Extended overlap-save and overlap-add convolution algorithms for real signal

2007 ◽  
Author(s):  
J.D. Kene
Keyword(s):  
Real Signal

scholarly journals A Novel Noise Reduction Method of UAV Magnetic Survey Data Based on CEEMDAN, Permutation Entropy, Correlation Coefficient and Wavelet Threshold Denoising

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1309
Author(s):  
Yaoxin Zheng ◽  
Shiyan Li ◽  
Kang Xing ◽  
Xiaojuan Zhang
Keyword(s):  
Noise Reduction ◽  
Correlation Coefficient ◽  
Field Experiments ◽  
Reduction Method ◽  
Magnetic Data ◽  
Permutation Entropy ◽  
Magnetic Survey ◽  
Intrinsic Mode Functions ◽  
Real Signal ◽  
The Real

Despite the increased attention that has been given to the unmanned aerial vehicle (UAV)-based magnetic survey systems in the past decade, the processing of UAV magnetic data is still a tough task. In this paper, we propose a novel noise reduction method of UAV magnetic data based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), permutation entropy (PE), correlation coefficient and wavelet threshold denoising. The original signal is first decomposed into several intrinsic mode functions (IMFs) by CEEMDAN, and the PE of each IMF is calculated. Second, IMFs are divided into four categories according to the quartiles of PE, namely, noise IMFs, noise-dominant IMFs, signal-dominant IMFs, and signal IMFs. Then the noise IMFs are removed, and correlation coefficients are used to identify the real signal-dominant IMFs. Finally, the wavelet threshold denoising is applied to the real signal-dominant IMFs, the denoised signal can be obtained by combining the signal IMFs and the denoised IMFs. Both synthetic and field experiments are conducted to verify the effectiveness of the proposed method. The results show that the proposed method can eliminate the interference to a great extent, which lays a foundation for the further interpretation of UAV magnetic data.

A real signal and its states

2017 ◽  
Vol 48 (3) ◽  
pp. 488-508
Author(s):  
S. G. Basiladze
Keyword(s):  
Real Signal

Automated phase correction via maximization of the real signal

2009 ◽  
Vol 27 (3) ◽  
pp. 393-400 ◽  
Author(s):  
Edme H. Hardy ◽  
Jürgen Hoferer ◽  
Dirk Mertens ◽  
Gerhard Kasper
Keyword(s):  
Phase Correction ◽  
Real Signal ◽  
The Real

scholarly journals Evaluation of Uncertainty of Phase Difference Determination in Presence of Bias

2016 ◽  
Vol 23 (4) ◽  
pp. 603-614 ◽  
Author(s):  
Lazar V. Saranovac ◽  
Nada M. Vučijak
Keyword(s):  
Measurement Uncertainty ◽  
Phase Difference ◽  
The Other ◽  
Real Signal ◽  
Measurement Systems ◽  
Comparison Of Results ◽  
Sinusoidal Signals

AbstractDetermination of the phase difference between two sinusoidal signals with noise components using samples of these signals is of interest in many measurement systems. The samples of signals are processed by one of many algorithms, such as 7PSF, UQDE and MSAL, to determine the phase difference. The phase difference result must be accompanied with estimation of the measurement uncertainty. The following issues are covered in this paper: the MSAL algorithm background, the ways of treating the bias influence on the phase difference result, comparison of results obtained by applying MSAL and the other mentioned algorithms to the same real signal samples, and evaluation of the uncertainty of the phase difference.

Method of measuring transmission quality in adaptive sound broadcasting channels by real signal

2019 ◽  
Author(s):  
V. A. Abramov ◽  
O. B. Popov ◽  
T. V. Chernysheva
Keyword(s):  
Real Signal ◽  
Transmission Quality

Cytochrom-c-oxidase measured in near-infrared spectroscopy -real signal or an artifact?

2002 ◽  
Author(s):  
K. Uludag ◽  
H. Obrig ◽  
R. Wenzel ◽  
M. Kohl ◽  
A. Villringer
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Real Signal

scholarly journals ADS-B Signal Verification Using a Coherent Receiver

2021 ◽  
Vol 13 (1) ◽  
pp. 4
Author(s):  
Wouter Huygen ◽  
Junzi Sun ◽  
Jacco Hoekstra
Keyword(s):  
Software Defined Radio ◽  
High Performance ◽  
Cost Effective ◽  
Direction Of Arrival ◽  
Effective Solution ◽  
Real Signal ◽  
Update Rate ◽  
Signal Injection ◽  
Coherent Receivers ◽  
Radio Transceiver

Automatic Dependent Surveillance-Broadcast (ADS-B) enables aircraft to periodically broadcast their flight states such as position and velocity. Compared to classical radar surveillance, it increases update rate and accuracy. Currently, Mode S Extended Squitter is the most common implementation for ADS-B. Due to the simplicity of Mode S design, ADS-B signals are prone to injections. This study proposes a cost-effective solution that verifies the integrity of ADS-B signals using coherent receivers. We design the verification approach by combining the signal’s direction of arrival, estimated from the multi-channel data, with the target bearing calculated from ADS-B messages. By using another high-performance software-defined radio transceiver, we also conduct real signal injection experiments to validate our approaches.

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