Predictive Quantization for Staggered Synthetic Aperture Radar

被引:0
作者
Gollin, Nicola [1 ]
Martone, Michele [1 ]
Villano, Michelangelo [1 ]
Rizzoli, Paola [1 ]
Krieger, Gerhard [1 ]
机构
[1] DLR, Microwaves & Radar Inst, Cologne, Germany
来源
2019 12TH GERMAN MICROWAVE CONFERENCE (GEMIC) | 2019年
关键词
Synthetic Aperture Radar; Quantization; Predictive Coding; Staggered SAR; Tandem-L;
D O I
10.23919/gemic.2019.8698197
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For upcoming spaceborne SAR mission the amount of data collected onboard is increasing, due to the employment of large bandwidths, multiple polarizations, and large swath widths, which lead to hard requirements in terms of onboard memory and downlink capacity. In this context, SAR raw data quantization represents an essential aspect, since it affects both the amount of data to be stored and transmitted to the ground and the quality of the resulting SAR products. In this paper, a data reduction approach based on predictive quantization is investigated in the context of Tandem-L, a DLR proposal for a highly innovative bistatic L-band radar satellite mission, aimed at monitoring the dynamic processes of the Earth. The proposed technique takes advantage of the time-variant autocorrelation properties of the non-uniform azimuth raw data stream in order to reduce the amount of data through a novel quantization method, named Predictive-Block Adaptive Quantization. Different prediction orders are investigated by considering the trade-off between achievable performance and complexity. Simulations for different target scenarios show that a data reduction of about 17.5% can be achieved with the proposed technique with a modest increase of the system complexity. Moreover, having a priori information on the gap positions in staggered SAR, a technique for their reconstruction based on dynamic bit allocation has been successfully implemented as well, showing no significant loss of information.
引用
收藏
页码:83 / 86
页数:4
相关论文
共 50 条
  • [21] An Universal Circular Synthetic Aperture Radar
    Nan, Yijiang
    Huang, Xiaojing
    Guo, Y. Jay
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [22] Dynamic Predictive Quantization for Staggered SAR: Experiments With Real Data
    Gollin, Nicola
    Giez, Jakob
    Martone, Michele
    Rizzoli, Paola
    Scheiber, Rolf
    Krieger, Gerhard
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [23] Compression of synthetic aperture radar video phase history data using trellis-coded quantization techniques
    Owens, JW
    Marcellin, MW
    Hunt, BR
    Kleine, M
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (02): : 1080 - 1085
  • [24] Optimal Radar Cross Section Estimation in Synthetic Aperture Radar
    Volosyuk, V. K.
    Zhyla, S. S.
    2017 IEEE FIRST UKRAINE CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (UKRCON), 2017, : 191 - 195
  • [25] Fusion of dynamic predictive block adaptive quantization and vector quantization for staggered SAR data compression
    Zou, Hang
    Zhao, Fengjun
    Jia, Xiaoxue
    Zhang, Heng
    Wang, Wei
    REMOTE SENSING LETTERS, 2021, 12 (02) : 206 - 215
  • [26] An Algorithm to Retrieve Precipitation with Synthetic Aperture Radar
    Xie Ya'nan
    Liu Zhikun
    An Dawei
    JOURNAL OF METEOROLOGICAL RESEARCH, 2016, 30 (03) : 401 - 411
  • [27] CALIBRATION OF CIRCULARLY POLARIZED SYNTHETIC APERTURE RADAR
    Sumantyo, Josaphat Tetuko Sri
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 5361 - 5364
  • [28] An Acceleration Framework for Synthetic Aperture Radar Algorithms
    Kim, Youngsoo
    Gloster, Clay S.
    Alexander, Winser E.
    ALGORITHMS FOR SYNTHETIC APERTURE RADAR IMAGERY XXIV, 2017, 10201
  • [29] Digital beam forming synthetic aperture radar
    Heer, C
    Shutie, PF
    2005 IEEE MTT-S International Microwave Symposium, Vols 1-4, 2005, : 1627 - 1630
  • [30] Migration technique for rotor synthetic aperture radar
    Jeon, M
    Kim, YS
    ELECTRONICS LETTERS, 1997, 33 (07) : 630 - 631