Measurement of River Surface Currents With UHF FMCW Radar Systems

Wang, C. J.; Wen, Biyang; G., Z.; Yan, Wu; Huang, Xianglin

doi:10.1163/156939307779367350

Cited by 25 publications

(18 citation statements)

References 14 publications

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“…Although this study chooses only simple models of ships as targets of recognition, one can add different types of random components to RCS for modeling RCS of complex targets. This study can be applied to many other applications in radar target recognition [7][8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Resultsmentioning

confidence: 99%

Application of Ica Technique to Pca Based Radar Target Recognition

Huang¹,

Lee²

2010

PIER

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Abstract-In this paper, the ICA (independent component analysis) technique is applied to PCA (principal component analysis) based radar target recognition. The goal is to identify the similarity between the unknown and known targets. The RCS (radar cross section) signals are collected and then processed to serve as the features for target recognition. Initially, the RCS data from targets are collected by angular-diversity technique, i.e., are observed in directions of different elevation and azimuth angles. These RCS data are first processed by the PCA technique to reduce noise, and then further processed by the ICA technique for reliable discrimination. Finally, the identification of targets will be performed by comparing features in the ICA space. The noise effects are also taken into consideration in this study. Simulation results show that the recognition scheme with ICA processing has better ability to discriminate features and to tolerate noises than those without ICA processing. The ICA technique is inherently an approach of high-order statistics and can extract much important information about radar target recognition. This property will make the proposed recognition scheme accurate and reliable. This study will be helpful to many applications of radar target recognition.

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Section: Resultsmentioning

confidence: 99%

Application of Ica Technique to Pca Based Radar Target Recognition

Huang¹,

Lee²

2010

PIER

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“…Therefore, noise-reduction processing on collected data becomes necessary. This study can be applied to many other applications in radar target recognition [11][12][13][14][15][16][17][18][19][20][21].…”

Section: Discussionmentioning

confidence: 99%

Application of SVD Noise-Reduction Technique to Pca Based Radar Target Recognition

Lee¹,

Ou²,

Fang³

2008

PIER

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Abstract-The noise effect is very challenging in radar target recognition. It usually degrades the accuracy of target recognition and then makes the recognition unreliable. In this study, we present a noise-reduction technique to improve the accuracy of radar target recognition. Our noise-reduction technique is based on the SVD (singular value decomposition). The PCA (principal components analysis) based radar recognition algorithm is utilized to verify our noise-reduction scheme. In our treatment, the received signals are arranged into a Hankel-form matrix. This Hankel-form matrix is decomposed into two subspaces, i.e., the noise-related subspace and clean-signal subspace. The noise reduction is obtained by suppressing the noise-related subspace and retaining the clean-signal space only. Simulation results show that the accuracy of target recognition is greatly improved as the received signals are first processed by the SVD noise-reduction technique. With the use of proposed noise-reduction scheme, the radar target recognition can tolerate more noises and then becomes more reliable. The noise-reduction technique in this study can also be applied to many other problems in radar engineering.

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“…According to the Ambiguity Function of the radar waveform, FMCW radar has advantages in range measurement, the same as CW radar in velocity measurement [12][13][14]. The dual mode radar presented in this paper combines radar in two designs can make a good performance in both range and velocity measurement, which is important in traffic information collection.…”

Section: Introductionmentioning

confidence: 99%

Velocity Error Analysis of a K-Band Dual Mode Traffic Radar

Yang¹,

Xu²,

Sun³

2008

PIER B

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Abstract-This paper is addressed to a design of K-band dual mode radar used in traffic information collection. The radar can work in both Frequency Modulate Continual Wave (FMCW) mode and Continual Wave (CW) mode. As VCO is seldom used as the oscillator in CW radar for velocity measurement, this paper studied the effect of phase noise and detecting distance on velocity error in CW mode in VCO design. The analysis shows that the effect of phase noise on velocity error can be reduced by shortening the detecting distance. There's little difference in short-range velocity measurement between the dual mode radar with MMIC VCO and the CW radar with low phase noise oscillator.

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Measurement of River Surface Currents With UHF FMCW Radar Systems

Cited by 25 publications

References 14 publications

Application of Ica Technique to Pca Based Radar Target Recognition

Application of Ica Technique to Pca Based Radar Target Recognition

Application of SVD Noise-Reduction Technique to Pca Based Radar Target Recognition

Velocity Error Analysis of a K-Band Dual Mode Traffic Radar

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