A Developed ESPRIT Algorithm for DOA Estimation

Frequenz ◽  
2015 ◽  
Vol 69 (5-6) ◽  
Author(s):  
Youssef Fayad ◽  
Caiyun Wang ◽  
Qunsheng Cao ◽  
Alaa El-Din Sayed Hafez
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Performance Enhancement ◽  
Doa Estimation ◽  
Signal Parameter ◽  
Nonlinearity Effect ◽  
Esprit Algorithm ◽  
Cramer Rao Bound ◽  
Novel Algorithm ◽  
Better Than

AbstractA novel algorithm for estimating direction of arrival (DOAE) for target, which aspires to contribute to increase the estimation process accuracy and decrease the calculation costs, has been carried out. It has introduced time and space multiresolution in Estimation of Signal Parameter via Rotation Invariance Techniques (ESPRIT) method (TS-ESPRIT) to realize subspace approach that decreases errors caused by the model’s nonlinearity effect. The efficacy of the proposed algorithm is verified by using Monte Carlo simulation, the DOAE accuracy has evaluated by closed-form Cramér–Rao bound (CRB) which reveals that the proposed algorithm’s estimated results are better than those of the normal ESPRIT methods leading to the estimator performance enhancement.

scholarly journals Direction of Arrival Estimation Accuracy Enhancement via Using Displacement Invariance Technique

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Youssef Fayad ◽  
Caiyun Wang ◽  
Qunsheng Cao ◽  
Alaa El-Din Sayed Hafez
Keyword(s):  
Performance Enhancement ◽  
Doppler Frequency ◽  
Direction Of Arrival ◽  
Estimation Accuracy ◽  
Direction Of Arrival Estimation ◽  
Target Movement ◽  
Nonlinearity Effect ◽  
Esprit Algorithm ◽  
Cramer Rao Bound ◽  
Better Than

A new algorithm for improving Direction of Arrival Estimation (DOAE) accuracy has been carried out. Two contributions are introduced. First, Doppler frequency shift that resulted from the target movement is estimated using the displacement invariance technique (DIT). Second, the effect of Doppler frequency is modeled and incorporated into ESPRIT algorithm in order to increase the estimation accuracy. It is worth mentioning that the subspace approach has been employed into ESPRIT and DIT methods to reduce the computational complexity and the model’s nonlinearity effect. The DOAE accuracy has been verified by closed-form Cramér-Rao bound (CRB). The simulation results of the proposed algorithm are better than those of the previous estimation techniques leading to the estimator performance enhancement.

A theoretical model of jump diffusion-mean reversion

2017 ◽  
Vol 23 (3) ◽  
pp. 537-554
Author(s):  
Anindya Chakrabarty ◽  
Zongwei Luo ◽  
Rameshwar Dubey ◽  
Shan Jiang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Theoretical Model ◽  
Interest Rate ◽  
Mean Reversion ◽  
Jump Diffusion ◽  
Fixed Income ◽  
Short Term ◽  
Content Type ◽  
Better Than

Purpose The purpose of this paper is to develop a theoretical model of a jump diffusion-mean reversion constant proportion portfolio insurance strategy under the presence of transaction cost and stochastic floor as opposed to the deterministic floor used in the previous literatures. Design/methodology/approach The paper adopts Merton’s jump diffusion (JD) model to simulate the price path followed by risky assets and the CIR mean reversion model to simulate the path followed by the short-term interest rate. The floor of the CPPI strategy is linked to the stochastic process driving the value of a fixed income instrument whose yield follows the CIR mean reversion model. The developed model is benchmarked against CNX-NIFTY 50 and is back tested during the extreme regimes in the Indian market using the scenario-based Monte Carlo simulation technique. Findings Back testing the algorithm using Monte Carlo simulation across the crisis and recovery phases of the 2008 recession regime revealed that the portfolio performs better than the risky markets during the crisis by hedging the downside risk effectively and performs better than the fixed income instruments during the growth phase by leveraging on the upside potential. This makes it a value-enhancing proposition for the risk-averse investors. Originality/value The study modifies the CPPI algorithm by re-defining the floor of the algorithm to be a stochastic mean reverting process which is guided by the movement of the short-term interest rate in the economy. This development is more relevant for two reasons: first, the short-term interest rate changes with time, and hence the constant yield during each rebalancing steps is not practically feasible; second, the historical literatures have revealed that the short-term interest rate tends to move opposite to that of the equity market. Thereby, during the bear run the floor will increase at a higher rate, whereas the growth of the floor will stagnate during the bull phase which aids the model to capitalize on the upward potential during the growth phase and to cut down on the exposure during the crisis phase.

Conservative Surrogate Model Using Weighted Kriging Variance for Sampling-Based RBDO

2013 ◽  
Vol 135 (9) ◽  
Author(s):  
Liang Zhao ◽  
K. K. Choi ◽  
Ikjin Lee ◽  
David Gorsich
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Optimum Design ◽  
Surrogate Model ◽  
Large Scale ◽  
Prediction Interval ◽  
Safety Margin ◽  
Probabilistic Constraints ◽  
Kriging Variance ◽  
Better Than

In sampling-based reliability-based design optimization (RBDO) of large-scale engineering applications, the Monte Carlo simulation (MCS) is often used for the probability of failure calculation and probabilistic sensitivity analysis using the prediction from the surrogate model for the performance function evaluations. When the number of samples used to construct the surrogate model is not enough, the prediction from the surrogate model becomes inaccurate and thus the Monte Carlo simulation results as well. Therefore, to count in the prediction error from the surrogate model and assure the obtained optimum design from sampling-based RBDO satisfies the probabilistic constraints, a conservative surrogate model, which is not overly conservative, needs to be developed. In this paper, a conservative surrogate model is constructed using the weighted Kriging variance where the weight is determined by the relative change in the corrected Akaike Information Criterion (AICc) of the dynamic Kriging model. The proposed conservative surrogate model performs better than the traditional Kriging prediction interval approach because it reduces fluctuation in the Kriging prediction bound and it performs better than the constant safety margin approach because it adaptively accounts large uncertainty of the surrogate model in the region where samples are sparse. Numerical examples show that using the proposed conservative surrogate model for sampling-based RBDO is necessary to have confidence that the optimum design satisfies the probabilistic constraints when the number of samples is limited, while it does not lead to overly conservative designs like the constant safety margin approach.

scholarly journals Genetic Algorithm based Optimization of Uniform Circular Array

2020 ◽  
Vol 10 (6) ◽  
pp. 6403-6409
Author(s):  
V. Kumar ◽  
S. K. Dhull
Keyword(s):  
Genetic Algorithm ◽  
Signal Classification ◽  
Circular Array ◽  
Signal Parameter ◽  
Multiple Signal Classification ◽  
First Order ◽  
Forward Prediction ◽  
Array Structure ◽  
Esprit Algorithm ◽  
Better Than

Signal estimation at the antenna is a major challenge of the antenna array structure because the received signals have different directions. Therefore, in this paper, a Genetic Algorithm (GA) is applied to the uniform circular array for the optimization of array structure in regard to its geometry. On the optimized array structure, four different algorithms (Estimation of Signal Parameter via Rotational Invariance Technique – ESPRIT, First Order Forward Prediction - FOFP, Beamscan, and Multiple Signal Classification - MUSIC) have been implemented in order to estimate the signal direction accurately with quick estimation time. The accuracy has been calculated with Root Mean Square Error (RMSE) indices. From the experimental analysis, it has been found that the performance of the ESPRIT algorithm is better than the others in terms of accuracy and estimation time.

scholarly journals Expectations on mass determination using astrometric microlensing by Gaia

2020 ◽  
Vol 640 ◽  
pp. A83
Author(s):  
J. Klüter ◽  
U. Bastian ◽  
J. Wambsganss
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Mass Determination ◽  
Single Star ◽  
Data Release ◽  
The Absolute ◽  
The Individual ◽  
Background Star ◽  
Better Than ◽  
Do So

Context. Astrometric gravitational microlensing can be used to determine the mass of a single star (the lens) with an accuracy of a few percent. To do so, precise measurements of the angular separations between lens and background star with an accuracy below 1 milli − arcsec at different epochs are needed. Therefore only the most accurate instruments can be used. However, since the timescale is on the order of months to years, the astrometric deflection might be detected by Gaia, even though each star is only observed on a low cadence. Aims. We want to show how accurately Gaia can determine the mass of the lensing star. Methods. Using conservative assumptions based on the results of the second Gaia data release (Gaia DR2), we simulated the individual Gaia measurements for 501 predicted astrometric microlensing events during the Gaia era (2014.5–2026.5). For this purpose we used the astrometric parameters of Gaia DR2, as well as an approximative mass based on the absolute G magnitude. By fitting the motion of the lens and source simultaneously, we then reconstructed the 11 parameters of the lensing event. For lenses passing by multiple background sources, we also fitted the motion of all background sources and the lens simultaneously. Using a Monte-Carlo simulation we determined the achievable precision of the mass determination. Results. We find that Gaia can detect the astrometric deflection for 114 events. Furthermore, for 13 events Gaia can determine the mass of the lens with a precision better than 15% and for 13 + 21 = 34 events with a precision of 30% or better.

scholarly journals Optimal Regimens and Cutoff Evaluation of Ceftiofur Against Actinobacillus pleuropneumoniae in Swine

2020 ◽  
Author(s):  
Da Sun ◽  
Kun Mi ◽  
Haihong Hao ◽  
Shuyu Xie ◽  
Dongmei Chen ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ex Vivo ◽  
Actinobacillus Pleuropneumoniae ◽  
Cutoff Value ◽  
Gram Positive Bacteria ◽  
Cephalosporin Antibiotic ◽  
Emergence Of Resistance ◽  
Better Than

Abstract BackgroundActinobacillus pleuropneumoniae, formerly known as Haemophilus pleuropneumoniae, can cause pleuropneumoniae in pigs of different ages, leading to significant mortality. Ceftiofur was the first cephalosporin antibiotic used in animals that was effective against gram-negative and gram-positive bacteria. This study aimed to determine the breakpoint of ceftiofur against Actinobacillus pleuropneumoniae based on the investigation of the epidemiologic cutoff value (ECV), and pharmacodynamic-pharmacokinetic breakpoint.ResultsThe epidemiologic cutoff value was 0.125 µg/mL. The results of the pharmacodynamic study showed that the MICs of BW39 were 0.5 µg/mL and 1 µg/mL under in vitro and ex-vivo conditions, respectively, and the minimal bactericidal concentrations (MBCs) under in vitro and ex vivo conditions were both 1 µg/mL. The time-killing profiles of ceftiofur against BW39 were time-dependent. According to the inhibitory sigmoid Emax model, the AUC24 h/MIC values for the bacteriostatic, bactericidal, and elimination effects in serum were 45.73, 63.83, and 69.04 h for healthy pigs, respectively. Based on the Monte Carlo simulation, the COPD was calculated as 2 µg/mL, and the optimized dosage regimen of ceftiofur against Actinobacillus pleuropneumoniae to achieve bacteriostatic, bactericidal, and elimination effects over 24 h was 2.13, 2.97, and 3.42 mg/kg for the 50% target attainment rate (TAR) and 2.47, 3.21, and 3.70 mg/kg for the 90% TAR, respectively.ConclusionsIn this study, the epidemiologic cutoff value was 0.125 µg/mL, as calculated by ECOFFinder software. According to the PK/PD evaluation in vitro and ex vivo, the value of the pharmacodynamics cutoff was 2 µg/mL, as obtained by Monte Carlo simulation. The COPD suggested that the breakpoint could be better than the COWT value because COPD derived from PL/PD data was obtained in vitro and ex vivo, which was more significant. According to the PK/PD parameters, the single bactericidal dose was 3.21 mg/kg for the 90% target, which would be more available to cure Actinobacillus pleuropneumoniae and avoid the emergence of resistance for clinical ceftiofur use.

scholarly journals Effectiveness of Geant4 in Monte Carlo Simulation Studyofphonon Conduction in Sn Host with Si Nanowire Interface

2019 ◽  
Vol 61 (1) ◽  
pp. 12-21
Author(s):  
C. Iheduru ◽  
M. A. Eleruja ◽  
B. Olofinjana ◽  
O. E. Awe ◽  
A.D.A Buba
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Performance Enhancement ◽  
Low Cost ◽  
Geant4 Simulation ◽  
Time Step ◽  
Si Nanowire ◽  
Average Temperature ◽  
Numerical Predictions ◽  
Phonon Conduction

AbstractWe have explored the effectiveness of Geant4 by using it to simulate phonon conduction in Sn Host with Si Nanowire Interface. Our Monte Carlo Simulation shows that the effectiveness of the phonon conduction Geant4 simulation increases when the system attained a steady state of 100 time steps. We have simulated phonon conduction in Sn host with Si nanowire interface using a Geant4Condensed Matter Physics Monte Carlo simulation toolkit in a low cost and less powerful processing computer machine. In the simulation, phonons were displaced inside a computation domain from their initial positions with the velocities and direction vectors assigned to them. A time step was selected so that a phonon can move at most the length of one sub-cell in one time step. Our phonon conduction analysis of SiSn based alloy using Geant4 showed performance enhancement and reasonable predicted thermal values. Numerical predictions of the thermal profile simulations of the values of the temperature in each cell were all within ten percent of the average temperature of Silicon – Tin.

scholarly journals Monte Carlo Simulation Of The Portfolio-Balance Model Of Exchange Rates: Finite Sample Properties Of The GMM Estimator

2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Hong-Ghi Min
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Exchange Rates ◽  
Balance Model ◽  
Finite Sample ◽  
Gmm Estimator ◽  
Portfolio Balance ◽  
Finite Sample Properties ◽  
Chi Squared ◽  
Better Than

Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.

Two-Dimensional DOA Estimation for Planar Array Using a Successive Propagator Method

2019 ◽  
Vol 28 (10) ◽  
pp. 1950161 ◽  
Author(s):  
Weiyang Chen ◽  
Xiaofei Zhang ◽  
Chi Jiang
Keyword(s):  
Computational Cost ◽  
Doa Estimation ◽  
Rotational Invariance ◽  
Eigenvalue Decomposition ◽  
Invariance Property ◽  
Two Dimensional ◽  
Propagator Method ◽  
Planar Array ◽  
Esprit Algorithm ◽  
Better Than

We consider the problem of two-dimensional (2D) direction of arrival (DOA) estimation for planar array, and propose a successive propagator method (PM)-based algorithm. The rotational invariance property of the propagator matrix is exploited to obtain the initial angle estimations, while the accurate estimates can be achieved through successive one-dimensional and local spectrum-peak searches. The proposed algorithm can obtain automatically paired 2D-DOA estimations, and it requires no eigenvalue decomposition of the covariance matrix of received data, which remarkably reduces the computational cost compared with traditional 2D-PM algorithm. In addition, the DOA estimation performance of the proposed algorithm is better than estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm and PM algorithm, and is close to 2D-PM algorithm which requires 2D spectrum-peak search. Numerical simulations demonstrate the effectiveness and improvement of the proposed algorithm.

scholarly journals A GEANT-BASED STUDY OF ATMOSPHERIC NEUTRINO OSCILLATION PARAMETERS AT INO

2008 ◽  
Vol 23 (02) ◽  
pp. 233-245 ◽  
Author(s):  
ABHIJIT SAMANTA ◽  
SUDEB BHATTACHARYA ◽  
AMBAR GHOSAL ◽  
KAMALES KAR ◽  
DEBASISH MAJUMDAR ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Neutrino Oscillation ◽  
Atmospheric Neutrino ◽  
Experimental Results ◽  
Detector Response ◽  
Chi Square ◽  
Iron Calorimeter ◽  
Chi Square Analysis ◽  
Better Than

We have studied the dependence of the allowed space of the atmospheric neutrino oscillation parameters on the time of exposure for a magnetized Iron CALorimeter (ICAL) detector at the India-based Neutrino Observatory (INO). We have performed a Monte Carlo simulation for a 50 kTon ICAL detector generating events by the neutrino generator NUANCE and simulating the detector response by GEANT. A chi-square analysis for the ratio of the up-going and down-going neutrinos as a function of L/E is performed and the allowed regions at 90% and 99% CL are displayed. These results are found to be better than the current experimental results of MINOS and Super-K. The possibilities of further improvement have also been discussed.

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