scholarly journals Multiple Moving Targets Detection and Parameters Estimation in Strong Reverberation Environments

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Ge Yu ◽  
Shengchun Piao
Keyword(s):  
Fractional Fourier Transform ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Significant Feature ◽  
Moving Targets ◽  
Variance Matrix ◽  
Linear Frequency Modulation Signal ◽  
Multiple Moving Targets

This paper considers the problem of multiple moving targets detection and parameters estimation (direction of arrival and range) in strong reverberation environments. As reverberation has a strong correlation with target echo, the performance of target detection and parameters estimation is significantly degraded in practical underwater environments. In this paper, we utilize two uniform circular arrays to receive plane wave of the linear frequency modulation signal reflected from far-field targets. On the basis of received signal, we build a variance matrix of multiple beams by using modal decomposition, conventional beamforming, and fractional Fourier transform (FrFT). We then propose a novel detection method and an estimation method of parameters based on the constructed image. A significant feature of the proposed methods is that our design does not involve any a priori knowledge about targets number and parameters of marine environments. Finally, we demonstrate via numerical simulation examples that the detection probability and the accuracy of estimated parameters of the proposed method are higher than the existing methods in both low signal-to-reverberation ratio and signal-to-noise ratio environment.

APPROACH OF MULTIPLE MOVING TARGETS DETECTION FOR MICROWAVE SURVEILLANCE SENSORS

2007 ◽  
Vol 04 (01) ◽  
pp. 57-68 ◽  
Author(s):  
WENQIN WANG
Keyword(s):  
Information Acquisition ◽  
Fractional Fourier Transform ◽  
Target Velocity ◽  
Fourier Domain ◽  
Moving Target ◽  
Moving Targets ◽  
True Position ◽  
Simulation Results ◽  
Multiple Moving Targets ◽  
Magnitude Improvement

Multiple moving targets detection is one of the fundamental problems in information acquisition. In this paper, the use of a transformable period and symmetrical linear frequency modulated (TPS-LFM) waveform for microwave surveillance sensor multiple moving targets identification, is proposed. In order to accurately estimate target's true position and velocity, a relatively unknown yet powerful technique, the so-called fractional Fourier transform (FrFT), is applied to estimate the moving target parameters. By mapping a target's signal onto a fractional Fourier axis, the FrFT permits a constant-velocity target to be focused in the fractional Fourier domain thereby affording orders of magnitude improvement in signal-clutter-ratio. Moving target velocity and position parameters are derived and expressed in terms of an optimum fractional angle and a measured fractional Fourier position, allowing a target to be accurately located. Moreover, to resolve the problem whereby weak targets are covered by the sidelobes of strong ones, the CLEAN technique is also applied. Simulation results show that the method is effective in estimating target velocity and position parameters for microwave surveillance sensors.

scholarly journals Parameters Estimation of LFMCW Signals Based on Periodic Fractional Fourier Transform

2014 ◽  
Vol 8 (5) ◽  
pp. 143
Author(s):  
Ying Liu ◽  
Dianren Chen ◽  
Lei Chen
Keyword(s):  
Fourier Transform ◽  
Continuous Wave ◽  
Fractional Fourier Transform ◽  
Estimation Method ◽  
Observation Time ◽  
Parameters Estimation ◽  
Estimation Accuracy ◽  
True Parameter ◽  
Wave Radar ◽  
Output Snr

When using fractional Fourier transform (FrFT) to detect and estimate linear frequency-modulated continuous wave radar signals, two problems will appear: multiple peaks occur in FRFT image and the output SNR at the true parameter values does not increase when the observation time is longer than the signals period. A multiple period LFMCW signals parameters estimation method based on period FRFT (PFRFT) is studied in this paper. The PFRFT formula of multiple period LFMCW signals is given. The relationship among PFRFT output SNR, observation time and sample signals SNR is analyzed. The estimation accuracy formula of PFRFT is derived. At last, numerical simulation shows the effectiveness of the algorithm and PFRFT is superior to FRFT for estimating a multiple periods LFMCW signals.  

A Parameter Estimation Method for Poly-Phase Coded Signal Based on the Modified Fractional Fourier Transform

2012 ◽  
Vol 588-589 ◽  
pp. 715-718
Author(s):  
Guo Yi Zhang ◽  
Xu Zhou Zhang ◽  
Jia Na Li
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Signal To Noise Ratio ◽  
Computational Cost ◽  
Estimation Method ◽  
Wigner Transform ◽  
Signal To Noise ◽  
Quadratic Phase ◽  
Estimate Frequency

To estimate parameters of poly-phase coded radar signals, a modified Fractional Fourier transform (FrFT) is advanced. This algorithm employs Integrated Quadratic Phase function (IQPF) to estimate frequency rate with which the best degree for Frft is computed. Its computational cost is lower than that of Radon-Wigner transform (RWT) and Radon-Ambiguity transform (RAT). When the signal-to-noise ratio (SNR) is -7 dB, Simulations show its parameter estimation performance closes to the Cramer-Rao Lower Bounds (CRLB).

scholarly journals A Novel Parameter Estimation Method Based on a Tuneable Sigmoid in Alpha-Stable Distribution Noise Environments

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3012 ◽  
Author(s):  
Li Li ◽  
Nicolas Younan ◽  
Xiaofei Shi
Keyword(s):  
Parameter Estimation ◽  
Time Delay ◽  
Stable Distribution ◽  
Fractional Fourier Transform ◽  
Impulsive Noise ◽  
A Priori ◽  
Estimation Method ◽  
Fractional Power ◽  
Estimation Accuracy ◽  
Alpha Stable Distribution

In this paper, a novel method, that employs a fractional Fourier transform and a tuneable Sigmoid transform, is proposed, in order to estimate the Doppler stretch and time delay of wideband echoes for a linear frequency modulation (LFM) pulse radar in an alpha-stable distribution noise environment. Two novel functions, a tuneable Sigmoid fractional correlation function (TS-FC) and a tuneable Sigmoid fractional power spectrum density (TS-FPSD), are presented in this paper. The novel algorithm based on the TS-FPSD is then proposed to estimate the Doppler stretch and the time delay. Then, the derivation of unbiasedness and consistency is presented. Furthermore, the boundness of the TS-FPSD to the symmetric alpha stable ( S α S ) noise, the parameter selection of the TS-FPSD, and the feasibility analysis of the TS-FPSD, are presented to evaluate the performance of the proposed method. In addition, the Cramér–Rao bound for parameter estimation is derived and computed in closed form, which shows that better performance has been achieved. Simulation results and theoretical analysis are presented, to demonstrate the applicability of the forgoing method. It is shown that the proposed method can not only effectively suppress impulsive noise interference, but it also does not need a priori knowledge of the noise with higher estimation accuracy in alpha-stable distribution noise environments.

Research on Aircraft Magnetic Compensation Based on Improved Singular Value Decomposition

2013 ◽  
Vol 281 ◽  
pp. 41-46 ◽  
Author(s):  
Jian Zhang ◽  
Peng Deng ◽  
Chun Sheng Lin
Keyword(s):  
Singular Value Decomposition ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Singular Value ◽  
Parameters Estimation ◽  
Interference Model ◽  
Estimation Accuracy ◽  
Regression Parameters ◽  
Magnetic Compensation ◽  
Value Decomposition

In aeromagnetic detection, the estimation of the regression parameters in aircraft magnetic interference model is the key of aircraft magnetic compensation. Taking aim at the multicollinearity of aircraft magnetic interference model, a new parameters estimation method with combination of wavelet threshold denoising and singular value decomposition (SVD) was proposed, which is called WSVD. First, wavelet threshold denoising was used to pretreat magnetometer data in order to decrease the noise of electric equipments which will influence the accuracy of parameters estimation. Then SVD was used in the estimation of regression parameters. In a simulation example, the estimation accuracy of LS estimation, SVD and WSVD was compared in different signal to noise ratio (SNR). The result shows that WSVD is more accurate than other two methods, especially more adaptive in low SNR. And the regression parameters of WSVD is effective in aircraft magnetic compensation. The compensation ratio is above 90%.

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.

scholarly journals Detection and localization of multiple small damages in beam

2021 ◽  
Vol 13 (1) ◽  
pp. 168781402098732
Author(s):  
Ayisha Nayyar ◽  
Ummul Baneen ◽  
Syed Abbas Zilqurnain Naqvi ◽  
Muhammad Ahsan
Keyword(s):  
Frequency Response ◽  
Natural Frequencies ◽  
Signal To Noise Ratio ◽  
Moving Average ◽  
A Priori ◽  
Damage Index ◽  
High Signal ◽  
Frequency Range ◽  
Spatial Locality ◽  
System Frequency

Localizing small damages often requires sensors be mounted in the proximity of damage to obtain high Signal-to-Noise Ratio in system frequency response to input excitation. The proximity requirement limits the applicability of existing schemes for low-severity damage detection as an estimate of damage location may not be known  a priori. In this work it is shown that spatial locality is not a fundamental impediment; multiple small damages can still be detected with high accuracy provided that the frequency range beyond the first five natural frequencies is utilized in the Frequency response functions (FRF) curvature method. The proposed method presented in this paper applies sensitivity analysis to systematically unearth frequency ranges capable of elevating damage index peak at correct damage locations. It is a baseline-free method that employs a smoothing polynomial to emulate reference curvatures for the undamaged structure. Numerical simulation of steel-beam shows that small multiple damages of severity as low as 5% can be reliably detected by including frequency range covering 5–10th natural frequencies. The efficacy of the scheme is also experimentally validated for the same beam. It is also found that a simple noise filtration scheme such as a Gaussian moving average filter can adequately remove false peaks from the damage index profile.

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