Parameter Estimation of Co-Channel AIS Signal Using Ambiguity Function

2014 ◽  
Vol 644-650 ◽  
pp. 4035-4039
Author(s):  
Hao Su Zhou ◽  
Jian Xin Wang
Keyword(s):  
Parameter Estimation ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Reference Signal ◽  
Two Dimensions ◽  
Ambiguity Function ◽  
Weak Signal ◽  
Strong Signal ◽  
Estimated Parameters ◽  
Simulation Results

A new data-aided algorithm for parameter estimation of the co-channel AIS signal transmitted over the additive white Gaussian noise channel is proposed in this paper. The co-channel signal consists of a strong signal with high power and a weak signal with low power. The parameters of the strong signal are estimated by searching the ambiguity function of the co-channel signal in two dimensions. A reference signal is therefore reconstructed with the estimated parameters and the aided data. By removing the ambiguity function of the reconstructed reference signal from that of the original co-channel signal, a new co-channel signal ambiguity function is obtained, from which the parameters of the weak signal are estimated. The simulation results illustrate that the proposed algorithm can estimate the parameters of the co-channel AIS signal effectively.

scholarly journals BER Performance Analysis of Non-Coherent Q-Ary Pulse Position Modulation Receivers on AWGN Channel

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6102
Author(s):  
Xianhua Shi ◽  
Yimao Sun ◽  
Jie Tian ◽  
Maolin Chen ◽  
Youjiang Liu ◽  
...  
Keyword(s):  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Theoretical Formula ◽  
Pulse Position Modulation ◽  
Error Performance ◽  
Optimal Receiver ◽  
Awgn Channel ◽  
Simulation Results ◽  
The Relationship ◽  
Better Than

This paper introduces the structure of a Q-ary pulse position modulation (PPM) signal and presents a noncoherent suboptimal receiver and a noncoherent optimal receiver. Aiming at addressing the lack of an accurate theoretical formula of the bit error rate (BER) of a Q-ary PPM receiver in the additive white Gaussian noise (AWGN) channel in the existing literature, the theoretical formulas of the BER of a noncoherent suboptimal receiver and noncoherent optimal receiver are derived, respectively. The simulation results verify the correctness of the theoretical formulas. The theoretical formulas can be applied to a Q-ary PPM system including binary PPM. In addition, the analysis shows that the larger the Q, the better the error performance of the receiver and that the error performance of the optimal receiver is about 2 dB better than that of the suboptimal receiver. The relationship between the threshold coefficient of the suboptimal receiver and the error performance is also given.

scholarly journals Performance Comparison of Digitized Quaternion Modulation with other Modulation Schemes

2019 ◽  
Vol 27 ◽  
pp. 01004
Author(s):  
Anam Zahra ◽  
Qasim Umar Khan
Keyword(s):  
Global Positioning System ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Performance Comparison ◽  
Superior Performance ◽  
Positioning System ◽  
Space Communication ◽  
Global Positioning ◽  
Simulation Results ◽  
Modulation Schemes

In wireless networks signal’s security from noise has been a very challenging issue, primarily because of the broadcast nature of communication. This paper focuses on digitized Quaternion Modulation (QM) which gives better performance as compared to QPSK, QAM and QFSK. We compare the performance of quaternion modulation with other modulation schemes in terms of BER using idealistic Additive White Gaussian Noise AWGN channel. This scheme can be used in applications such as Global Positioning System (GPS), satellite and space communication system to reduce errors. The simulation results show superior performance of the proposed digitized Quaternion Modulation over its counterparts. Thus one may trade off bandwidth for BER.

scholarly journals Extended Particle-Aided Unscented Kalman Filter Based on Self-Driving Car Localization

2020 ◽  
Vol 10 (15) ◽  
pp. 5045 ◽  
Author(s):  
Ming Lin ◽  
Byeongwoo Kim
Keyword(s):  
Kalman Filter ◽  
Real World ◽  
Gaussian Noise ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Localization Problem ◽  
Simulation Results ◽  
Non Gaussian ◽  
Self Driving Cars

The location of the vehicle is a basic parameter for self-driving cars. The key problem of localization is the noise of the sensors. In previous research, we proposed a particle-aided unscented Kalman filter (PAUKF) to handle the localization problem in non-Gaussian noise environments. However, the previous basic PAUKF only considers the infrastructures in two dimensions (2D). This previous PAUKF 2D limitation rendered it inoperable in the real world, which is full of three-dimensional (3D) features. In this paper, we have extended the previous basic PAUKF’s particle weighting process based on the multivariable normal distribution for handling 3D features. The extended PAUKF also raises the feasibility of fusing multisource perception data into the PAUKF framework. The simulation results show that the extended PAUKF has better real-world applicability than the previous basic PAUKF.

Research on Overlapped Time Division Multiplexing in the Amplify-and-Forward Cooperative Mode

2015 ◽  
Vol 713-715 ◽  
pp. 1103-1106
Author(s):  
Hong Zhang ◽  
Wei Ping Ma
Keyword(s):  
Cooperative Communication ◽  
Gaussian Noise ◽  
Communication System ◽  
Additive White Gaussian Noise ◽  
Spectrum Efficiency ◽  
Amplify And Forward ◽  
Time Division Multiplexing ◽  
Simulation Results ◽  
Time Division ◽  
New System

In order to improve spectrum efficiency of cooperative communication system, Overlapped Time Division Multiplexing (OVTDM) is applied to Amplify-and-Forward (AF) cooperative communication system. The simulation results under Additive White Gaussian Noise (AWGN) channel show that the performance of new system is superior to that of corresponding AF cooperative communication system.

scholarly journals RECOGNITION OF RADIO EXCHANGE VOICE MESSAGES IN AVIATION BASED ON CORRELATION ANALYSIS

2021 ◽  
Vol 23 (1) ◽  
pp. 91-96
Author(s):  
N.A. Andriyanov ◽  
Keyword(s):  
Correlation Analysis ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Reference Signal ◽  
Reference Sample ◽  
Test Sample ◽  
White Gaussian Noise ◽  
Civil Aviation ◽  
Spectral Transform ◽  
The Time Domain

The paper considers the problem of speech messages recognition in phraseological radio exchange for tasks of civil aviation. The introduction substantiates the relevance of this problem. The following are research methods based on correlation analysis. Finally, a description of the experiment and the results of the recognition algorithms based on correlation analysis are given. Various variants were recorded for five speech messages and spectral representations of such signals were constructed. Spectral transform can be obtained either using specialized software or based on the Fourier transform of the signal in the time domain. To obtain a more universal reference signal and eliminate the influence of interference, the spectral components of the same speech message recorded several times were averaged. In fact, three spectra of the same speech message were used for averaging. This spectrum averaging over three training components provided a reference sample of phrases or patterns for each phrase, and reduced the influence of additive white Gaussian noise in the reference. Later, on the basis of correlation analysis, the connections between test phrases and all patterns were calculated. On the basis of these connections, a correlation matrix of reference phrases is built. Research has shown that phrases spoken by one person were highly correlated. The analysis showed that the choice of the class (the content of the speech message) when solving the recognition problem corresponding to the value of the correlation coefficient closest to one provides over 90% of correct recognitions on a test sample containing a total of 100 phrases, 20 for each phrase. It should be noted that, when recording test messages, an additive white Gaussian noise was additionally present as a background, reproduced by another audio device. In the case of information analysis without artificially generated noise, the probability of correct recognition for a test sample of 100 phrases, 20 for each phrase, is 100% when using correlation analysis.

New Controller Design in QCNN and the Synchronization with Chaotic System

2015 ◽  
Vol 719-720 ◽  
pp. 359-364
Author(s):  
Chang Xing Chen ◽  
De Zhi Niu ◽  
Hui Fu ◽  
Yan Ming Zhao ◽  
Xu Jing Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Controller Design ◽  
Reference Signal ◽  
Periodic Signal ◽  
Weak Signal ◽  
New Thought ◽  
Duffing System ◽  
Synchronization Problem ◽  
Simulation Results ◽  
Synchronization Structure

Synchronization problem between QCNN (Quantum Cellular Neural Networks) and duffing system was studied in the paper. Not only one new controller with less parameters in QCNN was designed, but it was proved by Lyapunov function that output signal would be convergent to reference signal, and meanwhile, forms of multi-dimension controllers were given. Then the synchronization structure was draw with the corresponding controllers. In the simulation results, the new controller has higher time efficiency, which shows applying the new controller to QCNN is feasible and effective and it can assure the achievement of synchronization. Furthermore, weak periodic signal can be detected in QCNN, which provides one new thought to detection of weak signal.

scholarly journals Convergence analysis of the unpunctured turbo trellis-coded modulation (UTTCM)

2019 ◽  
Vol 13 (2) ◽  
pp. 447
Author(s):  
Ahmed Haffane ◽  
Abdelhafid Hasni ◽  
Mustapha Khelifi ◽  
Boufeldja Kadri
Keyword(s):  
Gaussian Noise ◽  
Iterative Decoding ◽  
Information Transfer ◽  
Additive White Gaussian Noise ◽  
Coded Modulation ◽  
Extrinsic Information ◽  
Trellis Coded Modulation ◽  
Exit Chart ◽  
Trellis Coded ◽  
Simulation Results

In this paper, the performance of the Unpunctured Turbo Trellis-Coded Modulation (UTTCM) over Additive White Gaussian Noise (AWGN) channel is analyzed using the non-binary extrinsic information transfer (EXIT) chart. The exchange of the extrinsic information between the decoder components is tracked, allowing the generation of an EXIT chart, which is a powerful tool for analyzing the convergence behavior of iterative decoding and prediction of convergence position. The Simulation results are compared with the turbo cliff positions on the BER curves.

scholarly journals Iterative based image and video denoising by fractional block matching and transform domain filtering

2021 ◽  
Author(s):  
Amir Mehdizadeh Hemat Abadi ◽  
Mohammad Reza Hosseiny Fatemi
Keyword(s):  
Image Denoising ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Weighted Average ◽  
Block Matching ◽  
Objective Measures ◽  
Transform Domain ◽  
Video Denoising ◽  
Simulation Results ◽  
Fractional Motion Estimation

This paper presents an iterative algorithm for image and video denoising which is based on fractional block-matching and transform domain filtering. We propose fractional motion estimation technique to find the most accurate similar blocks for each block of an image which improves sparsity enabling effective image denoising. By taking the advantage of blocks similarity and wavelet transform domain filtering along with weighted average function (WAF) in an iterative based manner, we achieve a higher level of sparsity and a better exploiting of blocks similarity redundancies of noisy images that increase the chance of preserving details and edges in the restored image. Since our algorithm is iterative, we can tradeoff between image denoising degree and computational complexity. In addition, we develop a video denoising algorithm based on the proposed image denoising algorithm. The simulation results of images and videos contaminated by additive white Gaussian noise demonstrate that our algorithm substantially achieves better denoising performance compared with previously published algorithms in terms of subjective and objective measures.

A dichotomous search-based frequency estimator with generic analytical expression

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840095
Author(s):  
Gangbing Zhang ◽  
Lu Jin ◽  
Defeng (David) Huang
Keyword(s):  
Gaussian Noise ◽  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Frequency Interval ◽  
Analytical Expression ◽  
Dichotomous Search ◽  
Simulation Results ◽  
Fine Resolution ◽  
Frequency Estimator

Fine resolution frequency estimation of a single-tone complex sinusoidal signal in the additive white Gaussian noise is of importance in many fields. In this paper, a generic analytical expression is proposed to refine the residual of a dichotomous search, leading to an estimator with much less iterations than the conventional dichotomous search estimator. Compared with other existing estimators, the proposed estimator has a better trade-off between performance and computational complexity. Simulation results demonstrate that the root-mean-square error (RMSE) of the proposed estimator is closer to the Cramer–Rao lower bound (CRLB) than other estimators over the whole frequency interval when the signal-to-noise ratio (SNR) is above a threshold.

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