scholarly journals A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

2017 ◽  
Author(s):  
Yixiong Zhang ◽  
Rujia Hong ◽  
Cheng-Fu Yang ◽  
Yunjian Zhang ◽  
Zhenmiao Deng ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Computational Cost ◽  
Estimation Method ◽  
Doppler Frequency ◽  
Parameters Estimation ◽  
Estimation Methods ◽  
Radar Systems ◽  
Isar Imaging ◽  
Motion Parameters ◽  
Wideband Radar

In wideband radar systems, the performance of motion parameters estimation can significantly affect the performance of object detection and the quality of inverse synthetic aperture radar (ISAR) imaging. Although the traditional motion parameters estimation methods can reduce the range migration (RM) and Doppler frequency migration (DFM) effects in ISAR imaging, the computational complexity is high. In this paper, we propose a new fast non-searching motion parameters estimation method based on cross-correlation of adjacent echoes (CCAE) for wideband LFM signals. A cross-correlation operation is carried out for two adjacent echo signals, then the motion parameters can be calculated by estimating the frequency of the correlation result. The proposed CCAE method can be applied directly to the stretching system, which is commonly adopted in wideband radar systems. Simulational results demonstrate that the new method can achieve better estimation performances, with much lower computational cost, compared with existing methods. The experimental results on real radar data sets are also evaluated to verify the effectiveness and superiority of the proposed method compared to the state-of-the-art existing methods.

scholarly journals A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

2017 ◽  
Vol 7 (5) ◽  
pp. 500 ◽  
Author(s):  
Yi-Xiong Zhang ◽  
Ru-Jia Hong ◽  
Cheng-Fu Yang ◽  
Yun-Jian Zhang ◽  
Zhen-Miao Deng ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Fast Motion ◽  
Motion Parameters

scholarly journals A Fast and Accurate Guessing Entropy Estimation Algorithm for Full-key Recovery

2020 ◽  
pp. 26-48
Author(s):  
Ziyue Zhang ◽  
A. Adam Ding ◽  
Yunsi Fei
Keyword(s):  
Experimental Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Security Evaluation ◽  
Side Channel ◽  
Data Sets ◽  
Key Recovery ◽  
Entropy Estimation

Guessing entropy (GE) is a widely adopted metric that measures the average computational cost needed for a successful side-channel analysis (SCA). However, with current estimation methods where the evaluator has to average the correct key rank over many independent side-channel leakage measurement sets, full-key GE estimation is impractical due to its prohibitive computing requirement. A recent estimation method based on posterior probabilities, although scalable, is not accurate.We propose a new guessing entropy estimation algorithm (GEEA) based on theoretical distributions of the ranking score vectors. By discovering the relationship of GE with pairwise success rates and utilizing it, GEEA uses a sum of many univariate Gaussian probabilities instead of multi-variate Gaussian probabilities, significantly improving the computation efficiency.We show that GEEA is more accurate and efficient than all current GE estimations. To the best of our knowledge, it is the only practical full-key GE evaluation on given experimental data sets which the evaluator has access to. Moreover, it can accurately predict the GE for larger sizes than the experimental data sets, providing comprehensive security evaluation.

scholarly journals An Accurate and Efficient Time Delay Estimation Method of Ultra-High Frequency Signals for Partial Discharge Localization in Substations

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3439 ◽  
Author(s):  
Pengfei Li ◽  
Kejie Dai ◽  
Tong Zhang ◽  
Yantao Jin ◽  
Yushun Liu ◽  
...  
Keyword(s):  
Time Delay ◽  
High Frequency ◽  
Cross Correlation ◽  
Partial Discharge ◽  
Estimation Method ◽  
Time Delay Estimation ◽  
Estimation Methods ◽  
Zero Crossing ◽  
Ultra High Frequency ◽  
Correlation Algorithm

Partial discharge (PD) localization in substations based on the ultra-high frequency (UHF) method can be used to efficiently assess insulation conditions. Localization accuracy is affected by the accuracy of the time delay (TD) estimation, which is critical for PD localization in substations. A review of existing TD estimation methods indicates that there is a need to develop methods that are both accurate and computationally efficient. In this paper, a novel TD estimation method is proposed to improve both accuracy and efficiency. The TD is calculated using an improved cross-correlation algorithm based on full-wavefronts of array UHF signals, which are extracted using the minimum cumulative energy method and zero-crossing points searching methods. The cross-correlation algorithm effectively suppresses the TD error caused by differences between full-wavefronts. To verify the method, a simulated PD source test in a laboratory and a field test in a 220 kV substation were carried out. The results show that the proposed method is accurate even in case of low signal-to-noise ratio, but with greatly improved computational efficiency.

scholarly journals A Novel Robust Model Predictive Controller for Aerospace Three-Phase PWM Rectifiers

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2490 ◽  
Author(s):  
Tao Lei ◽  
Weiwei Tan ◽  
Guangsi Chen ◽  
Delin Kong
Keyword(s):  
Power System ◽  
Bayesian Estimation ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Least Square ◽  
Estimation Methods ◽  
Control Performance ◽  
Least Square Estimation ◽  
Three Phase ◽  
Pwm Rectifiers

This paper presents a novel Model Predictive Direct Power Control (MPDPC) approach for the pulse width modulation (PWM) rectifiers in the Aircraft Alternating Current Variable Frequency (ACVF) power system. The control performance of rectifiers may be largely affected by variations in the AC side impedance, especially for systems with limited power volume system. A novel idea for estimating the impedance variation based on the Bayesian estimation, using an algorithm embedded in MPDPC is presented in this paper. The input filter inductance and its equivalent series resistance (ESR) of PWM rectifiers are estimated in this algorithm by measuring the input current and input voltage in each cycle with the probability Bayesian estimation theory. This novel estimation method can overcome the shortcomings of traditional data based estimation methods such as least square estimation (LSE), which achieves poor estimation results with the small samples data set. In ACVF systems, the effect on the parameters estimation accuracy caused by the number of sampling points in one cycle is also analyzed in detail by simulation. The validity of this method is verified by the digital and Hard-in-loop simulation compared with other estimation methods such as the least square estimation method. The experimental testing results show that the proposed estimation algorithm can improve the robustness and the control performance of the MPDPC under the condition of the uncertainty of the AC side parameters of the three-phase PWM rectifiers in aircraft electrical power system.

scholarly journals Statistical Analysis of Target Detection using TRTSGRFT

2019 ◽  
Vol 8 (3) ◽  
pp. 6570-6573
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Statistical Analysis ◽  
Target Detection ◽  
Computational Cost ◽  
Doppler Frequency ◽  
Maneuvering Target ◽  
Novel Method ◽  
Range Migration ◽  
Motion Parameters

This paper proposes novel methodology for target detection and motion parameter estimation for a maneuvering target. Noise like interference may inculcate few difficulties such as Range Migration (RM) and Doppler Frequency Migration (DFM). This paper proposes a novel method to overcome the issue. The method is to use Time Reversing Transform (TRT) and special generalized Radon Fourier transform (SGRFT), i.e., TRT-SGRFT. TRT separates the motion parameters and reduces the clutter. Then the SGRFT operation is employed to estimate part of the motion parameters. This method ensures a good tradeoff between the computational cost and estimation performance. Finally, simulations results are discussed to demonstrate the numerical results.

Different inference approaches for the estimators of the sushila distribution

2021 ◽  
Vol 16 (4) ◽  
pp. 251-260
Author(s):  
Marcos Vinicius de Oliveira Peres ◽  
Ricardo Puziol de Oliveira ◽  
Edson Zangiacomi Martinez ◽  
Jorge Alberto Achcar
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Bayesian Method ◽  
Weighted Least Squares ◽  
Computational Cost ◽  
Estimation Method ◽  
Computation Time ◽  
Ordinary Least Squares ◽  
Likelihood Method ◽  
Estimation Methods

In this paper, we order to evaluate via Monte Carlo simulations the performance of sample properties of the estimates of the estimates for Sushila distribution, introduced by Shanker et al. (2013). We consider estimates obtained by six estimation methods, the known approaches of maximum likelihood, moments and Bayesian method, and other less traditional methods: L-moments, ordinary least-squares and weighted least-squares. As a comparison criterion, the biases and the roots of mean-squared errors were used through nine scenarios with samples ranging from 30 to 300 (every 30rd). In addition, we also considered a simulation and a real data application to illustrate the applicability of the proposed estimators as well as the computation time to get the estimates. In this case, the Bayesian method was also considered. The aim of the study was to find an estimation method to be considered as a better alternative or at least interchangeable with the traditional maximum likelihood method considering small or large sample sizes and with low computational cost.

A RESPIRATORY MECHANICAL PARAMETERS ESTIMATION TECHNOLOGY BASED ON EXTENDED LEAST SQUARES

2016 ◽  
Vol 16 (03) ◽  
pp. 1650028 ◽  
Author(s):  
YAN SHI ◽  
JINGLONG NIU ◽  
MAOLIN CAI ◽  
WEIQING XU
Keyword(s):  
Mathematical Model ◽  
Mechanical Ventilation ◽  
Least Squares ◽  
Ventilation System ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Noise Model ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Mechanical Parameters

Respiratory mechanical parameters of ventilated patients are usually referred in the respiratory diagnosis and treatment. However, the effectiveness of the modern estimation methods is limited. To estimate the overall breathing resistance, overall respiratory compliance, and residual volume simultaneously, a new mathematical model of mechanical ventilation system was proposed. Furthermore, to improve the estimation accuracy, the noise model of mechanical ventilation system was taken into consideration. Based on the mathematical model, a respiratory mechanical parameters estimation method based on extended least squares (ELS) algorithm was derived. Finally, to test the respiratory mechanical parameters estimation method, it was studied experimentally and numerically, and it was approved that the proposed method is effective to estimate the three respiratory mechanical parameters simultaneously and precisely. The estimated values of the parameters can be adopted in the clinical practice. The study provides a new method to estimate respiratory mechanical parameters.

scholarly journals Parameter Estimation of Chirp for Underwater Acoustic Channel

2018 ◽  
Vol 173 ◽  
pp. 03044
Author(s):  
FAN Junhui ◽  
PENG Hua ◽  
WEI Chi
Keyword(s):  
Fourier Transform ◽  
Simulation Experiment ◽  
Fractional Fourier Transform ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Estimation Methods ◽  
Single Frequency ◽  
Chirp Rate ◽  
Underwater Acoustic ◽  
Initial Frequency

To overcome the performance degradation of conventional Chirp parameters estimation methods in underwater acoustic multipath channels, a novel parameters estimation method based on Fractional Fourier transform (FRFT) and Fourier transform (FFT) was proposed. Firstly, the Chirp rate was estimated by searching for the best degree of Chirp after Fractional Fourier transform. Secondly, the Chirp signal turned into a single-frequency signal by means of Chirp rate equalization. Finally, FFT was applied to estimate the initial frequency. The simulation experiment show that the proposed algorithm enhanced about 1dB RMSE performance on Chirp initial frequency compared with FRFT while the computational complexity is similar to FRFT.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

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