Clutter Statistics Research Articles

Electromagnetic wave imaging of targets buried in a cluttered medium using a hybrid inversion-DORT method

The detection and the characterization of targets buried in a natural medium using an array of monochromatic micro-wave antennas are difficult tasks as medium heterogeneities blur the signature of the objects of interest. In this paper, we propose to couple a nonlinear inversion method to an eigenvector analysis of the time reversal operator (Décomposition de l’Opérateur de Retournement temporel (DORT) technique) for imaging the targets. We show that this combined approach yields much better results than those of the inversion or DORT approaches alone. In particular, it enables us to characterize targets in highly cluttered environments supporting multiple scattering. The efficiency of the technique is illustrated throughout many examples with varying clutter statistics.

The CFAR Detection of Ground Moving Targets Based on a Joint Metric of SAR Interferogram's Magnitude and Phase

By analyzing the backscattering difference between moving targets and stationary clutter contained in the interferogram, a constant false alarm rate (CFAR) detecting method based on a joint metric of synthetic aperture radar (SAR) interferogram's magnitude and phase (IMP) for ground moving targets has been proposed in this paper. First, utilizing the exclusive mapping relationship between interferometric phase and the module of corresponding vector, and combining interferometric magnitude, a new joint metric, called IMP metric, has been constructed. Second, under the frame of multiplicative model, based on the complex Wishart-distribution, the IMP metric's statistical model, simply denoted as S0 distribution, has been derived. Meanwhile, the parametric estimators of the S0 distribution have also been presented based on the Mellin transform. Finally, the CFAR threshold of ground moving target detection using the S0 distribution has been given analytically. The experiments performed on measured dual-SAR images not only show the effectiveness of the IMP metric's statistical models and the parametric estimators, but also prove the good performance of the proposed CFAR detecting method.

Application of Artificial Neural Network for Clutter Rejection

This paper deals with application of Artificial Neural Network (ANN) for Radar Clutter rejection, function approximation method of supervised ANN is applied here using back propagation algorithm. The database used for training and testing the ANN has been collected from simulating a moving vehicle in MATALAB(version 7.9) to obtain the RCS values at range and cross-range profiles. This work is validated by comparing received signal after clutter rejection with the received signal in no clutter condition.

A physical statistical clutter model for active sonar scenarios with variable signal-to-noise ratios

Active sonar classification algorithms need to be robust in preventing operator overload while not being misled by false targets. This talk describes a new 3-parameter statistical sonar clutter model that not only provides a physical context for relating the characteristics of normalized matched-filter echo-data distributions to scatterer attributes, but scatterer information that is largely independent of its peak signal-to-noise ratio (SNR) value. It extends our 2-parameter Poisson-Rayleigh model (Fialkowski and Gauss, IEEE JOE, 2010) by adding a quantitative measure of scatterer spatial dispersion to its measures of scatterer density and relative strength. Maximum likelihood estimates of the clutter model’s 3 parameters were derived from mid-frequency (1-5 kHz) shallow-water active sonar data containing returns from biologic, geologic and anthropogenic objects with differing spatial and scattering characteristics. The resulting clutter model’s probability density functions not only fit the non-Rayleigh data well while displaying an insensitivity to SNR, but the dispersion parameter values were consistent with the known spatial characteristics of the scatterers and the values’ ping-to-ping variance correlated strongly with clutter object class, all of which are encouraging with regard to developing robust physics-based active classification algorithms. [Work supported by ONR.]

Ground Moving Target Indication and Velocity Estimation Using an InSAR System

For InSAR systems with both along track baseline and cross track baseline, referred to as the hybrid baseline for simplicity, can be used to perform GMTI and DEM generation simultaneously. However, the cross-track baseline of such system is sensitive to the terrain fluctuation which badly affects the performance of clutter suppression. To solve the problem above, a GMTI method which takes advantage of the coherence information of neighboring pixel pairs of SAR images is presented in this paper. After neighboring pixel pairs are jointly used to compensate the terrain interferometric phase, an adaptive filtering method is used to suppress the stationary clutter with the benefit of calibrating the sensor responses. In addition, the accuracy of velocity estimation is improved due to the improvement of clutter suppression. Stimulation experiments illustrate the effectiveness of the proposed algorithm.

Indication of slowly moving ground targets in non-Gaussian clutter using multi-channel synthetic aperture radar

The problem of how best to maximise the ratio of mean target intensity to mean background intensity for slowly moving targets in sets of multi-channel synthetic aperture radar images is discussed for highly non-Gaussian background clutter. The problem is formulated as a direct maximisation of target-to-clutter ratio thus giving a true maximisation of that ratio. Complex-valued weights derived using generalised eigensystem theory are used to maximise the ratio of quadratic forms representing the mean intensity of the target and background derived from their coherence matrices. For two to four channels it is shown that when the target is highly coherent an optimum steering vector is a discrete Fourier transform. For more than two channels it is shown that the optimal solution is only valid within a subspace of the whole parameter space defined by the correlation parameters of the background clutter. Images from a publically released ground moving target indicator dataset are filtered using the results for three channels. The method outperform a standard space-time adaptive processing algorithm in suppressing the stationary background urban clutter image intensity relative to the image intensity because of a known slowly moving ground vehicle. Moreover, the steering vector is much simpler to implement.

Automatic Construction of 3D Basic-Semantic Models of Inhabited Interiors Using Laser Scanners and RFID Sensors

This paper is focused on the automatic construction of 3D basic-semantic models of inhabited interiors using laser scanners with the help of RFID technologies. This is an innovative approach, in whose field scarce publications exist. The general strategy consists of carrying out a selective and sequential segmentation from the cloud of points by means of different algorithms which depend on the information that the RFID tags provide. The identification of basic elements of the scene, such as walls, floor, ceiling, windows, doors, tables, chairs and cabinets, and the positioning of their corresponding models can then be calculated. The fusion of both technologies thus allows a simplified 3D semantic indoor model to be obtained. This method has been tested in real scenes under difficult clutter and occlusion conditions, and has yielded promising results.

Amplitude Statistics of Sea Clutter by MDL Principle

Amplitude Statistics of Sea Clutter by MDL Principle

Sea Clutter Amplitude Statistics Analysis by Goodness-of-Fit Test

This paper provides a quantitative method for analyzing the amplitudes statistics of sea clutter by goodness-of-fit (GOF) tests. It first introduces several well-known GOF tests, and then employs them to test the amplitude statistics of recorded live sea clutter. Results confirm that the amplitudes of recorded live sea clutter can be well modeled by the Weibull and K distributions.

1J5-5 Improvement of Automated Identification of the Heart wall by Reducing Stationary Clutter in Ultrasonic Echoes(Biomedical Ultrasound)

1J5-5 Improvement of Automated Identification of the Heart wall by Reducing Stationary Clutter in Ultrasonic Echoes(Biomedical Ultrasound)

Moving Target Indication via Three-Antenna SAR with Simplified Fractional Fourier Transform

Ground moving target indiction (GMTI) is of great important for surveillance and reconnaissance, but it is not an easy job. One technique is the along-track interferometry (ATI) synthetic aperture radar (SAR), which was initially proposed for estimating the radial velocity of ground moving targets. However, the measured differential phase may be contaminated by overlapping stationary clutter, leading to errors in velocity and position estimates. As effective clutter suppression can be achieved by multiple aperture or phase center antennas, this article presents a simplified fractional Fourier transform (SFrFT) for three-antenna-based SAR GMTI applications. This approach cancels clutter with three-antenna-based methods and forms two-channel signals through which moving targets are detected and imaged. Next, the Doppler parameters of the moving targets are estimated with the SFrFT-based estimation algorithm. In this way, both target location and target velocity are acquired. Next, the moving targets are focused with one uniform imaging algorithm. The feasibility is validated by theory analysis and simulation results.

Ground Moving Target Indication via Multichannel Airborne SAR

We consider moving target detection and velocity estimation for multichannel synthetic-aperture-radar (SAR)-based ground moving target indication (GMTI). Via forming velocity versus cross-range images, we show that small moving targets can be detected even in the presence of strong stationary ground clutter. Furthermore, the velocities of the moving targets can be estimated, and the misplaced moving targets can be placed back to their original locations based on the estimated velocities. An iterative adaptive approach, which is robust and user parameter free, is used to form velocity versus cross-range images for each range bin of interest. Moreover, we discuss calibration techniques to estimate the relative antenna distances and antenna gains in practical systems. Furthermore, we present a simple algorithm for stationary clutter cancelation. We conclude by demonstrating the effectiveness of our approaches by using the Air Force Research Laboratory publicly released Gotcha airborne SAR-based GMTI data set.

Ship Detection in Ice-Infested Waters Based on Dual-Polarization SAR Imagery

This letter discusses the potential of automatic ship detection in ice-infested waters based on satellite synthetic aperture radar (SAR) imagery. The popular K -distribution is used to model the backscatter statistics of sea ice clutter. The goodness of fit of this model is assessed with the Kolmogorov-Smirnov and Anderson-Darling test statistics for both VV and VH polarizations. We also test the impact of introducing the Method of Log Cumulant (MoLC) estimator for the shape parameter of the K-distribution. Finally, a constant false-alarm rate ship detection algorithm, applying the K -distribution with the MoLC estimator, is evaluated on dual-polarization RADARSAT-2 SAR data. Our results demonstrate that this is a viable approach to ship detection in ice-infested waters.

Clutter suppression for airborne phased radar with conformal arrays by least squares estimation

The radar clutter statistics for airborne conformal arrays varies by range, i.e., the clutter distributions are nonstationary, which causes performance degradation for the conventional space–time adaptive processing (STAP), which estimates the clutter covariance matrix (CCM) from data at adjacent range cells. In this paper, a novel clutter suppression method for airborne phased radar with conformal arrays is proposed that takes a form of corrected sample matrix inversion (SMI) through the CCM estimated by the least squares (LS) estimation. The estimated CCM can provide partial information about the real CCM in the novel method, which results in improved detection performance for targets in conformal array applications. Simulation results relative to several typical conformal arrays verify the effectivity of the presented method.

Coherent Detection of Swerling 0 Targets in Sea-Ice Weibull-Distributed Clutter Using Neural Networks

The detection of Swerling 0 targets in movement in sea-ice Weibull-distributed clutter by neural networks (NNs) is presented in this paper. Synthetic data generated for typical sea-ice Weibull parameters reported in the literature are used. Due to the capability of NNs for learning the statistical properties of the clutter and target signals during a supervised training, high clutter reduction rates are achieved, reverting on high detection performances. The proposed NN-based detector is compared with a reference detector proposed in the literature that approximates the Neyman-Pearson (NP) detector. The results presented in the paper allow empirically demonstrating how the NN-based detector outperforms the detector taken as reference in all the cases under study. It is achieved not only in performance but also in robustness with respect to changes in sea-ice Weibull-distributed clutter conditions. Moreover, the computational cost of the NN-based detector is very low, involving high signal processing speed.

Statistic characteristic analysis of forward scattering surface clutter in bistatic radar

In this paper, based on the processing results of measured forward scattering clutter data in bistatic radar, using the Gaussian distribution model, Exponential distribution model, Power-Law distribution model, high order Auto-Regressive model and so on, the probability density distribution and power spectrum mathematical model are obtained, and the impact of clutter statistic models on target detection performance is analytically derived from statistic theory. According to the estimated clutter probability distribution, power spectrum model and generalized matching filter theory, the forward scattering clutter in bistatic radar is effectively suppressed and the target motion parameters are accurately estimated from the measured clutter data.

Using radar to measure humidity: an overview

WeatherVolume 65, Issue 12 p. 332-334 Research Article Using radar to measure humidity: an overview Kimberley Bartholomew, Corresponding Author Kimberley Bartholomew k.bartholomew@reading.ac.uk Department of Meteorology, University of ReadingUniversity of Reading, Department of Meteorology, Earley Gate, PO BOX 234, Reading RG6 6BB, UKSearch for more papers by this authorAnthony Illingworth, Anthony Illingworth Department of Meteorology, University of ReadingSearch for more papers by this authorJohn Nicol, John Nicol Department of Meteorology, University of ReadingSearch for more papers by this author Kimberley Bartholomew, Corresponding Author Kimberley Bartholomew k.bartholomew@reading.ac.uk Department of Meteorology, University of ReadingUniversity of Reading, Department of Meteorology, Earley Gate, PO BOX 234, Reading RG6 6BB, UKSearch for more papers by this authorAnthony Illingworth, Anthony Illingworth Department of Meteorology, University of ReadingSearch for more papers by this authorJohn Nicol, John Nicol Department of Meteorology, University of ReadingSearch for more papers by this author First published: 25 November 2010 https://doi.org/10.1002/wea.658Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume65, Issue12December 2010Pages 332-334 RelatedInformation

Biomimetic staring infrared imaging omnidirectional detection technology

In order to realize omnidirectional real-time detection and awareness in thermal infrared (IR) region, a kind of biomimetic miniature IR imaging detection system (BMIRIDS) has been successfully developed. It is classified as a long wave IR(LWIR) system and a mid-wave IR(MWIR) one. The former consists of a LWIR fish-eye lens and a LWIR focal plane array (FPA)-biomimetic electronic module, the latter consists of a MWIR fish-eye lens and a MWIR FPA-biomimetic electronic module. Both can provide complete hemispherical staring field of view, and have the capability to determine target bearings, to remove all stationary scene clutter and only detect moving targets, to sense targets range and their velocity. The capability closely approximates the vision process performed in nature by biological sensors. Furthermore, an additional biomimetic module block has been integrated into BMIRIDS. The module block imitating the function of human vision produces the logarithmic brightness image, and enhances the target image outline by virtue of the Roberts gradient difference. The logarithmic transform permits expanding the dynamic range of optical incidence without saturating the electric circuit, and makes the image more suitable for watching. DSP and FPGA perform the aforesaid vision functions that are advantageous to detect and track targets. Therefore, BMIRIDS can perform more powerful real-time signal and image processing on the resulting image data than the ordinary previous systems mainly by the aid of “software-only” processing. Because BMIRIDS has a 2π-steradian (sr.) staring field-of-view, two of such systems opposed to one another would provide a complete view of space around the sensor platform. In addition, its low power consumption makes itself meet the manifold platforms’ needs. The practice has proved that BMIRIDS can truly realize “omnidirectional” “real-time” situation awareness and dynamic information acquirement. By virtue of biomimetic technology, some limitations of the current photoelectric equipment have been broken and a new type of IR equipment has been developed.

Examination of the Effect of Array Weighting Function on Radar Target Detectability

A methodology is described to assess the detectability of targets by an airborne fire control radar (FCR) operating in a medium pulse-repetition frequency (PRF) mode in the presence of strong ground clutter as a function of the transmitting and receiving antenna array weighting functions and proportion of failed array elements. It describes the radar, antenna, and clutter modelling processes and the method by which target detectability is quantified. The detectability of targets in clutter is described using a detectability map, which provides a useful means of comparing target detectability as clutter conditions change. It concludes that the best target detectability is to be achieved using those weighting functions on transmit and receive which result in the lowest average sidelobe levels but that the margins between the more highly tapered weighting functions were small. Furthermore, it concludes that target detectability degrades as the proportion of failed elements increases. A failure of 5% of the elements gave modest, though meaningful, degradations in target detectability and would therefore form a suitable upper limit.

The Influence of Propagation Focusing on Clutter Statistics

Fluctuations in reverberation (clutter) from scatterers at long range in shallow water can be affected by many mechanisms. Their statistics, in particular the scintillation index (SI), depend not only on the statistics of the scatterers (their physical distribution, shape, orientation, etc.) but on the outward and return propagation paths. This paper investigates the focusing effects due to forward scattering from weak undulations in the seabed. Some existing Fresnel-Kirchhoff theory for monostatic, vertical incidence on a 2-D surface is adapted to demonstrate the behavior of the intensity's SI in bistatic geometry. In addition, using a simulation of bistatic geometry and a 1-D surface the intensity statistics are extended to include autocorrelation function and probability distribution. The behavior of these properties is investigated for various Gaussian-correlated roughnesses with or without an added component of uncorrelated roughness. Bistatic geometries include source and receiver moving with constant separation, and moving source with fixed receiver. Fairly modest vertical undulations can result in significant fluctuation due to reflection focusing with scintillation indices possibly greater than unity.