Imaging Algorithm of Millimeter-wave LFMCW Radar for Water Surface Texture Detection

WEI Xiangfei; CHONG Jinsong; WANG Xiaoqing; LI Yuan; MENG Hui

doi:10.11999/JEIT160684

Volume 39 Issue 5

May 2017

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(5): 1030-1035

WEI Xiangfei, CHONG Jinsong, WANG Xiaoqing, LI Yuan, MENG Hui. Imaging Algorithm of Millimeter-wave LFMCW Radar for Water Surface Texture Detection[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1030-1035. doi: 10.11999/JEIT160684

Citation:

WEI Xiangfei, CHONG Jinsong, WANG Xiaoqing, LI Yuan, MENG Hui. Imaging Algorithm of Millimeter-wave LFMCW Radar for Water Surface Texture Detection[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1030-1035. doi: 10.11999/JEIT160684

Citation:

PDF( 1503 KB)

Imaging Algorithm of Millimeter-wave LFMCW Radar for Water Surface Texture Detection

doi: 10.11999/JEIT160684

Funds:

The Foundation of National Key Laboratory of Science and Technology on Microwave Imaging (CXJJ_15S119)

Received Date: 2016-06-29
Rev Recd Date: 2016-11-01
Publish Date: 2017-05-19

Abstract

Abstract

In the application of millimeter-wave Linear Frequency Modulated Continuous Wave (LFMCW) radar for water surface detection, the echo of water surface itself is always covered by the echo of stationary targets and noises, leading to the result that water surface texture can hardly be seen in the figures obtained by the conventional imaging algorithm. To solve this problem, an imaging algorithm of millimeter-wave LFMCW radar for water surface texture is proposed, the Dechirp technique is adopted to complete the range compression in range direction, and the data is divided into blocks to be dealt with separately in azimuth direction. During the processing in azimuth direction, interference from static targets is removed in frequency domain according to the fact that stationary targets and moving targets have different Doppler frequencies; then, based on the electromagnetic scattering characteristic of water surface, a maximum likelihood estimation method is used to estimate azimuth spectrum parameters to calculate the energy of water surface echo. The proposed algorithm is used to process measured data, and the results show that water surface texture can be obtained, which means that the proposed algorithm is superior to the traditional one.

FullText(HTML)

References(16)

References

MEHDI G and MIAO Jungang. Millimeter wave FMCW radar for foreign object debris (FOD) detection at airport runways[C]. International Bhurban Conference on Applied Sciences Technology (IBCAST), Islamabad, Pakistan, 2012: 407-412. doi: 10.1109/IBCAST.2012.6177589.

FERRI M, GIUNTA G, BANELLI A, et al. Millimeter wave radar applications to airport surface movement control and foreign object detection[C]. European Radar Conference, Rome, Italy, 2009: 437-440.

MAZOUNI K, KOHMURA A, FUTATSUMORI S, et al. 77GHz FM-CW radar for FODs detection [C]. European Radar Conference, Paris, France, 2010: 451-454.

NSENGIYUMVA F, PICHOT C, ALIFERIS I, et al. Millimeter-wave imaging of foreign object debris (FOD) based on two-dimensional approach[C]. IEEE Conference on Antenna Measurements Applications (CAMA), Chiang Mai, Thailand, 2015. doi: 10.1109/CAMA.2015.7428122.

ZHONG Qi, ZHANG Zhongjin, YAN Danqing, et al. Airport runway FOD detection based on LFMCW radar using interpolated FFT and CLEAN[C]. IEEE 12th International Conference on Computer and Information Technology, Chengdu, China, 2012: 747-750. doi: 10.1109/CIT.2012.160.

FEIL P, MENZEL W, NGUYEN T P, et al. Foreign objects debris detection (FOD) on airport runways using a broadband 78 GHz sensor[C]. European Radar Conference, Amsterdam, Netherlands, 2008: 451-454. doi: 10.1109/ EUMC.2008.4751779.

LEONARD T, LAMONT S T, HODGES R, et al. 94 GHz TARSIER radar measurements of wind waves and small targets[C]. European Radar Conference, Manchester, UK, 2011: 73-76.

CAPUTI W J. Stretch: A time-transformation technique [J]. IEEE Transactions on Aerospace and Electronic System, 1971, 7(2): 269-278. doi: 10.1109/TAES.1971.310366.

CROMBIE D D. Doppler spectrum of sea echo at 13.56Mc/s [J]. Nature, 1955, 175(4459): 681-682. doi: 10.1049/cp.2012. 1727.

HUANG Weimin and GILL E. Measuring surface wind direction by mono-static HF Ground-Wave radar at the eastern China sea[J]. IEEE Journal of Oceanic Engineering, 2004, 29(4): 1032-1037. doi: 10.1109/JOE.2004.834175.

HUANG Weimin and GILL E. HF radar wave and wind measurement over the eastern China sea[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(9): 1950-1955. doi: 10.1109/TGRS.2002.803718.

BRUNING C, ALPER W R, and SCHROTER J G. On the focusing issue of synthetic aperture radar imaging of ocean waves[J]. IEEE Transactions on Geoscience and Remote Sensing, 1991, 29(1): 120-128. doi: 10.1109/36.101378.

OUCHI K. Synthetic aperture radar imagery of range traveling ocean waves[J]. IEEE Transactions on Geoscience and Remote Sensing, 1988, 26(1): 30-37. doi: 10.1109/36. 2997.

GOODMAN J W. Statistical Properties of Laser Speckle Patterns[M]. Laser Speckle and Related Phenomena, New York, USA, Springer, 1975: 9-75.

OLIVER C and QUEGAN S. Understanding Synthetic Aperture Radar Images[M]. Raleigh, NC, SciTech Publishing, USA, 2004: 49-100.

CHITROUB S, HOUACINE A, and SANSAL B. Statistical characterisation and modelling of SAR images[J]. Signal Processing, 2002, 82(1): 69-92.

Relative Articles

Supplements(0)

Cited By

Proportional views