scholarly journals Estimation of K–Distributed Clutter by using Characteristic Function Method

2012 ◽  
Author(s):  
Mohammad Hamiruce Marhaban
Keyword(s):  
Characteristic Function ◽  
Function Method ◽  
Maximum Likelihood Method ◽  
Radar System ◽  
Likelihood Method ◽  
Empirical Characteristic Function ◽  
Sea Clutter ◽  
Novel Approach ◽  
Simulation Results ◽  
Distribution Parameter Estimation

Prestasi pengesanan radar maritim selalunya terbatas disebabkan gema laut atau serakan yang tidak diingini. Taburan-K adalah salah satu ketumpatan berekor panjang, di mana ia dikenali dalam komuniti pemprosesan isyarat untuk memadan dengan tepat serakan laut. Dalam kertas kerja ini, satu pendekatan novel untuk menganggar parameter taburan-K dibentangkan. Kaedah ini diterbitkan dari fungsi ciri empirik komponen quadrature. Hasil simulasi menunjukkan pembaikan yang ketara dari segi kecenderungan dan varians teranggar, berbanding dengan manamana kaedah bukan kemungkinan maksimum sedia ada. Kata kunci: Sistem radar, serakan laut, taburan–K, penganggaran parameter, fungsi ciri Detection performance of the maritime radars is often limited by the unwanted sea echo or clutter. K-distribution is one of the long-tailed densities which is known in the signal processing community for fitting the radar sea clutter accurately. In this paper, a novel approach for estimating the parameter of K-distribution is presented. The method is derived from the empirical characteristic function of the quadrature components. Simulation results show a great improvement in term of estimated bias and variance, compared with any existing non-maximum likelihood method. Key words: Radar system, sea clutter, K–distribution, parameter estimation, characteristic function

scholarly journals A Novel Deceptive Jamming Approach for Hiding Actual Target and Generating False Targets

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Shahid Mehmood ◽  
Aqdas Naveed Malik ◽  
Ijaz Manssor Qureshi ◽  
Muhammad Zafar Ullah Khan ◽  
Fawad Zaman
Keyword(s):  
Mathematical Model ◽  
Radiation Pattern ◽  
Radar System ◽  
The Novel ◽  
Novel Approach ◽  
Electronic Countermeasure ◽  
Deceptive Jamming ◽  
Frequency Diverse Array ◽  
Simulation Results ◽  
Actual Target

Deceptive jamming is a popular electronic countermeasure (ECM) technique that generates false targets to confuse opponent surveillance radars. This work presents a novel approach for hiding the actual target while producing multiple false targets at the same time against frequency diverse array (FDA) radar. For this purpose, the modified FDA radar is assumed to be mounted on the actual aircraft. It intercepts the opponent’s radar signals and transmits back to place nulls in the radiation pattern at the desired range and direction to exploit FDA radar’s range-dependent pattern nulling capability. The proposed deceptive jammer produces delayed versions of the intercepted signals to create false targets with multiple ranges to confuse the opponent’s radar system. The novel mathematical model is proposed whose effectiveness is verified through several simulation results for different numbers of ranges, directions, and antenna elements.

scholarly journals New Extension of Weibull Distribution: Copula, Mathematical Properties and Data Modeling

2020 ◽  
Vol 8 (4) ◽  
pp. 972-993
Author(s):  
Hanaa Elgohari ◽  
Haitham Yousof
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Likelihood Estimation ◽  
Likelihood Method ◽  
Model Parameters ◽  
Graphical Simulation ◽  
Mathematical Properties ◽  
Exponentiated Weibull ◽  
Lifetime Model ◽  
Simulation Results

This paper introduces a new flexible four-parameter lifetime model. Various of its structural properties are derived. The new density is expressed as a linear mixture of well-known exponentiated Weibull density. The maximum likelihood method is used to estimate the model parameters. Graphical simulation results to assess the performance of the maximum likelihood estimation are performed. We proved empirically the importance and flexibility of the new model in modeling four various types of data.

scholarly journals Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Mohammed Benmoumen ◽  
Jelloul Allal ◽  
Imane Salhi
Keyword(s):  
Parameter Estimation ◽  
Simulated Annealing ◽  
Kalman Filter ◽  
Maximum Likelihood Method ◽  
Random Coefficient ◽  
Likelihood Method ◽  
Simulation Results ◽  
Quasi Maximum Likelihood ◽  
Annealing Method ◽  
Random Coefficient Autoregressive

In this paper we elaborate an algorithm to estimate p-order Random Coefficient Autoregressive Model (RCA(p)) parameters. This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. In the aim to generalize the results found for RCA(1), we have integrated a subalgorithm which calculate the theoretical autocorrelation. Simulation results demonstrate that the algorithm is viable and promising.

scholarly journals On the Omega Distribution: Some Properties and Estimation

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 656
Author(s):  
Abdelaziz Alsubie ◽  
Zuber Akhter ◽  
Haseeb Athar ◽  
Mahfooz Alam ◽  
Abd EL-Baset A. Ahmad ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Order Statistics ◽  
Maximum Likelihood Method ◽  
Real Data ◽  
Likelihood Method ◽  
Type Ii ◽  
Data Set ◽  
Simulation Results ◽  
Censoring Scheme ◽  
Single And Product Moments

We obtain explicit expressions for single and product moments of the order statistics of an omega distribution. We also discuss seven methods to estimate the omega parameters. Various simulation results are performed to compare the performance of the proposed estimators. Furthermore, the maximum likelihood method is adopted to estimate the omega parameters under the type II censoring scheme. The usefulness of the omega distribution is proven using a real data set.

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

The co-responsibility of mass and environment in the formation of lenticular galaxies

2020 ◽  
Vol 15 (S359) ◽  
pp. 173-174
Author(s):  
A. Cortesi ◽  
L. Coccato ◽  
M. L. Buzzo ◽  
K. Menéndez-Delmestre ◽  
T. Goncalves ◽  
...  
Keyword(s):  
Active Galactic Nuclei ◽  
Maximum Likelihood Method ◽  
Spiral Galaxies ◽  
Galactic Nuclei ◽  
Rotation Velocity ◽  
Elliptical Galaxies ◽  
Likelihood Method ◽  
Data Set ◽  
Lenticular Galaxies ◽  
Galaxies Kinematics

AbstractWe present the latest data release of the Planetary Nebulae Spectrograph Survey (PNS) of ten lenticular galaxies and two spiral galaxies. With this data set we are able to recover the galaxies’ kinematics out to several effective radii. We use a maximum likelihood method to decompose the disk and spheroid kinematics and we compare it with the kinematics of spiral and elliptical galaxies. We build the Tully- Fisher (TF) relation for these galaxies and we compare with data from the literature and simulations. We find that the disks of lenticular galaxies are hotter than the disks of spiral galaxies at low redshifts, but still dominated by rotation velocity. The mechanism responsible for the formation of these lenticular galaxies is neither major mergers, nor a gentle quenching driven by stripping or Active Galactic Nuclei (AGN) feedback.

On the first zero of an empirical characteristic function

1991 ◽  
Vol 28 (3) ◽  
pp. 593-601 ◽  
Author(s):  
H. U. Bräker ◽  
J. Hüsler
Keyword(s):  
Characteristic Function ◽  
Limit Distribution ◽  
Random Variable ◽  
Empirical Characteristic Function ◽  
The Real ◽  
Exponential Decrease ◽  
Characteristic Process

We deal with the distribution of the first zero Rn of the real part of the empirical characteristic process related to a random variable X. Depending on the behaviour of the theoretical real part of the underlying characteristic function, cases with a slow exponential decrease to zero are considered. We derive the limit distribution of Rn in this case, which clarifies some recent results on Rn in relation to the behaviour of the characteristic function.

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