Empirical model for low-angle millimeter wave (MMW) radar ground clutter

1995 ◽  
Author(s):  
Geoffrey H. Goldman
Keyword(s):  
Millimeter Wave ◽  
Empirical Model ◽  
Ground Clutter

Physical Scale Modeling the Millimeter-Wave Backscattering Behavior of Ground Clutter

2001 ◽  
Author(s):  
A. J. Gatesman ◽  
T. M. Goyette ◽  
J. C. Dickinson ◽  
J. Waldman ◽  
J. Neilson ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Ground Clutter ◽  
Scale Modeling ◽  
Physical Scale

Physical scale modeling the millimeter-wave backscattering behavior of ground clutter

2001 ◽  
Author(s):  
Andrew J. Gatesman ◽  
Thomas M. Goyette ◽  
Jason C. Dickinson ◽  
Jerry Waldman ◽  
Jim Neilson ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Ground Clutter ◽  
Scale Modeling ◽  
Physical Scale

scholarly journals Small Foreign Object Debris Detection for Millimeter-Wave Radar Based on Power Spectrum Features

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2316
Author(s):  
Peishuang Ni ◽  
Chen Miao ◽  
Hui Tang ◽  
Mengjie Jiang ◽  
Wen Wu
Keyword(s):  
Power Spectrum ◽  
Millimeter Wave ◽  
Pso Algorithm ◽  
Classification Performance ◽  
Support Vector ◽  
Measured Signal ◽  
Foreign Object ◽  
Millimeter Wave Radar ◽  
Ground Clutter ◽  
Wave Radar

Foreign object debris (FOD) detection can be considered a kind of classification that distinguishes the measured signal as either containing FOD targets or only corresponding to ground clutter. In this paper, we propose a support vector domain description (SVDD) classifier with the particle swarm optimization (PSO) algorithm for FOD detection. The echo features of FOD and ground clutter received by the millimeter-wave radar are first extracted in the power spectrum domain as input eigenvectors of the classifier, followed with the parameters optimized by the PSO algorithm, and lastly, a PSO-SVDD classifier is established. However, since only ground clutter samples are utilized to train the SVDD classifier, overfitting inevitably occurs. Thus, a small number of samples with FOD are added in the training stage to further construct a PSO-NSVDD (NSVDD: SVDD with negative examples) classifier to achieve better classification performance. Experimental results based on measured data showed that the proposed methods could not only achieve a good detection performance but also significantly reduce the false alarm rate.

Empirical model for SAR ground clutter data

2017 ◽  
Vol 11 (7) ◽  
pp. 805-813
Author(s):  
Dheeren Ku Mahapatra ◽  
Lakshi Prosad Roy
Keyword(s):  
Empirical Model ◽  
Ground Clutter

Empirical Model for Backscattering at Millimeter-Wave Frequency by Bare Soil Subsurface With Varied Moisture Content

2013 ◽  
Vol 10 (6) ◽  
pp. 1324-1328 ◽  
Author(s):  
Alon Eliran ◽  
Naftaly Goldshleger ◽  
Asher Yahalom ◽  
Eyal Ben-Dor ◽  
Menachem Agassi
Keyword(s):  
Moisture Content ◽  
Millimeter Wave ◽  
Empirical Model ◽  
Bare Soil ◽  
Wave Frequency ◽  
Soil Subsurface

An Empirical Model of Volume Scattering From Dry Sand-Covered Surfaces at Millimeter-Wave Frequencies

2013 ◽  
Vol 51 (6) ◽  
pp. 3673-3682 ◽  
Author(s):  
Adib Y. Nashashibi ◽  
Kamal Sarabandi ◽  
Fahad A. Al-Zaid ◽  
Sami Alhumaidi
Keyword(s):  
Millimeter Wave ◽  
Empirical Model ◽  
Volume Scattering ◽  
Dry Sand

Thin Film Inspection with Millimeter-Wave Reflectometer

1995 ◽  
Vol 7 (1) ◽  
pp. 89-100
Author(s):  
H. C. Han ◽  
E. S. Mansueto
Keyword(s):  
Thin Film ◽  
Millimeter Wave
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