softmax in the large timescale, and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale. Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

show abstract

Section: Introductionmentioning

confidence: 99%

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Lu,

Zhao,

et al. 2024

CMC

View full text Add to dashboard Cite

show abstract

“…The TanDEM-X adopts the GPS signals to trigger its startup time, and then its system time is controlled with a high-stable clock source [23]. Different from the TanDEM-X, the LT-1 uses a pulse-per-second pulse of the GPS to synchronize time, and the GPS-disciplined clock [24] is used to maintain the time synchronization. Based on the processing framework of the LT-1 [25], time deviations can be estimated from the synchronization signals, and the influence of time deviations can be removed in baseline estimation, as detailed in Section III.…”

mentioning

confidence: 99%

An Advanced Interferometric Baseline Estimation Method (IBEM) for Spaceborne Bistatic SAR

Zhang,

Li,

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

Spaceborne bistatic SAR (BiSAR) employs singlepass Cross-Track Interferometry (XTI) to invert Digital Elevation Models (DEMs) of target areas. However, the accuracy of the inverted DEM is affected by various factors, especially interferometric baseline estimation. To this end, this paper proposes an advanced Interferometric Baseline Estimation Method (IBEM) for spaceborne BiSAR. First, the IBEM compensates for the time synchronization deviation of BiSAR systems using the pulse exchange phase synchronization method. Subsequently, the time, position, and velocity vectors of satellites are input into a highprecision orbit propagator to derive the state vectors at the imaging time. Leveraging these state vectors, the interferometric baseline is calculated with the main satellite that transmits radar signals as the origin of the coordinate system. Eventually, interferometric baseline estimation and DEM generation are performed based on two sets of data from the LuTan-1 (LT-1) BiSAR system, and the generated DEMs are compared with the external reference DEM to evaluate the performance of the IBEM and the LT-1 system. Results indicate that the proposed IBEM can accurately estimate the interferometric baseline and has extensive application prospects in future spaceborne multibaseline Interferometric SAR (InSAR) missions.

show abstract

Comparative analysis of deep learning based building extraction methods with the new VHR Istanbul dataset

Bakırman¹,

Komurcu²,

Sertel³

2022

Expert Systems with Applications

View full text Add to dashboard Cite

The Real-Time Framework of the Push-to-Talk (PTT) Synchronization Scheme for Distributed SAR

Cited by 6 publications

References 10 publications

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

An Advanced Interferometric Baseline Estimation Method (IBEM) for Spaceborne Bistatic SAR

Comparative analysis of deep learning based building extraction methods with the new VHR Istanbul dataset

Contact Info

Product

Resources

About