Noise Reduction of Acoustic Signals from Armored Vehicles Based on Local Projective Algorithm

2013 ◽  
Vol 10 (6) ◽  
pp. 1577-1584
Author(s):  
Zhiyang Chen
Keyword(s):  
Noise Reduction ◽  
Acoustic Signals ◽  
Projective Algorithm ◽  
Armored Vehicles

scholarly journals Noise Reduction Method of Underwater Acoustic Signals Based on Uniform Phase Empirical Mode Decomposition, Amplitude-Aware Permutation Entropy, and Pearson Correlation Coefficient

Entropy ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. 918 ◽  
Author(s):  
Guohui Li ◽  
Zhichao Yang ◽  
Hong Yang
Keyword(s):  
Noise Reduction ◽  
Empirical Mode Decomposition ◽  
High Frequency ◽  
Reduction Method ◽  
Pearson Correlation ◽  
Low Frequency ◽  
Acoustic Signals ◽  
Permutation Entropy ◽  
Underwater Acoustic ◽  
Mode Decomposition

Noise reduction of underwater acoustic signals is of great significance in the fields of military and ocean exploration. Based on the adaptive decomposition characteristic of uniform phase empirical mode decomposition (UPEMD), a noise reduction method for underwater acoustic signals is proposed, which combines amplitude-aware permutation entropy (AAPE) and Pearson correlation coefficient (PCC). UPEMD is a recently proposed improved empirical mode decomposition (EMD) algorithm that alleviates the mode splitting and residual noise effects of EMD. AAPE is a tool to quantify the information content of nonlinear time series. Unlike permutation entropy (PE), AAPE can reflect the amplitude information on time series. Firstly, the original signal is decomposed into a series of intrinsic mode functions (IMFs) by UPEMD. The AAPE of each IMF is calculated. The modes are separated into high-frequency IMFs and low-frequency IMFs, and all low-frequency IMFs are determined as useful IMFs (UIMFs). Then, the PCC between the high-frequency IMF with the smallest AAPE and the original signal is calculated. If PCC is greater than the threshold, the IMF is also determined as a UIMF. Finally, all UIMFs are reconstructed and the denoised signal is obtained. Chaotic signals with different signal-to-noise ratios (SNRs) are used for denoising experiments. Compared with EMD and extreme-point symmetric mode decomposition (ESMD), the proposed method has higher SNR and smaller root mean square error (RMSE). The proposed method is applied to noise reduction of real underwater acoustic signals. The results show that the method can further eliminate noise and the chaotic attractors are smoother and clearer.

scholarly journals Noise Reduction Method of Underwater Acoustic Signals Based on CEEMDAN, Effort-To-Compress Complexity, Refined Composite Multiscale Dispersion Entropy and Wavelet Threshold Denoising

Entropy ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 11 ◽  
Author(s):  
Guohui Li ◽  
Qianru Guan ◽  
Hong Yang
Keyword(s):  
Noise Reduction ◽  
Empirical Mode Decomposition ◽  
Reduction Method ◽  
Signal To Noise Ratio ◽  
Acoustic Signals ◽  
Ensemble Empirical Mode Decomposition ◽  
Underwater Acoustic ◽  
Real Signal ◽  
Mode Decomposition ◽  
Soft Threshold

Owing to the problems that imperfect decomposition process of empirical mode decomposition (EMD) denoising algorithm and poor self-adaptability, it will be extremely difficult to reduce the noise of signal. In this paper, a noise reduction method of underwater acoustic signal denoising based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), effort-to-compress complexity (ETC), refined composite multiscale dispersion entropy (RCMDE) and wavelet threshold denoising is proposed. Firstly, the original signal is decomposed into several IMFs by CEEMDAN and noise IMFs can be identified according to the ETC of IMFs. Then, calculating the RCMDE of remaining IMFs, these IMFs are divided into three kinds of IMFs by RCMDE, namely noise-dominant IMFs, real signal-dominant IMFs, real IMFs. Finally, noise IMFs are removed, wavelet soft threshold denoising is applied to noise-dominant IMFs and real signal-dominant IMFs. The denoised signal can be obtained by combining the real IMFs with the denoised IMFs after wavelet soft threshold denoising. Chaotic signals with different signal-to-noise ratio (SNR) are used for denoising experiments by comparing with EMD_MSE_WSTD and EEMD_DE_WSTD, it shows that the proposed algorithm has higher SNR and smaller root mean square error (RMSE). In order to further verify the effectiveness of the proposed method, which is applied to noise reduction of real underwater acoustic signals. The results show that the denoised underwater acoustic signals not only eliminate noise interference also restore the topological structure of the chaotic attractors more clearly, which lays a foundation for the further processing of underwater acoustic signals.

Satisfaction With Noise Reduction Circuits

1993 ◽  
Vol 2 (1) ◽  
pp. 51-53 ◽  
Author(s):  
Ruth A. Bentler
Keyword(s):  
Noise Reduction

Long range target recognition and identification of camouflaged armored vehicles.

1979 ◽  
Author(s):  
William L. Warnick ◽  
Garvin D. Chastain ◽  
William H. Ton
Keyword(s):  
Long Range ◽  
Target Recognition ◽  
Armored Vehicles

КОНЦЕПЦІЯ СТВОРЕННЯ СИЛОВОЇ УСТАНОВКИ СІМЕЙСТВА РЕГІОНАЛЬНИХ ПАСАЖИРСЬКИХ ЛІТАКІВ АН-148/АН-158

2019 ◽  
pp. 50-63
Author(s):  
О. Д. Донець ◽  
В. П. Іщук
Keyword(s):  
Power Plant ◽  
Noise Reduction ◽  
Fuel Consumption ◽  
Electronic System ◽  
Electronic Control ◽  
Level Of Automation ◽  
Auxiliary Power ◽  
Power Plant Control ◽  
Technical Status ◽  
Air Intake

The basic results of calculation and research works carried out in the process of creation of power unit of regional passenger airplanes’ family are given. The design features of the propulsion engines and engine of the auxiliary power plant are described. The aforementioned propulsion system includes propulsion engines D-436-148 and engine AI-450-MS of auxiliary power plant. In order to comply with the requirements of Section 4 of the ICAO standard (noise reduction of the aircraft in site), in part of ensuring the noise reduction of engines, when creating the power plant of the An-148/An-158 aircraft family, a single- and double-layer acoustic filler was used in the structure of the engine nacelle and air intake. The use of electronic system for automatic control of propulsion engines such as FADEC and its integration into the digital airborne aircraft complex ensured the operation of engines, included in the power plant provided with high specific fuel consumption, as well as increased the level of automation of the power plant control and monitoring, and ensured aircraft automation landing in ICAO category 3A. In addition, the use of the aforementioned electronic system, allowed to operate the power plant of the aircraft in accordance with technical status. The use of the AI-450-MS auxiliary power plant with an electronic control system such as FADEC, and the drive of the service compressor from a free turbine, eliminated the effect of changes in power and air takeoff, on the deviation of the engine from optimal mode, which also minimized the fuel consumption. The use of fuel metering system TIS-158, allowed to ensure control of its condition and assemblies, without the use of auxiliary devices, built-in control means. In the fire protection system, the use of the electronic control and monitor unit, as well as the use of digital serial code for the exchange of information between the elements of the system and the aircraft systems, has reduced the number of connections, which increased the reliability of the system and reduced its weight characteristics.

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