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    CFAR adaptive threshold for ESM receiver with logarithmic amplification

    , Article Signal Processing ; Volume 84, Issue 1 , 2004 , Pages 41-53 ; 01651684 (ISSN) Khalighi, M. A ; Nayebi, M. M ; Sharif University of Technology
    An adaptive threshold with constant false alarm rate (CFAR) property is proposed to be used in a channelized electronic support measures (ESM) system with logarithmic video amplification. For this purpose, two CFAR processors are designed which are in fact modified excision (MEx) and adaptive MEx (AMEx) processors, previously presented by authors, but modified for the logarithmic amplification case. In the case of relatively small variations in the noise power, MEx-LOG/CFAR is proposed. This processor exhibits a good robustness against interfering pulses, which cause the major difficulty in the estimation of noise statistics. In the case of relatively large variations in the noise power,... 

    Robust Wiener filter-based time gating method for detection of shallowly buried objects

    , Article IET Signal Processing ; 2021 ; 17519675 (ISSN) Gharamohammadi, A ; Behnia, F ; Shokouhmand, A ; Shaker, G ; Sharif University of Technology
    Institution of Engineering and Technology  2021
    A robust method for ultra-wideband (UWB) imaging of buried shallow objects based on time gating, Wiener filtering, as well as constant false alarm rate (CFAR) is proposed. Moreover, it is demonstrated that Wiener filtering can be used as a clutter removal tool in UWB signal applications. Basically, the problem with time gating method is that the length of the timing window for unknown targets cannot be determined accurately in advance. In fact, it is a blind methodology and some targets can be missed due to a lack of pre-knowledge about their depth. Imprecise window length selection leads to missing some parts of the target signals along with the clutter, which in turn increases the missed... 

    A new technique in passive coherent radar signal processing

    , Article EURAD 2005 - 2nd European Radar Conference, Paris, 6 October 2005 through 7 October 2005 ; Volume 2005 , 2005 , Pages 149-151 ; 2960055136 (ISBN); 9782960055139 (ISBN) Borhani, M ; Sedghi, V ; Nayebi, M. M ; Sharif University of Technology
    IEEE Computer Society  2005
    In this paper, we focus on adaptive and wavelet based systems in radar signal processing, and a new algorithm to Doppler compensation is developed. The new wavelet-based method for ambiguity surface smoothing that applies the three dimensions dual tree wavelet transform and adapt constant false alarm rate, is proposed. The model captures the dependence between a wavelet coefficient and its parent. Simulation results show that new approach is better than older algorithms. We have simulated this new method for bistatic FM-based passive coherent receiver  

    Multi-antenna assisted spectrum sensing in spatially correlated noise environments

    , Article Signal Processing ; Volume 108 , December , 2015 , Pages 69-76 ; 01651684 (ISSN) Koochakzadeh, A ; Malek Mohammadi, M ; Babaie Zadeh, M ; Skoglund, M ; Sharif University of Technology
    Elsevier  2015
    A significant challenge in spectrum sensing is to lessen the signal to noise ratio needed to detect the presence of primary users while the noise level may also be unknown. To meet this challenge, multi-antenna based techniques possess a greater efficiency compared to other algorithms. In a typical compact multi-antenna system, due to small interelement spacing, mutual coupling between thermal noises of adjacent receivers is significant. In this paper, unlike most of the spectrum sensing algorithms which assume spatially uncorrelated noise, the noises on the adjacent antennas can have arbitrary correlations. Also, in contrast to some other algorithms, no prior assumption is made on the... 

    KNNDIST: A non-parametric distance measure for speaker segmentation

    , Article 13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012 ; Volume 3 , 2012 , Pages 2279-2282 ; 9781622767595 (ISBN) Mohammadi, S. H ; Sameti, H ; Langarani, M. S. E ; Tavanaei, A ; Sharif University of Technology
    A novel distance measure for distance-based speaker segmentation is proposed. This distance measure is nonparametric, in contrast to common distance measures used in speaker segmentation systems, which often assume a Gaussian distribution when measuring the distance between two audio segments. This distance measure is essentially a k-nearest-neighbor distance measure. Non-vowel segment removal in preprocessing stage is also proposed. Speaker segmentation performance is tested on artificially created conversations from the TIMIT database and two AMI conversations. For short window lengths, Missed Detection Rated is decreased significantly. For moderate window lengths, a decrease in both... 

    Image steganalysis based on SVD and noise estimation: Improve sensitivity to spatial LSB embedding families

    , Article IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21 November 2011 through 24 November 2011, Bali ; 2011 , Pages 1266-1270 ; 9781457702556 (ISBN) Diyanat, A ; Farhat, F ; Ghaemmaghami, S ; Sharif University of Technology
    We propose a novel image steganalysis method, based on singular value decomposition and noise estimation, for the spatial domain LSB embedding families. We first define a content independence parameter, DS, that is calculated for each LSB embedding rate. Next, we estimate the DS curve and use noise estimation to improve the curve approximation accuracy. It is shown that the proposed approach gives an estimate of the LSB embedding rate, as well as information about the existence of the embedded message (if any). The proposed method can effectively be applied to a wide range of the image LSB steganography families in spatial domain. To evaluate the proposed scheme, we applied the method to a... 

    Critical object recognition in millimeter-wave images with robustness to rotation and scale

    , Article Journal of the Optical Society of America A: Optics and Image Science, and Vision ; Volume 34, Issue 6 , 2017 , Pages 846-855 ; 10847529 (ISSN) Mohammadzade, H ; Ghojogh, B ; Faezi, S ; Shabany, M ; Sharif University of Technology
    OSA - The Optical Society  2017
    Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper... 

    Non-coherent radar CFAR detection based on goodness-of-fit tests

    , Article IET Radar, Sonar and Navigation ; Volume 1, Issue 2 , 2007 , Pages 98-105 ; 17518784 (ISSN) Norouzi, Y ; Gini, F ; Nayebi, M. M ; Greco, M ; Sharif University of Technology
    This paper considers the problem of constant false alarm rate (CFAR) detection of radar targets using multiple observations. In the Gaussian clutter scenario, the structure of the optimum (uniformly most powerful) CFAR detector is rather simple, but when the clutter is heavy-tailed, that is non-Gaussian distributed, the derivation of the optimal detector becomes infeasible. For this latter relevant case, a new CFAR algorithm is porposed based on goodness-of-fit (GoF) tests. The performance of the proposed detector is numerically investigated through Monte Carlo simulations assuming heavy-tailed Weibull and Lognormal distributed clutter. Numerical results shown that, in heavy-tailed clutter... 

    Detection of a band-limited signal using an orthonormal, fully-decimated filter-bank

    , Article Scientia Iranica ; Volume 14, Issue 6 , 2007 , Pages 555-565 ; 10263098 (ISSN) Derakhtian, M ; Tadaion, A. A ; Nayebi, M. M ; Aref, M. R ; Sharif University of Technology
    Sharif University of Technology  2007
    In this paper, two methods are proposed for the detection of a band-limited signal in unknown variance white Gaussian noise. The complex amplitude and the frequency of the signal and the noise variance are assumed as unknown parameters. Using wavelet concepts, an orthonormal, fully-decimated filter-bank is employed to decompose the signal into its subband components. It is shown that, in this process, the noise is also decomposed into orthonormal zero-mean components. In the output, if a band-limited target signal is present, the respective single subband component (or two components in marginal cases) containing the target signal presents a non-zero mean. The presence of a non-zero mean... 

    A robust CFAR detection with ML estimation

    , Article 2008 IEEE Radar Conference, RADAR 2008, Rome, 26 May 2008 through 30 May 2008 ; December , 2008 ; 9781424415397 (ISBN) Pourmottaghi, A ; Taban, M. R ; Norouzi, Y ; Sadeghi, M. T ; Sharif University of Technology
    Any clutter edge in the reference window of a radar CFAR detection, produces an error in the clutter power estimation which reduces the detectability of the cell under test (CUT). In processors such as OS-CFAR, the designers have attempted to improve the detection performance, nevertheless, none of these processors applies an intelligent method of clutter edge recognition and destroyer data elimination. Therefore any of these processors are effective in some especial cases of nonhomogeneous environment, but are deficient in other cases. In this paper an intelligent method is proposed for clutter edge recognition. This method determines the borders in which the clutter statistics are changing... 

    A Fast Soft Decision Algorithm for Cooperative Spectrum Sensing

    , Article IEEE Transactions on Circuits and Systems II: Express Briefs ; Volume 68, Issue 1 , 2021 , Pages 241-245 ; 15497747 (ISSN) Golvaei, M ; Fakharzadeh, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    Hidden Primary User problem caused by fading and shadowing severely affects the detection rate of the cognitive radio systems with a single spectrum sensor. Cooperative Spectrum Sensing has been introduced to tackle this problem by using the spatial diversity of spectrum sensors. It is shown that the use of soft decision algorithms in fusion center has a better performance than hard decision algorithms. The problem of soft decision based on sensor measurements perfectly matches the Machine Learning paradigm. In this brief, a novel fast soft decision algorithm is proposed based on Machine Learning theory for wideband Cooperative Spectrum Sensing, which finds a decision boundary to classify... 

    Life-threatening arrhythmia verification in ICU patients using the joint cardiovascular dynamical model and a bayesian filter

    , Article IEEE Transactions on Biomedical Engineering ; Volume 58, Issue 10 PART 1 , 2011 , Pages 2748-2757 ; 00189294 (ISSN) Sayadi, O ; Shamsollahi, M. B ; Sharif University of Technology
    In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,...