scholarly journals Fast Implementation of Approximated Maximum Likelihood Parameter Estimation for Frequency Agile Radar under Jamming Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2022
Author(s):  
Yang Zhao ◽  
Jianxin Wu ◽  
Zhiyong Suo ◽  
Xiaoyu Liu
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Order Approximation ◽  
Estimation Algorithm ◽  
Adaptive Beamforming ◽  
Computationally Efficient ◽  
Fine Grid ◽  
Frequency Agile ◽  
Parameter Estimation Algorithm ◽  
Deceptive Jamming

A computationally efficient target parameter estimation algorithm for frequency agile radar (FAR) under jamming environment is developed. First, the barrage noise jamming and the deceptive jamming are suppressed by using adaptive beamforming and frequency agility. Second, the analytical solution of the parameter estimation is obtained by a low-order approximation to the multi-dimensional maximum likelihood (ML) function. Due to that, fine grid-search (FGS) is avoided and the computational complexity is greatly reduced.

scholarly journals A Frequency-Time Algorithm of Parameter Estimation for Sinusoidal Signal in Noise

2021 ◽  
Vol 21 (1) ◽  
pp. 33-38
Author(s):  
Peng Chen ◽  
Qin Chen ◽  
Zhijun Xie ◽  
Xiaohui Chen ◽  
Shaomei Zhao
Keyword(s):  
Parameter Estimation ◽  
Time Domain ◽  
Initial Phase ◽  
Linear Prediction ◽  
Estimation Algorithm ◽  
Time Algorithm ◽  
Sinusoidal Signal ◽  
Estimation Accuracy ◽  
Computationally Efficient ◽  
Parameter Estimation Algorithm

Abstract In this paper, a computationally efficient and high precision parameter estimation algorithm with frequency-time combination is proposed to improve the estimation performance for sinusoidal signal in noise, which takes the advantages of frequency- and time-domain algorithms. The noise influence is suppressed through spectrum analysis to get coarse frequency, and the fine frequency is obtained by denoising filtering and using linear prediction property. Then, estimation values of the amplitude and initial phase are obtained. The numerical results indicate that the proposed algorithm makes up for the shortcomings of frequency- and time-domain algorithms and improves the anti-interference performance and parameter estimation accuracy for sinusoidal signal.

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