Iterative Phase-Based Frequency Estimation with Extended Threshold and Estimation Range at Moderate Complexity

2006 ◽  
Author(s):  
Ivan Perisa ◽  
Jurgen Lindner
Keyword(s):  
Frequency Estimation ◽  
Moderate Complexity ◽  
Estimation Range

A Novel Non-Data-Aided Frequency Estimation Algorithm for M-PSK Signals

2013 ◽  
Vol 756-759 ◽  
pp. 3109-3113
Author(s):  
Qing Hua Tian ◽  
Xin Man ◽  
Sheng Zeng
Keyword(s):  
Computational Complexity ◽  
Carrier Frequency ◽  
Frequency Estimation ◽  
Estimation Algorithm ◽  
New Method ◽  
Estimation Accuracy ◽  
Step Factor ◽  
Carrier Frequency Estimation ◽  
Estimation Range

This paper deals with the problem of carrier frequency estimation for MPSK symbols. We present a novel non-data-aided method by introducing a step factor into an earlier estimation algorithm to reduce the computational complexity with little loss of the estimation accuracy. We also make some comparisons with earlier algorithms. From the results of simulations, we make the conclusion that the new method can separate the estimation range and the estimation accuracy, and avoid the weakness of reaching large estimation range at the expense of estimation accuracy.

Data-Aided Parameters Estimation of Satellite-Based AIS Signals

2013 ◽  
Vol 816-817 ◽  
pp. 862-865
Author(s):  
She Xiang Ma ◽  
Xiao Juan Liu ◽  
Xin Meng
Keyword(s):  
Computer Simulations ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Data Fitting ◽  
Parameters Estimation ◽  
Estimation Accuracy ◽  
Small Range ◽  
Principal Value ◽  
Precision Estimation ◽  
Estimation Range

Aiming at the problem of poor accuracy and small range of frequency estimation in the area of satellite-based AIS signals, this paper presents a novel data-aided estimation method based on the autocorrelation and DFT. The algorithm determines the principal value and the expansion of the frequency and then acquires high-precision estimation by data fitting. Based on that, other parameters can be estimated. Computer simulations were used to illustrate better estimation accuracy and a large estimation range.

Technique for Improving the Flow Rate Estimation Range by Using an Axial Flow Water Turbine Generator

2017 ◽  
Vol 137 (1) ◽  
pp. 30-35
Author(s):  
Hiroaki Narita ◽  
Makoto Saruwatari ◽  
Jun Matsui ◽  
Yasutaka Fujimoto
Keyword(s):  
Flow Rate ◽  
Axial Flow ◽  
Turbine Generator ◽  
Rate Estimation ◽  
Water Turbine ◽  
Estimation Range

Off-Grid Frequency Estimation with Random Measurements

2017 ◽  
Vol E100.A (11) ◽  
pp. 2493-2497
Author(s):  
Xushan CHEN ◽  
Jibin YANG ◽  
Meng SUN ◽  
Jianfeng LI
Keyword(s):  
Frequency Estimation ◽  
Random Measurements

Improvement of Jain’s algorithm for frequency estimation

2020 ◽  
Vol 65 (1) ◽  
pp. 115-122
Author(s):  
Andrea Amalia Minda
Keyword(s):  
Frequency Estimation ◽  
The Real ◽  
Real Frequency

In this paper we propose a procedure to correct Jain's algorithm, which in certain situations fails in correctly estimating the frequency by indicating frequency values that are very far from the real frequency. It happens because the two points considered for the method proposed by Jain are not on the same lobe. Thus, a method is proposed according to which these points are chosen so that the results are improved.

FFT-Based Moving Average Maximum Likelihood Single-tone Frequency Estimation

2011 ◽  
Vol 30 (4) ◽  
pp. 831-835
Author(s):  
Yu-chun Huang ◽  
Zai-lu Huang ◽  
Ben-xiong Huang ◽  
Shu-hua Xu
Keyword(s):  
Maximum Likelihood ◽  
Frequency Estimation ◽  
Moving Average ◽  
Tone Frequency ◽  
Single Tone ◽  
Average Maximum
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