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Analysis on target detection and classification in LTE based passive forward scattering radar


Raja Abdullah, Raja Syamsul Azmir and Abdul Aziz, Noor Hafizah and Abdul Rashid, Nur Emileen and Salah, Asem Ahmad and Hashim, Fazirulhisyam (2016) Analysis on target detection and classification in LTE based passive forward scattering radar. Sensors, 16 (10). art. no. 1607. pp. 1-16. ISSN 1424-8220


The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

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Official URL or Download Paper: http://www.mdpi.com/1424-8220/16/10/1607

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.3390/s16101607
Publisher: MDPI
Keywords: Passive forward scattering radar sensor; Target detection; Target classification
Depositing User: Nabilah Mustapa
Date Deposited: 03 Jul 2017 09:28
Last Modified: 03 Jul 2017 09:28
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/s16101607
URI: http://psasir.upm.edu.my/id/eprint/56000
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