Models of clutter

Musha, Toshimitsu; Sekine, Matsuo

doi:10.1049/pbra004e_ch2

Cited by 6 publications

(5 citation statements)

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“…In [38], the use of the bivariate Gamma to model the magnitudes of wavelength-resolution SAR images is confirmed to be more realistic than the use of the bivariate Rayleigh distribution. The background clutter from high resolution or low grazing angle radar emission can be fit by the Weibull distribution by tuning its shape parameter [45]. This distribution can be used as an empirical model for the sea ice clutter [46], [47].…”

Section: Pdf Analysismentioning

confidence: 99%

Enhancing Change Detection in Ultra-Wideband VHF SAR Imagery: An Entropy-Based Approach With Median Ground Scene Masking

Vinholi,

Silva,

Alves

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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We propose an algorithm based on Information Theory to detect changes in Ultra-Wideband (UWB) Very-High Frequency (VHF) Synthetic Aperture Radar (SAR) images with high performance and low complexity. Our algorithm models the clutter-plus-noise using six different distributions and computes a scalar statistic for each pixel based on a multi-temporal stack of images. With this statistic, it is then possible to apply hypothesis testing and classification methods to infer the occurrence of a change. In this context, we derive expressions necessary for the entropy-based statistics, including the entropy variance for the Weibull and Rice distributions. We also evaluate the computational time complexity of the algorithm for each distribution studied. Furthermore, a masking strategy is used to reduce false alarms significantly. We show that the mask mapping assumptions are mild in scenarios with stacks of images, allowing its use in many scenarios. Our algorithm achieves a false alarm rate (FAR) of 0.08 and a probability of detection (PD) of 100%, outperforming existing methods on the CARABAS II data set.

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Section: Pdf Analysismentioning

confidence: 99%

Enhancing Change Detection in Ultra-Wideband VHF SAR Imagery: An Entropy-Based Approach With Median Ground Scene Masking

Vinholi,

Silva,

Alves

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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“…1) Video data processor, in which the raw video from each miniradar is received, deformatted and sent to the clutter map processor; detection; a common rectangular coordinates system for all detections; 4) Radar fusion processor, in which the data coming from each miniradar are fused in the common reference system; detections from one or more miniradar generate system plots;…”

Section: Processing Architecture and Functionsmentioning

confidence: 99%

“…In this particular application moving target indicator (MTI) filtering is absent, and the traditional spatial averaging CFAR processor (e.g., the mean level detector or more sophisticated automatic thresholding [4]) is not adequate due to the presence of extended targets. The solution proposed to attain CFAR is based on time averaging maps (often referred to as clutter map CFAR); the envelope of the signal received for each range-azimuth cell is time averaged scan by scan.…”

Section: Processing Architecture and Functionsmentioning

confidence: 99%

Airport surface surveillance with a network of miniradars

Galati¹,

Naldi²,

Ferri³

1999

IEEE Trans. Aerosp. Electron. Syst.

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A distributed system based on a network of short-range (1.5-3 km) radars, operating in the W-band (93-95 GHz), is proposed for the ground surveillance of airports. Both the architecture and the main features of each subsystem are described. The system can boast very high resolution, the elimination of shadowing, and the inclusion of image processing techniques in the track-while-scan (TWS) function.

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“…In many previous studies, many distributions were commonly found to be a good fit to the experimental data [17, 18]. Among them, the Weibull distribution fits well the data acquired from a number of clutter environments by changing its shape parameter [19]. Several detectors were analysed in the Weibull clutter distribution in the maximum likelihood sense [5, 20–22].…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of mean level constant false alarm rate detectors with binary integration in Weibull background

Baadeche

Soltani

2015

IET Radar, Sonar & Navigation

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In this study, the authors analyse the performance of some constant false alarm rate (CFAR) detectors namely: the cell averaging-CFAR (CA-CFAR), greatest of CFAR (GO-CFAR), the smallest of CFAR (SO-CFAR), the smallest of OS and CA-CFAR (SOSCA-CFAR) and the OS and CA-CFAR greatest of (OSCAGO-CFAR) detectors in homogeneous and nonhomogeneous Weibull background with binary integration under the assumption of a known shape parameter. The nonhomogeneity is modelled by the presence of interfering targets and the presence of a clutter edge in the reference window. The authors derive close-form expressions of the probability of false alarm in the case of a homogeneous clutter environment. For a non-homogeneous environment, the performance of these detectors is investigated by means of Monte Carlo simulations. The obtained results showed that the best false alarm rate performance at clutter boundary is obtained for the OSCAGO and GO-CFAR detectors, whereas the SOSCA and SO-CFAR detectors present better performance for the interfering targets situation.

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Models of clutter

Cited by 6 publications

References 0 publications

Enhancing Change Detection in Ultra-Wideband VHF SAR Imagery: An Entropy-Based Approach With Median Ground Scene Masking

Enhancing Change Detection in Ultra-Wideband VHF SAR Imagery: An Entropy-Based Approach With Median Ground Scene Masking

Airport surface surveillance with a network of miniradars

Performance analysis of mean level constant false alarm rate detectors with binary integration in Weibull background

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