Journal articles on the topic 'Clutter rate'
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Blanchet, Paul G., Lindsey M. Farrell, and Greg Snyder. "University Students' Perceptions of a Person Who Clutters With or Without Video Education." Perspectives of the ASHA Special Interest Groups 2, no. 4 (January 2017): 28–40. http://dx.doi.org/10.1044/persp1.sig4.28.
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Purpose The purpose of this study was to examine the effects of video education about cluttering on students' perceptions of a person who clutters. Method A total of 193 undergraduate students served as participants. Ninety-five students were provided with a written definition of cluttering, while 98 were also provided with video education about cluttering. Students then rated a person who clutters on speech and personality scales. Results Results yielded significant group differences in ratings of intelligibility, speech rate, ease of listening, and competence. Respondents who viewed the educational video rated a person who clutters significantly more negatively along these dimensions than respondents who read a definition only. However, participants who did not view the video reported knowing significantly more people who clutter. Conclusion Findings suggest that this particular form of video education might provide students with “realistic” exposure to cluttering. Further research is needed to assess effects of exposure to and interaction with a person who clutters on perceptions of cluttering. Implications include the impact of prior exposure to those who clutter, as well as potential confusion between cluttering and “fast speech.” These factors might have influenced identification rates of individuals who clutter, which could have affected the results.
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Shin, Jeong Hoon, and Youngjin Choi. "Robust Control for the Detection Threshold of CFAR Process in Cluttered Environments." Sensors 20, no. 14 (July 13, 2020): 3904. http://dx.doi.org/10.3390/s20143904.
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The constant false alarm rate (CFAR) process is essential for target detection in radar systems. Although the detection performance of the CFAR process is normally guaranteed in noise-limited environments, it may be dramatically degraded in clutter-limited environments since the probabilistic characteristics for clutter are unknown. Therefore, sophisticated CFAR processes that suppress the effect of clutter can be used in actual applications. However, these methods have the fundamental limitation of detection performance because there is no feedback structure in terms of the probability of false alarm for determining the detection threshold. This paper presents a robust control scheme for adjusting the detection threshold of the CFAR process while estimating the clutter measurement density (CMD) that uses only the measurement sets over a finite time interval in order to adapt to time-varying cluttered environments, and the probability of target existence with finite measurement sets required for estimating CMD is derived. The improved performance of the proposed method was verified by simulation experiments for heterogeneous situations.
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Mozumi, Michiya, Ryo Nagaoka, and Hideyuki Hasegawa. "Singular value decomposition filtering in high-frame-rate cardiac vector flow imaging." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 171–79. http://dx.doi.org/10.11591/eei.v9i1.1858.
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Dysfunction of the left ventricle (LV) weakens the cardiac function and affects the physical activity. Echocardiagraphy has been used to visualize the blood flow dynamics and to evaluate the cardiac function. However, the signal processing to suppress the clutter signals should be employed. In this study, we employed the singular value decomposition (SVD) clutter filtering to obtain the cardiac blood speckle images. We also employed the adaptive thresholding metric to determine the proper cutoff values at each phase during the cardiac cycle. Moreover, we employed a depth-dependent SVD clutter filter for more accurate estimation of the cardiac blood echo signals. The 2D blood flow velocity vectors were estimated by applying the block matching method to obtained blood speckle images. The obtained results show that the proposed filter suppressed the clutter signals from left ventricular wall significantly, and the contrast-to-noise ratio (CNR) was improved from -0.5 dB to 13.8 dB by the proposed SVD clutter filtering.
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Kim, Sungho, and Kyung-Tae Kim. "Adjacent Infrared Multitarget Detection Using Robust Background Estimation." Journal of Sensors 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/7279081.
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Small target detection is very important for infrared search and track (IRST) problems. Grouped targets are difficult to detect using the conventional constant false alarm rate (CFAR) detection method. In this study, a novel multitarget detection method was developed to identify adjacent or closely spaced small infrared targets. The neighboring targets decrease the signal-to-clutter ratio in hysteresis threshold-based constant false alarm rate (H-CFAR) detection, which leads to poor detection performance in cluttered environments. The proposed adjacent target rejection-based robust background estimation can reduce the effects of the neighboring targets and enhance the small multitarget detection performance in infrared images by increasing the signal-to-clutter ratio. The experimental results of the synthetic and real adjacent target sequences showed that the proposed method produces an upgraded detection rate with the same false alarm rate compared to the recent target detection methods (H-CFAR, Top-hat, and TDLMS).
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Ha, Dung, Hieu Le, My Bui, and Linh Cao. "A Two-stage Detector for First-order Sea Clutter in HF Surface Wave Radar." Proceedings of the Bulgarian Academy of Sciences 75, no. 6 (June 30, 2022): 873–81. http://dx.doi.org/10.7546/crabs.2022.06.11.
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The detection capabilities in vertical polarized, High-frequency SurfaceWave Radar (HFSWR) are limited by the clutter spikes in first-order sea clutter. The energy, position, and Doppler frequency of first-order sea clutter depend on the sea states, which are non-homogeneous – because of that, using a fixed expression to eliminate sea clutter gives limited results. In this paper, the authors proposed a new adaptive method using a two-stage detector based on the Order Statistic Constant False Alarm Rate (OS-CFAR) principle. The approach shows the capability to eliminate heterogeneous clutter and detect targets in the vicinities of sea clutter in the Range – Doppler map.
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Ji, Xiaowei, Qiang Yang, and Linwei Wang. "A Self-Regulating Multi-Clutter Suppression Framework for Small Aperture HFSWR Systems." Remote Sensing 14, no. 8 (April 14, 2022): 1901. http://dx.doi.org/10.3390/rs14081901.
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The problem that this paper is concerned with is High Frequency Surface Wave Radar (HFSWR) detection of desired targets against a complex interference background consisting of sea clutter, ionosphere clutter, Radio Frequency Interference (RFI) and atmospheric noise. Eliminating unwanted echoes and exploring obscured targets contribute to achieving ideal surveillance of sea surface targets. In this paper, a Self-regulating Multi-clutter Suppression Framework (SMSF) has been proposed for small aperture HFSWR. SMSF can remove many types of clutter or RFI; meanwhile, it mines the targets merged into clutter and tracks the travelling path of the ship. In SMSF, a novel Dynamic Threshold Mapping Recognition (DTMR) method is first proposed to reduce the atmospheric noise and recognize each type of unwanted echo; these recognized echoes are fed into the proposed Adaptive Prophase-current Dictionary Learning (APDL) algorithm. To make a comprehensive evaluation, we also designed three novel assessment parameters: Obscured Targets Detection Rate (OTDR), Clutter Purification Rate (CPR) and Erroneous Suppression Rate (ESR). The experiment data collected from a small aperture HFSWR system confirm that SMSF has precise suppression performance over most of the classical algorithms and concurrently reveals the moving targets, and OTDR of SMSF is usually higher than compared methods.
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Kim, Du Yong. "Visual multiple‐object tracking for unknown clutter rate." IET Computer Vision 12, no. 5 (April 5, 2018): 728–34. http://dx.doi.org/10.1049/iet-cvi.2017.0600.
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Jin, Zhen Lu, Quan Pan, Chun Hui Zhao, and Wen Tian Zhou. "SVM Based Land/Sea Clutter Classification Algorithm." Applied Mechanics and Materials 236-237 (November 2012): 1156–62. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.1156.
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In this paper, a support vector machine (SVM) based land/sea clutter classification algorithm was proposed. For target location error correction based on passive beacon reference source of over-the-horizon radar (OTHR), the signal model of land/sea clutter is established, the three kinds of multi-features of land/sea clutter are analyzed, and the classification algorithm based on SVM using multi-features is detailed. Simulation experiments were carried out for different clutter-noise- ratios, and the results showed that the proposed algorithm has a higher recognition rate of land/sea clutter than algorithms based on single feature of backscatter amplitude or linear discriminant analysis. This paper could provide theoretical guidance for improving target location accuracy.
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Yan, Bo, Hua Zhang, Luping Xu, Yu Chen, and Hongmin Lu. "A Novel 4D Track-before-Detect Approach for Weak Targets Detection in Clutter Regions." Remote Sensing 13, no. 23 (December 5, 2021): 4942. http://dx.doi.org/10.3390/rs13234942.
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A 4D TBD approach is developed here for closely weak extended target tracking and overcoming heterogeneous clutter background and various clutter regions. The 4D measurements in this work are the points containing three positional information in spatial space and corresponding timestamp. The proposed method is mainly designed to address two issues. The first one is the dilemma between the weak target detection and difficult computation originating from the high dimensions of measurement. The second issue is the suppression of inhomogeneous background clutter and various clutter regions. The extension experiment using synthetic data showcases that no false alarm track would be built in the clutter regions, and the detection rate of close targets exceeds 94%. The experiments using real 3D radar also prove that the method works well in tracking closely maneuvering extended targets even if a clutter region exists.
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Halliday, Graeme, and John Snowdon. "The Environmental Cleanliness and Clutter Scale (ECCS)." International Psychogeriatrics 21, no. 6 (July 10, 2009): 1041–50. http://dx.doi.org/10.1017/s1041610209990135.
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ABSTRACTBackground: Development of a scale to rate the degree and various aspects of uncleanliness will facilitate description and research in cases of severe domestic squalor.Methods: Discussion with representatives of relevant agencies led to selection of various aspects of domestic uncleanliness and clutter to be assessed when describing cases of squalor. Rooms and areas with varying functions (toilet, kitchen, bedroom, etc.) were all to be rated, along with other indicators of squalor (e.g. odor, vermin). Trial use and further discussion resulted in reduction to ten items, each rated on a four-point scale, with succinct descriptions of anchor-points. Two experienced psychogeriatricians then used this new Environmental Cleanliness and Clutter Scale (ECCS) to rate independently 55 dwellings which had been reported by Aged Care staff as cluttered or unclean, and also rated overall degree of squalor. Reliability and indications of validity were analyzed.Results: The inter-rater reliability for the ten items was considered satisfactory (κ 0.48, varying from 0.31 to 0.58). Cronbach's α for the new scale was 0.94, demonstrating high internal consistency. Each author's ratings of degree of squalor (none to severe) matched well with the other's ratings on the scale; a score of >12 usually indicated moderate or severe squalor.Conclusion: The ECCS proved reliable and useful in rating cases where elderly people were living in severe domestic squalor.
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Yang, Xiaoqi, Kai Huo, Jianwei Su, Xinyu Zhang, and Weidong Jiang. "An Anti-FOD Method Based on CA-CM-CFAR for MMW Radar in Complex Clutter Background." Sensors 20, no. 6 (March 14, 2020): 1635. http://dx.doi.org/10.3390/s20061635.
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Traditional constant false alarm rate (CFAR) methods have shown their potential for foreign object debris (FOD) indication. However, the performance of these methods would deteriorate under the complex clutter background in airport scenes. This paper presents a threshold-improved approach based on the cell-averaging clutter-map (CA-CM-) CFAR and tests it on a millimeter-wave (MMW) radar system. Clutter cases are first classified with variability indexes (VIs). In homogeneous background, the threshold is calculated by the student-t-distributed test statistic; under the discontinuous clutter conditions, the threshold is modified according to current VI conditions, in order to address the performance decrease caused by extended clutter edges. Experimental results verify that the chosen targets can be indicated by the t-distributed threshold in homogeneous background. Moreover, effective detection of the obscured targets could also be achieved with significant detectability improvement at extended clutter edges.
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Zhang, Guangwei, Ping Li, Guolin Li, and Ruili Jia. "Distribution Characteristics of Ground Echo Amplitude and Recognition of Signal Grazing Angle." Sensors 21, no. 24 (December 12, 2021): 8315. http://dx.doi.org/10.3390/s21248315.
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With the continuous advancement of electronic technology, terahertz technology has gradually been applied on radar. Since short wavelength causes severe ground clutter, this paper studies the amplitude distribution statistical characteristics of the terahertz radar clutter based on the measured data, and provides technical support for the radar clutter suppression. Clutter distribution is the function of the radar glancing angle. In order to achieve targeted suppression, in this paper, selected axial integral bispectrum (selected AIB) feature is selected as deep belief network (DBN)input to complete the radar glancing angle recognition and the network structure, network training method, robustness are analyzed also. The ground clutter amplitude distribution can follow normal distribution at 0~45° grazing angles. The Weibull distribution and G0 distribution can describe the amplitude probability density function of ground clutter at grazing angles 85° and 65°. The recognition rate of different signal grazing angles can reach 91% on three different terrains. At the same time, the wide applicability of the selected AIB feature is verified. The analysis results of ground clutter amplitude characteristics play an important role in the suppression of radar ground clutter.
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Zhang, Linke, Na Wei, and Xuhao Du. "Waveform Design for Improved Detection of Extended Targets in Sea Clutter." Sensors 19, no. 18 (September 13, 2019): 3957. http://dx.doi.org/10.3390/s19183957.
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Adaptive waveform design for cognitive radar in the case of extended target detection under compound-Gaussian (CG) sea clutter is addressed. Based on the CG characteristics of sea clutter, the texture component is employed to characterize the clutter ensemble during each closed-loop feedback and its estimation can be used for the next transmitted waveform design. The resulting waveform design problem is formulated according to the following optimization criterion: maximization of the output signal-to-interference-plus-noise ratio (SINR) for sea clutter suppression, and imposing a further constraint on sidelobes level of the waveform autocorrelation outputs for decreasing the false alarm rate. Numerical results demonstrate the effectiveness of this approach.
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Demirli, Ramazan, Moeness G. Amin, Xizhong Shen, and Yimin D. Zhang. "Ultrasonic Flaw Detection and Imaging through Reverberant Layers via Subspace Analysis and Projection." Advances in Acoustics and Vibration 2012 (July 18, 2012): 1–10. http://dx.doi.org/10.1155/2012/957379.
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Ultrasonic flaw detection and imaging through reverberant layers are challenging problems owing to the layer-induced reverberations and front surface reflections. These undesired signals present a strong clutter and mask the flaw echoes. In this paper, a subspace-based approach is developed for removing, or significantly reducing, the unwanted reverberations, enabling proper flaw detection and imaging. The technique utilizes a set of independent clutter-only reference measurements of the material through the layer. If these measurements are not available, array measurements of the material with flaws are used instead. The clutter, due to its high strength relative to the flaw reflections, forms a subspace spanned by the eigenvectors corresponding to the dominant eigenvalues of the data covariance matrix. The clutter subspace is estimated and removed using orthogonal subspace projection. The clutter usually occupies multidimension subspace that is dependent on the level of coupling, material inhomogeneity, surface roughness, and the sampling rate of the measurements. When the clutter-only reference is not available, information theoretic techniques are used to estimate the dimension of the clutter subspace so that clutter signals are sufficiently suppressed without distorting the flaw signals. The effectiveness of the proposed approach is demonstrated using simulations and real measurement results.
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Weinberg, Graham Victor. "Constant false alarm rate detectors for pareto clutter models." IET Radar, Sonar & Navigation 7, no. 2 (February 2013): 153–63. http://dx.doi.org/10.1049/iet-rsn.2011.0374.
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Mahler, Ronald P. S., Ba-Tuong Vo, and Ba-Ngu Vo. "CPHD Filtering With Unknown Clutter Rate and Detection Profile." IEEE Transactions on Signal Processing 59, no. 8 (August 2011): 3497–513. http://dx.doi.org/10.1109/tsp.2011.2128316.
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Si, Weijian, Hongfan Zhu, and Zhiyu Qu. "Robust Poisson Multi-Bernoulli Filter With Unknown Clutter Rate." IEEE Access 7 (2019): 117871–82. http://dx.doi.org/10.1109/access.2019.2936864.
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Bo Tang, Jun Tang, and Yingning Peng. "Convergence Rate of LSMI in Amplitude Heterogeneous Clutter Environment." IEEE Signal Processing Letters 17, no. 5 (May 2010): 481–84. http://dx.doi.org/10.1109/lsp.2010.2044849.
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Putri, Farra Anindya, Dayat Kurniawan, Rahmawati Hasanah, Taufiqurrahman Taufiqurrahman, Eko Joni Pristianto, Hana Arisesa, Yusuf Nur Wijayanto, et al. "Development of FMCW Radar Signal Processing for High-Speed Railway Collision Avoidance." Jurnal Elektronika dan Telekomunikasi 22, no. 1 (August 31, 2022): 40. http://dx.doi.org/10.55981/jet.482.
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Collision is the main issue in safe transportation, including in the railway system. Sensor systems have been developed to detect obstacles to prevent a collision, such as using cameras. One disadvantage of the camera systems is that performance detection decreases in a not clean environment, like the target position behind the fogs. This paper discusses the development of frequency modulated continuous wave (FMCW) radar signal processing for high-speed railway collision avoidance. The development of radar signal processing combines a two-dimensional constant false alarm rate (2D-CFAR) and robust principal component analysis (RPCA) to detect moving targets under clutter. Cell average (CA) and Greatest of CA (GOCA) CFAR are evaluated under a cluttered wall environment along the railway track. From the experiment, the development of FMCW radar can detect stationary or moving obstacles around 675 meters in front of the locomotive. Combining 2D-CFAR and RPCA algorithm outperforms average background subtraction in extracting moving targets from strong clutter signals along the railway track.
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Wen, Baotian, Yanbo Wei, and Zhizhong Lu. "Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering." Entropy 24, no. 2 (February 8, 2022): 250. http://dx.doi.org/10.3390/e24020250.
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In marine radar target detection, sea clutter will cause a large number of missed alarms and false alarms, which will affect the accuracy of target detection. In order to suppress sea clutter effectively, a sea clutter suppression and target detection algorithm of marine radar image sequence based on spatio-temporal domain joint filtering is proposed in this paper. The proposed method is to add a sea clutter suppression link before detecting the target. Firstly, the marine radar image sequence is transformed into three-dimensional frequency wavenumber domain by three-dimensional fast Fourier transform (3D-FFT), and then the three-dimensional image spectrum is obtained. According to the fact that the sea clutter spectrum obtained from the image spectrum satisfies the dispersion relation of linear wave theory in the three-dimensional frequency wavenumber domain, a sea clutter model is established. Then, through the established sea clutter model, a spatio-temporal domain joint sea clutter suppressor is designed to filter the image spectrum. After that, the filtered image spectrum is transformed by three-dimensional inverse fast Fourier transform (3D-IFFT) to obtain the image sequence in which sea clutter is suppressed. Finally, target detection is carried out for sea clutter suppressed image sequence. The method is validated by using the real data of X-band marine radar. Compared with the classical Empirical mode decomposition (EMD) method, the improvement of signal-to-noise ratio (SNR) is more obvious, and SNR can be increased by 15.3 db at most. In addition, compared with target detection on original images directly, the proposed method has excellent detection rate and can increase detection rates by at least 8%.
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Vartanian, Lenny R., Kristin M. Kernan, and Brian Wansink. "Clutter, Chaos, and Overconsumption." Environment and Behavior 49, no. 2 (July 27, 2016): 215–23. http://dx.doi.org/10.1177/0013916516628178.
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How do cluttered, chaotic environments—such as messy kitchens—influence snacking behavior? How does one’s mind-set help prevent unwanted snacking from occurring? One hundred one female undergraduate students participated under standard-kitchen conditions or in a chaotic-kitchen condition. Participants were also asked to recall and write about a time when they felt particularly in control or particularly out of control. Finally, participants were given cookies, crackers, and carrots to taste and rate. Participants in the chaotic-kitchen condition and the out-of-control mind-set condition consumed more cookies (103 kcal) than did participants who were in the in-control mind-set condition (38 kcal). The chaotic environment had no impact on consumption of crackers or carrots. Although a chaotic environment can create a vulnerability to making unhealthy food choices, one’s mind-set in that environment can either trigger or buffer against that vulnerability.
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Gallippi, Caterina M., and Gregg E. Trahey. "Adaptive Clutter Filtering via Blind Source Separation for Two-Dimensional Ultrasonic Blood Velocity Measurement." Ultrasonic Imaging 24, no. 4 (October 2002): 193–214. http://dx.doi.org/10.1177/016173460202400401.
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A method for adaptive clutter rejection via blind source separation (BSS) using principal and independent component analyses is presented in application to blood velocity measurement in the carotid artery. In particular, the filtering method's efficacy for eliminating clutter and preserving lateral blood flow signal components is presented. The performance of IIR filters is compromised by shorth data ensembles (10 to 20 temporal samples) as implemented for color-flow and high frame-rate imaging due to initialization requirements. Further, the ultrasonic imaging system's transfer function maps axial wall and lateral blood motion to overlapping spectra. As such, frequency domain-based approaches to wall filtering are ineffective for distinguishing wall from blood motion signals. Rather than operating in the frequency domain, BSS performs clutter rejection by decomposing the input data ensemble into N constitutive source signals in time, where N is the ensemble length. Source signal energy coupled with respective signal depth and time course profiles reveal which source signals correspond to blood, noise and clutter components. Clutter components may then be removed without disruption of lateral blood flow information needed for two-dimensional blood velocity measurement. A simplistic data simulation is employed to offer an intuitive understanding of BSS methods for signal separation. The adaptive BSS filter is further demonstrated using a Field II simulation of blood flow through the carotid artery including tissue motion. BSS clutter filter performance is compared to the performance of FIR, IIR and polynomial regression clutter filters. Finally, the filter is employed for clinical application using a Siemens Elegra scanner, carotid artery data with lateral blood flow collected from healthy volunteers, and Speckle Tracking; velocity magnitude and angle profiles are shown. Once again, the BSS clutter filter is contrasted to FIR, IIR and polynomial regression clutter filters using clinical examples. Velocities computed with Speckle Tracking after BSS wall filtering are highest in the center of the artery and diminish to low velocities near the vessel walls, with velocity magnitudes consistent with physiological expectations. These results demonstrate that the BSS adaptive filter sufficiently suppresses wall motion signal for clinical lateral blood velocity measurement using data ensembles suitable for color-flow and high frame-rate imaging.
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Bolisetti, Siva Karteek, Mohammad Patwary, Khawza Ahmed, Abdel-Hamid Soliman, and Mohamed Abdel-Maguid. "Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter." Scientific World Journal 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/341619.
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The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.
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Chen, Jinguang, Bugao Xu, Lili Ma, and Rui Sun. "GM-PHD Filter Combined with Track-Estimate Association and Numerical Interpolation." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/629023.
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For the standard Gaussian mixture probability hypothesis density (GM-PHD) filter, the number of targets can be overestimated if the clutter rate is too high or underestimated if the detection rate is too low. These problems seriously affect the accuracy of multitarget tracking for the number and the value of measurements and clutters cannot be distinguished and recognized. Therefore, we proposed an improved GM-PHD filter to tackle these problems. Firstly, a track-estimate association was implemented in the filtering process to detect and remove false-alarm targets. Secondly, a numerical interpolation technique was used to compensate the missing targets caused by low detection rate. At the end of this paper, simulation results were presented to demonstrate the proposed GM-PHD algorithm is more effective in estimating the number and state of targets than the previous ones.
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Li, Bowen, Xiaoming Liu, Shasha Du, and Wanhan Li. "CFAR Detector Based on the Identification of Sea Clutter Distribution Characteristics." Journal of Physics: Conference Series 2221, no. 1 (May 1, 2022): 012013. http://dx.doi.org/10.1088/1742-6596/2221/1/012013.
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Abstract To improve the capability of radar detection in a time-varying maritime environment, an algorithm was proposed and analyzed in this paper that can be applied to determine the shape and scale parameters of the K-distributed model using the radar parameters and environmental information under the context of K-distributed sea clutter, and improved the original algorithm to improve the accuracy of the parameter estimation algorithm. Furthermore, a CFAR detector capable of identifying the characteristics of sea clutter distribution was developed. It can estimate the parameters of K-distributed model for sea clutter in real time using both radar parameters and environmental perception information, thus improving the accuracy of clutter background estimation. When the false alarm rate reaches a certain level, the adaptive threshold factor can be obtained for the CFAR detector proposed in this paper, thus improving the effectiveness of control on the CFAR detector. As suggested by the simulation results, the proposed method outperforms the CFAR detector with fixed parameters in the capability of detection and robustness under the context of K-distributed clutter.
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Baranov, G., R. Gabruk, and I. Gorishna. "Features of Usіng Pulse-Doppler Radars for Determіnatіon Low-Altіtude Targets." Metrology and instruments, no. 2 (May 3, 2019): 62–66. http://dx.doi.org/10.33955/2307-2180(2)2019.62-66.
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In this paper, we analyzed the features of Doppler processing in radars. In ground based radars, the amount of clutter in the radar receiver depends heavily on the radar-to-target geometry. The amount clutter is considerably higher when the radar beam has to face toward the ground. Furthermore, radars employing high PRFs have to deal with an increased amount of clutter due to folding in range. Clutter introduces additional difficulties for airborne radars when detecting ground targets and other targets flying at low altitudes. This is illustrated in Fig. 10.5. Returns from ground clutter emanate from ranges equal to the radar altitude to those which exceed the slant range along the main-beam, with considerable clutter returns in the side-lobes and main-beam. The presence of such large amounts of clutter interferes with radar detection capabilities and makes it extremely difficult to detect targets in the look-down mode. This difficulty in detecting ground or low altitude targets has led to the development of pulse Doppler radars where other targets, kinematics such as Doppler effects are exploited to enhance detection. Pulse Doppler radars utilize high PRFs to increases the average transmitted power and rely on target's Doppler frequency for detection. The increase in the average transmitted power leads to an improved SNR which helps the detection process. However, using high PRFs compromise the radar's ability to detect long range target because of range ambiguities associated with high PRF applications.
Techniques such as using specialized Doppler filters to reject clutter are very effective and are often employed by pulse Doppler radars. Pulse Doppler radars can measure target Doppler frequency (or its range rate) fairly accurately and use the fact that ground clutter typically possesses limited Doppler shift when compared with moving targets to separate the two returns. Clutter filtering is used to remove both main-beam and altitude clutter returns, and fast moving target detection is done effectively by exploiting its Doppler frequency. In many modern pulse Doppler radars the limiting factor in detecting slow moving targets is not clutter but rather another source of noise referred to as phase noise generated from the receiver local oscillator instabilities.
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Saleem, Farida, Muhammad Imran Malik, and Awais Qasim. "Supervisor Support, Self-Efficacy, and Employee Performance: The Mediating Role of Office De-Clutter." Administrative Sciences 12, no. 4 (November 28, 2022): 177. http://dx.doi.org/10.3390/admsci12040177.
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The study aims to test the impact of social support from supervisors and self-efficacy on employee performance through office de-clutter (a mediator) in banks. During the COVID-19 pandemic, the supporting factors (social support and self-efficacy) to de-clutter for maintaining employee performance is a novel contribution to the literature and is supported by the social exchange theory—SET. The employee’s performance can be maintained with lower levels of office clutter (de-clutter). The office clutter can be managed through the availability of managerial social support and employee self-efficacy. The impact of supervisor support and self-efficacy on employee performance is examined through the lens of the social exchange theory. A cross-sectional and quantitative study was conducted with 202 primary responses from bank employees. The responses were recorded using closed-ended questionnaires. A response rate of 73.9% was achieved. Reliability and validity were assessed using Cronbach’s alpha scores and AVE, respectively. PLS-SEM was used as a data analysis and hypotheses testing technique. The results revealed that supervisors’ social support and self-efficacy significantly and positively affect employee performance. Moreover, supervisors’ social support and self-efficacy helped in office de-clutter, further ensuring better performance.
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Kamal, Mustafa Subhi, and Jiwa Abdullah. "New algorithm for multi targets detection in clutter edge radar environments." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (April 1, 2020): 420. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp420-427.
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<p>This paper deals with the problem of multi target detection that appears inside clutter cloud which represent the worst radar environments by using constant false alarm rate CFAR algorithm, in order to achieve maximum probability of detection with constant false alarm rate, to detect target in such environments it need to construct robust constant false alarm CFAR algorithm that excise the target spikes from CFAR window and deal with clutter edges in order to give best possible estimation to the noise background. Modified cell averaged (CA-CFAR) is analyzed and compared with Two important algorithms which are cell averaged (CA-CFAR) and ordered statistics (OS-CFAR) algorithms in additional to the modified CA-CFAR algorithm. All these algorithms were simulated with mat lab and applied them to matlab clutter test model that represent different radar environment cases. Tradeoff among these algorithms depending on their responses.</p>
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Farshchian, M., A. Abdi, and F. Posner. "Level crossing rate of sea clutter: theory and measured data." Electronics Letters 48, no. 12 (2012): 725. http://dx.doi.org/10.1049/el.2012.0422.
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Weinberg, Graham V., Lachlan Bateman, and Peta Hayden. "Constant false alarm rate detection in Pareto Type II clutter." Digital Signal Processing 68 (September 2017): 192–98. http://dx.doi.org/10.1016/j.dsp.2017.06.014.
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Wang, Zeyu, Jun Liu, Yachao Li, Hongmeng Chen, and Mugen Peng. "Adaptive Subspace Signal Detection in Structured Interference Plus Compound Gaussian Sea Clutter." Remote Sensing 14, no. 9 (May 8, 2022): 2274. http://dx.doi.org/10.3390/rs14092274.
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This paper discusses the problem of detecting subspace signals in structured interference plus compound Gaussian sea clutter with persymmetric structure. The sea clutter is represented by a compound Gaussian process wherein the texture obeys the inverse Gaussian distribution. The structured interference lies in a known subspace, which is independent with the target signal subspace. By resorting to the two-step generalized likelihood ratio test, two-step Rao, and two-step Wald design criteria, three adaptive subspace signal detectors are proposed. Moreover, the constant false-alarm rate property of the proposed detectors is proved. The experimental results based on IPIX real sea clutter data and simulated data illustrate that the proposed detectors outperform their counterparts.
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Qi, Ziyi, Xiaohong Huang, and Lanpu He. "A New Side-Looking Scheme for Speed Estimation and Detection of Tangential Slow-Moving Targets." Sensors 22, no. 12 (June 16, 2022): 4535. http://dx.doi.org/10.3390/s22124535.
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A single-beam radar system cannot adopt a side-looking installation scheme, which is completely perpendicular to the moving direction of the target in an intelligent transportation system (ITS), because of its own limitations. In this paper, a side-looking radar velocity measurement system that utilizes a new signal processing method and multi-channel radar scheme is proposed. Constant false alarm rate (CFAR) and generalized likelihood ratio test (GLRT) detectors are used to detect the data processing results in different stages in order to reduce the false alarm rate of targets. At the same time, a deconvolution-based clutter map algorithm is proposed to solve the problem of clutter interference in the test environment, and its theoretical performance is verified by simulation. Finally, 77 G commercial radar is used to test the system, and the results show that this algorithm can effectively detect and accurately estimate the speed of tangential low-speed targets under clutter interference.
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Qin, Yuxin, and Yu Chen. "Signal processing algorithm of ship navigation radar based on azimuth distance monitoring." International Journal of Metrology and Quality Engineering 10 (2019): 12. http://dx.doi.org/10.1051/ijmqe/2019010.
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The effect of ship navigation radar signal processing has a great impact on the overall performance of the radar system. In this paper, the signal processing algorithm is studied. Firstly, the principle of radar azimuth and distance monitoring is introduced, then the pulse accumulation algorithm and median filtering algorithm are analyzed, and finally a sea clutter suppression algorithm based on sensitivity time control (STC) and a rain and snow clutter suppression algorithm based on constant false alarm rate are designed to improve the target monitoring performance of radar. In the test of the algorithm, the radar signal processing algorithm designed in this study has good precision as monitoring error of the target's azimuth and distance is controlled within 1%; and it also has a better suppression effect of sea clutter and rain and snow clutter, which can suppress the clutter well, improve the target clarity, and ensure the safe navigation of the ship. The experiment proves the effectiveness of the proposed algorithm and provides some theoretical basis for the better processing of radar signals, which is beneficial to improve the environment perception ability of ships in harsh environments and promote the further development of the navigation industry.
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Qu, Fu Yong, and Xiang Wei Meng. "Detection Performance of Several Nonparametric Detectors under K-Distributed Clutter." Advanced Materials Research 433-440 (January 2012): 6417–21. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6417.
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Because of nonparametric detectors’ ability of ensuring constant false alarm rate (CFAR) for a wide class of input noise distributions and engineering implementation simply, much efforts have been directed towards the study of nonparametric methods of signal detection. This paper deals with a comparative analysis of nonparametric detectors-GS, MW, Savage detector under K-distributed clutter in homogeneous and nonhomogeneous background caused by multiple targets and clutter edge. Some results of detection probability versus signal-to-clutter ratio (SCR) are presented in curves for different detector parameter values in homogeneous and multiple targets background. And the ability to control the false alarm probability for the three nonparametric detectors is presented in table. The simulation results show that S detector performs robustly in homogeneous background and clutter edge background, and can tolerate more interfering targets through increasing the number of reference cells and pulse sweeps. Therefore as a compromise solution, S detector with moderate parameters can be used in actual radar system.
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Yang, Zheng, Yongqiang Cheng, and Hao Wu. "PCA-Based Matrix CFAR Detection for Radar Target." Entropy 22, no. 7 (July 9, 2020): 756. http://dx.doi.org/10.3390/e22070756.
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In radar target detection, constant false alarm rate (CFAR), which stands for the adaptive threshold adjustment with variation of clutter to maintain the constant probability of false alarm during the detection, plays an important role. Matrix CFAR detection performed on the manifold of Hermitian positive-definite (HPD) covariance matrices is an efficient detection method that is based on information geometry. However, the HPD covariance matrix, which is constructed by a small bunch of pulses, describes the correlations among received data and suffers from severe information redundancy that limits the improvement of detection performance. This paper proposes a Principal Component Analysis (PCA) based matrix CFAR detection method for dealing with the point target detection problems in clutter. The proposed method can not only reduce dimensionality of HPD covariance matrix, but also reduce the redundant information and enhance the distinguishability between target and clutter. We first apply PCA to the cell under test, and construct a transformation matrix to map higher-dimensional matrix space to a lower-dimensional matrix space. Subsequently, the corresponding detection statistics and detection decision on matrix manifold are derived. Meanwhile, the corresponding signal-to-clutter ratio (SCR) is improved. Finally, the simulation experiment and real sea clutter data experiment show that the proposed method can achieve a better detection performance.
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Ran, Xiao, Zheng Hua Liu, and Le Chang. "Small Target Detecting and Tracking Based Kernel Density Estimation and Mean-Shift Algorithm." Advanced Materials Research 816-817 (September 2013): 523–26. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.523.
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Detecting and tracking the small moving target which is below 6×6 pixels with low signal to clutter ratio is the main difficulty in practical engineering. Based on morphology, this paper presents a new approach to promote the signal to clutter rate and highlight the small target. Then a new algorithm based on kernel function density estimation and mean-shift algorithm is proposed to track the small target. Experimental results demonstrate that this approach can track and detect the real target effectively.
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Chen, Feng, Guangjun He, and Qifang He. "A Composite Guidance Law for Suppressing Measurement Noise of LOS Angular Rate." Mathematical Problems in Engineering 2019 (January 6, 2019): 1–10. http://dx.doi.org/10.1155/2019/7453602.
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To effectively intercept a low-altitude target in clutter background, a nonsingular fast terminal sliding mode guidance law is designed. The designed guidance law can fully exploit the fast convergence characteristics of linear sliding mode control and the finite-time-convergent characteristics of terminal sliding mode control to ensure that the line-of-sight (LOS) angle converges to a desired angle in a limited time at a faster rate. Utilizing the smooth switching characteristics of the hyperbolic tangent function similar to the saturation function, a finite-time-convergent differentiator is designed. Meanwhile, a new finite-time-convergent disturbance observer designed on the tracking differentiator can effectively track the ideal LOS angular rate, suppress the measurement noise, and make a smooth estimation of the target maneuvering acceleration in clutter background. Combining the estimated value of the disturbance observer, the sign function with switch coefficient is introduced to design a composite nonsingular fast terminal sliding mode guidance law. The simulation results show that the composite guidance law can not only effectively suppress the measurement noise of the LOS angular rate and improve the accuracy of low-altitude target intercepting, but also greatly reduce the energy consumption in the interception process.
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Seo, Iksu, Seongweon Kim, Youngwoo Ryu, Jungyong Park, and Dong Seog Han. "Underwater Moving Target Classification Using Multilayer Processing of Active Sonar System." Applied Sciences 9, no. 21 (October 30, 2019): 4617. http://dx.doi.org/10.3390/app9214617.
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The task of detecting and classifying highly maneuverable and unidentified underwater targets in complex environments is significant in active sonar systems. Previous studies have applied many detection schemes to this task using signals above a preset threshold to separate targets from clutter; this is because a high signal-to-noise ratio (SNR) target has sufficient feature vector components to be separated out. However, in real environments, the received target return’s SNR is not always above the threshold. Therefore, a target detection algorithm is needed for varied target SNR conditions. When the clutter energy is too strong, false detection can occur, and the probability of detection is reduced due to the weak target signature. Furthermore, since a long pulse repetition interval is used for long-range detection and ambient noise tends to be high, classification processing for each ping is needed. This paper proposes a multilayer classification algorithm applicable to all signals in real underwater environments above the noise level without thresholding and verifies the algorithm’s classification performance. We obtained a variety of experimental data by using a real underwater target and a hull-mounted active sonar system operated on Korean naval ships in the East Sea, Korea. The detection performance of the proposed algorithm was evaluated in terms of the classification rate and false alarm rate as a function of the SNR. Since experimental environment data, including the sea state, target maneuvering patterns, and sound speed, were available, we selected 1123 instances of ping data from the target over all experiments and randomly selected 1000 clutters based on the distribution of clutters for each ping. A support vector machine was employed as the classifier, and 80% of the data were selected for training, leaving the remaining data for testing. This process was carried out 1000 times. For the performance analysis and discussions, samples of scatter diagrams and feature characteristics are shown and classification tables and receiver operation characteristic (ROC) curves are presented. The results show that the proposed algorithm is effective under a variety of target strengths and ambient noise levels.
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Snowdon, John, and Graeme Halliday. "A study of severe domestic squalor: 173 cases referred to an old age psychiatry service." International Psychogeriatrics 23, no. 2 (August 3, 2010): 308–14. http://dx.doi.org/10.1017/s1041610210000906.
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ABSTRACTBackground: Although community psychiatric services commonly encounter cases where intervention is needed due to persons’ unclean or cluttered living conditions, evidence concerning the referral rate and prevalence of severe domestic squalor is sparse.Methods: Between 2000 and 2009, ratings of cleanliness and clutter have been made in all cases of people living in squalor who have been referred to an old age psychiatry service in Central Sydney. Where possible, one-year follow-up was arranged.Results: 173 persons aged 65 years or more were referred to the service during the ten years and assessed as living in squalor (120 moderate or severe, two thirds of whom showed a moderate or severe degree of hoarding/clutter). Of 157 followed up after one year, 47% were still at home, 32% were in long-term care homes, 12% had moved elsewhere, and 9% had died. The annual new referral rate was close to 1 per 1000 elderly people in the catchment area, and of moderate or severe squalor was 0.66 per 1000. Limiting follow-up to those in moderate or severe squalor, 41% were still at home one year later. Current findings suggest that the minimum prevalence in the community of older people living in moderate or severe squalor in Sydney is 1 per 1000.Conclusions: The costs of intervening in cases of severe domestic squalor are considerable. Increased attention and funding are warranted, as the incidence and prevalence are higher than had previously been estimated.
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Moacdieh, Nadine Marie, Travis Ganje, and Nadine Sarter. "Physician perceptions of clutter in electronic medical records." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 572. http://dx.doi.org/10.1177/1541931213601627.
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Electronic medical records (EMRs) are now used by more than 95% of US hospitals (American Hospital Association (AHA) Annual Survey Information Technology Supplement, 2013). EMR systems typically provide a wide range of functionalities, including computerized physician order entry and the storage and presentation of patient medical data. The expectation has always been that these EMR functions would contribute to increased efficiency and safety of operations in hospital environments (Blumenthal & Glaser, 2007). However, display clutter in EMRs can lead to negative performance effects that can compromise the efficiency and safety of medical environments (e.g., Moacdieh & Sarter, 2015; Murphy, Reis, Sittig, & Singh 2012). However, it is not clear to what extent physicians view clutter as an impediment to their work, and, if so, whether it is solely the amount of visual data that leads to their perception of “clutter”. To this end, the aims of this study were to determine 1) whether physicians believe the nature and amount of EMR visual data affect their use of EMRs, 2) whether physicians think improvements are needed, and 3) to what extent it is the amount of data that leads to clutter versus some other qualitative aspect of the data. An anonymous survey was conducted among emergency medicine residents at the University of Michigan Department of Emergency Medicine. The response rate was around 60%, with 31 residents responding (age range 21-40 years). Residents had to respond to 18 questions. The first five questions asked for demographic information and participants responded using a dropdown menu. The next eight questions asked participants for their opinions about their satisfaction with their current EMR and the effects of visual data load on their work; participants responded using a 5-point Likert scale (strongly disagree or not at all (1) to strongly agree or extremely important (5)). The next three questions were free text and allowed residents to suggest design improvements to their current EMRs. Finally, the last two questions asked residents to rate, on a 100-point scale, the amount of clutter and the amount of information on sample screenshots from their current EMRs. This data was then correlated with each of the clutter image processing algorithms of Rosenholtz, Li, & Nakano (2007): feature congestion, subband entropy, and edge density. In general, results showed that physicians place a lot of importance on the design of visual information. Of the residents who responded, 52% indicated that visual data representation was “extremely important” for safety and the same percentage also said it was “extremely important” for efficiency. Also, 41% of residents agreed or strongly agreed that problems with visual data presentation have led to medical errors in their experience. In the free text space, physicians described many improvements that could be made to their EMR displays, particularly the reduction of excess irrelevant data. In addition, the correlation coefficients between the algorithm values and the ratings of amount of information were lower than the coefficients for ratings of clutter. This suggests that it is not just the quantity of information that factors into physicians’ perception of clutter; other factors, such as color variation and organization, play a role as well. In conclusion, this study showed that there is more to EMR clutter than merely excess data, and physicians appear to be aware of the dangers of clutter in their EMR displays.
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Cao, Xingwei, Yongqiang Cheng, Hao Wu, Zheng Yang, He Jing, and Hongqiang Wang. "Kernel Function Based Mean Matrix Estimation and Its Application to Radar Target Detection." Journal of Physics: Conference Series 2031, no. 1 (September 1, 2021): 012028. http://dx.doi.org/10.1088/1742-6596/2031/1/012028.
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Abstract The estimation of mean matrix for a set of Hermitian positive definite (HPD) matrices is of fundamental importance to radar target CFAR detection, which can be considered based on a geometric framework. However, false targets can cause large errors in the estimation of the mean clutter matrix. In this paper, we consider the nonlinearity of kernel function and the mean matrix estimation method based on kernel function is designed. In order to reduce the influence of false targets in the estimation of mean matrix, we apply the kernel function to the nonlinear adjustment of the geometric distance. Then, the kernel function based constant false alarm rate (CFAR) detector is designed. Finally, numerical experiments based on simulated clutter data and measured sea clutter data are performed. We come to a conclusion that the method of matrix mean value estimation based on kernel function can restrain the false target in the reference cells effectively.
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Liu, Xu, Shuwen Xu, and Shiyang Tang. "CFAR Strategy Formulation and Evaluation Based on Fox’s H-function in Positive Alpha-Stable Sea Clutter." Remote Sensing 12, no. 8 (April 17, 2020): 1273. http://dx.doi.org/10.3390/rs12081273.
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The problem of target detection in impulsive non-Gaussian sea clutter has attracted a lot of attention in recent years. The positive alpha-stable (PαS) distribution has been validated as a suitable model for the impulsive non-Gaussian sea clutter. Since the probability density function (PDF) of the PαS variable cannot be expressed as a closed-form expression, the research into constant false alarm rate (CFAR) detectors in PαS distributed sea clutter is limited. This paper formulates and evaluates some CFAR detectors, such as Greatest Of-CFAR (GO-CFAR), Smallest Of-CFAR (SO-CFAR), Order Statistic-CFAR (OS-CFAR) and censored mean level (CML) detectors, in PαS distributed sea clutter. Firstly, the Fox’s H-function is adopted to express the PDF of the PαS variable, and the cumulative density function based on Fox’s H-function is derived in this paper. Then, by use of the properties of the H-function and PαS distribution, exact expressions of the probabilities of false alarm and detection for CFAR detectors in the PαS background are derived. Some CFAR properties of these detectors in the PαS background are also explored. Numerical results based on derived expressions are given and verified by Monte Carlo simulation. Some analyses of detection performance from a practical perspective are also given.
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Mohammed, Marwan Qaid, Lee Chung Kwek, Shing Chyi Chua, Abdulaziz Salamah Aljaloud, Arafat Al-Dhaqm, Zeyad Ghaleb Al-Mekhlafi, and Badiea Abdulkarem Mohammed. "Deep Reinforcement Learning-Based Robotic Grasping in Clutter and Occlusion." Sustainability 13, no. 24 (December 10, 2021): 13686. http://dx.doi.org/10.3390/su132413686.
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In robotic manipulation, object grasping is a basic yet challenging task. Dexterous grasping necessitates intelligent visual observation of the target objects by emphasizing the importance of spatial equivariance to learn the grasping policy. In this paper, two significant challenges associated with robotic grasping in both clutter and occlusion scenarios are addressed. The first challenge is the coordination of push and grasp actions, in which the robot may occasionally fail to disrupt the arrangement of the objects in a well-ordered object scenario. On the other hand, when employed in a randomly cluttered object scenario, the pushing behavior may be less efficient, as many objects are more likely to be pushed out of the workspace. The second challenge is the avoidance of occlusion that occurs when the camera itself is entirely or partially occluded during a grasping action. This paper proposes a multi-view change observation-based approach (MV-COBA) to overcome these two problems. The proposed approach is divided into two parts: 1) using multiple cameras to set up multiple views to address the occlusion issue; and 2) using visual change observation on the basis of the pixel depth difference to address the challenge of coordinating push and grasp actions. According to experimental simulation findings, the proposed approach achieved an average grasp success rate of 83.6%, 86.3%, and 97.8% in the cluttered, well-ordered object, and occlusion scenarios, respectively.
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Hu, Xiaoyu, Jinming Ge, Jiajing Du, Qinghao Li, Jianping Huang, and Qiang Fu. "A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar." Atmospheric Measurement Techniques 14, no. 2 (March 3, 2021): 1743–59. http://dx.doi.org/10.5194/amt-14-1743-2021.
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Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.
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Wang, Zhonghua, Siwei Duan, and Chengli Sun. "Infrared Small Target Detection Method Combined with Bilateral Filter and Local Entropy." Security and Communication Networks 2021 (February 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/6661852.
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According to the larger false alarm rate resulted from fluctuant clutter, a novel method combined with bilateral filter and local entropy is proposed for infrared small target detection in this paper. Firstly, the original image is respectively processed by bilateral filter and local entropy, and then the two processed images are fused by point product to generate the background suppression map. Secondly, the guided filter is used to further suppress the background and enhance the small target in the map. Thirdly, the small target is detected by the adaptive threshold in the filtered map. The theoretical analyses and experimental results show that the proposed method not only effectively suppresses the clutter background, depending on the edge preserving and denoising characteristics of bilateral filtering, but also effectively highlights the small target, relying on the sensitivity of local entropy to the abrupt gray region. Compared with other methods, it is demonstrated that the proposed method owns lower false alarm rate and higher detection rate.
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Bouchelaghem, H. E., M. Hamadouche, F. Soltani, and K. Baddari. "Distributed Clutter-Map Constant False Alarm Rate Detection Using Fuzzy Fusion Rules." Radioelectronics and Communications Systems 62, no. 1 (January 2019): 1–5. http://dx.doi.org/10.3103/s0735272719010011.
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Uzair, Muhammad, Russell S. A. Brinkworth, and Anthony Finn. "Detecting Small Size and Minimal Thermal Signature Targets in Infrared Imagery Using Biologically Inspired Vision." Sensors 21, no. 5 (March 5, 2021): 1812. http://dx.doi.org/10.3390/s21051812.
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Thermal infrared imaging provides an effective sensing modality for detecting small moving objects at long range. Typical challenges that limit the efficiency and robustness of the detection performance include sensor noise, minimal target contrast and cluttered backgrounds. These issues become more challenging when the targets are of small physical size and present minimal thermal signatures. In this paper, we experimentally show that a four-stage biologically inspired vision (BIV) model of the flying insect visual system have an excellent ability to overcome these challenges simultaneously. The early two stages of the model suppress spatio-temporal clutter and enhance spatial target contrast while compressing the signal in a computationally manageable bandwidth. The later two stages provide target motion enhancement and sub-pixel motion detection capabilities. To show the superiority of the BIV target detector over existing traditional detection methods, we perform extensive experiments and performance comparisons using high bit-depth, real-world infrared image sequences of small size and minimal thermal signature targets at long ranges. Our results show that the BIV target detector significantly outperformed 10 conventional spatial-only and spatiotemporal methods for infrared small target detection. The BIV target detector resulted in over 25 dB improvement in the median signal-to-clutter-ratio over the raw input and achieved 43% better detection rate than the best performing existing method.
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Krolik, Jeffrey, and Granger Hickman. "Joint range-velocity estimation with continuous active sonar." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A243. http://dx.doi.org/10.1121/10.0016147.
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Active sonars using linear frequency-modulated (LFM) continuous waveforms are typically processed in sub-bands to facilitate high target range update rates. Target range-rate is then estimated using incoherently processed matched-filter outputs from each sub-band as input to a tracker. Target returns can easily be confused with clutter because sub-band width is typically chosen to avoid decoherence caused by target and/or platform motion. In this paper, we present methods for joint range-velocity estimation which allows for coherent combination of sub-band outputs and accounts for target/platform motion. The approach involves pre-filtering beamformed sub-band outputs using the transmitted LFM waveform, match-filtering each frequency-domain pre-filtered sub-band under a range-velocity hypothesis, and coherently combining the results. A maximum likelihood estimate (MLE) of range-velocity is formed which involves adaptively suppressing clutter and noise using an estimate of sub-band clutter covariance matrices. Simulation results are presented which indicate that joint range-velocity estimation using coherent processing across sub-bands offers a significant improvement over conventional methods and allows for more flexible selection of sub-band processing bandwidth. Moreover, the approach lends itself to handling the case of partial coherence across sub-bands and offers the potential for improved discrimination of slowly moving targets versus clutter discretes. Work supported by ONR.
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Do, Cong-Thanh, Tran Thien Dat Nguyen, and Weifeng Liu. "Tracking Multiple Marine Ships via Multiple Sensors with Unknown Backgrounds." Sensors 19, no. 22 (November 18, 2019): 5025. http://dx.doi.org/10.3390/s19225025.
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In multitarget tracking, knowledge of the backgrounds plays a crucial role in the accuracy of the tracker. Clutter and detection probability are the two essential background parameters which are usually assumed to be known constants although they are, in fact, unknown and time varying. Incorrect values of these parameters lead to a degraded or biased performance of the tracking algorithms. This paper proposes a method for online tracking multiple targets using multiple sensors which jointly adapts to the unknown clutter rate and the probability of detection. An effective filter is developed from parallel estimation of these parameters and then feeding them into the state-of-the-art generalized labeled multi-Bernoulli filter. Provided that the fluctuation of these unknown backgrounds is slowly-varying in comparison to the rate of measurement-update data, the validity of the proposed method is demonstrated via numerical study using multistatic Doppler data.
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Ni, Peishuang, Chen Miao, Hui Tang, Mengjie Jiang, and Wen Wu. "Small Foreign Object Debris Detection for Millimeter-Wave Radar Based on Power Spectrum Features." Sensors 20, no. 8 (April 18, 2020): 2316. http://dx.doi.org/10.3390/s20082316.
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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.