Evolution of real-time onboard processing and classification of remotely sensed data

H N Mahendra  lowast; S Mallikarjunaswamy; G K Siddesh; M Komala; N Sharmila

doi:10.17485/IJST/v13i20.459

Article

Evolution of real-time onboard processing and classification of remotely sensed data

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v13i20.459

Year: 2020, Volume: 13, Issue: 20, Pages: 2010-2020

Original Article

Evolution of real-time onboard processing and classification of remotely sensed data

H N Mahendra^1∗, S Mallikarjunaswamy² , G K Siddesh² , M Komala³ , N Sharmila⁴

1 Assistant Professor and Research Scholar, Department of Electronics and Communication, JSS Academy of Technical Education, Bangalore, and Affiliated to Visvesvaraya Technological University, Belagavi, KA, India. Tel.: +91 9740129884
2 Associate Professor, Department of Electronics and Communication, JSS Academy of Technical Education, Bangalore, and Affiliated to Visvesvaraya Technological University, Belagavi, KA, India
3 Associate Professor, Department of Electronics and Communication, SJB Institute of Technology, Bangalore, and Affiliated to Visvesvaraya Technological University, Belagavi, KA, India
4 Assistant Professor, Department of Electrical and Electronics, RNS Institute of Technology, Bangalore and Affiliated to Visvesvaraya Technological University, Belagavi, KA, India

∗Corresponding author:
H N Mahendra
Assistant Professor and Research Scholar, Department of Electronics and Communication, JSS Academy of Technical Education, Bangalore, and Affiliated to Visvesvaraya Technological University, Belagavi, KA, India.
Tel: +91 9740129884
Email: [email protected]

Received Date:12 May 2020, Accepted Date:21 May 2020, Published Date:18 June 2020

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objectives: To provide a technical review of current hardware architecture, techniques, problems, and practices used for real-time on-board data processing and classification of Remotely Sensed (RS) data. Method: The major issues of data processing such as power limitation and downlink bandwidth are considered for analysis. Performance of traditional Central Processing Unit (CPU) and onboard Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA)based data processing are presented in Table 3. Different hardware architecture used for onboard data classification such as FPGA, Advanced RISC Microcontroller (ARM), and Digital Signal Processor (DSP) based system performance are reported in Tables 5 and 6 respectively. Findings: In general satellite data processing, immediate action cannot be taken against natural disasters because of the time taken in processing data at the ground station. Also the downlink bandwidth available between satellite and ground station many not be sufficient to transfer large size of data. One of the solutions to resolve this issue is to process the data onboard, so that data size will be reduced and can be downlink to the ground station for different applications such as urban planning, agriculture, defense/security purposes, biological threat detection, fire tracking on wild land, risk/hazard prevention and also helps to take immediate action during natural disasters. The existing hardware module and its architecture have been studied and concluded with a comparative result. These results aid the researchers to come up with a more optimized design and hardware architecture for data preprocessing and classification.

Keywords: Remote Sensing; pre-processing; classification; field programmable gate array; digital signal processor; graphics processing unit; central processing unit

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Copyright

© 2020 Mahendra, Mallikarjunaswamy, Siddesh, Komala, Sharmila. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Published By Indian Society for Education and Environment (iSee)