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This paper proposes a Doppler estimation algorithm for underwater acoustic communication by constructing the guide function of the objective function based on linear frequency modulation (LFM) signal. The algorithm employs the least square principle and the particle swarm method, to build the objective function and solves the global optimal solution, respectively. Computer simulations show that the...
Passive radar systems based on navigation satellite reflected signal achieve the target detection and location by receiving and processing very weak Globe Navigation Satellite System (GNSS) reflected signal efficiently. During the multichannel signal processing of navigation satellite reflected signals, digital beamforming (DBF) has been introduced to form automatically array antenna beam pointing...
Automatic Modulation classification lays important role in the systems of electromagnetic spectrum monitoring. However performance of the algorithms is depreciated due to inaccurate estimation of signal parameters. The problem of unknown parameters is well documented in the literature however, authors usually propose improved algorithms in order to maximize probability of correct classification when...
This paper addresses the problem of acoustic noise reduction and speech enhancement in new telecommunication systems by adaptive filtering algorithms. We propose a new two-channel forward BSS algorithm based on signal prediction to give an automatic algorithm with a very nice behavior at the output. This algorithm is called the two-channel fast normalized least mean square (TCFNLMS) algorithm. This...
In this paper, we address the problem of noise reduction and speech enhancement by adaptive filtering algorithms using the forward blind source separation structure (FBSS), which is often combined with adaptive algorithms to efficiently cancel the acoustic noise at the output. In this paper, we propose to combine the FBSS with the Simplified Fast Transversal Filter (SFTF) algorithm, where the adaptation...
Parameters estimation is a crucial and challenging component for Frequency-Hopping (FH) communication. Time-frequency analysis is a valid signal processing tool to estimate parameters of FH signal. However, the existing Time-Frequency analysis methods have several shortcomings such as weak suppression noise interference and feeble concentration of Time-Frequency, resulting in inaccurate parameter...
Indoor target tracking has garnered interest as communication systems and mobile device capabilities advance. Visible light communication (VLC) is an alternative to RF methods that uses light emitting diodes. In this paper, probabilistic filtering algorithms (particle and extended Kalman filters) are used for indoor tracking. The performance of the filters is compared with an another positioning method:...
Compared to conventional radar systems, passive coherent location (PCL) systems utilize transmitters already deployed within an environment. In this paper, we investigate PCL systems to estimate an unknown target position in three dimensional space, and propose a target-tracking process of three steps: 1) receiver selection, 2) target-tracking algorithm, and 3) filtering process. To reduce an estimation...
The demand for radio spectrum is rapidly increasing for applications such as mobile telephony, digital video broadcasting (DVB), wireless local area networks (WiFi), and wireless sensor networks (ZigBee), and internet of things. Indeed, these resources are becoming increasingly scarce or even nonexistent. This scarcity has led to the concept of Cognitive Radio (CR) communication which has used to...
As the communication systems have been increasingly complex, the problem of channel estimation for such complex communication systems has also emerged as an equally challenging task. To solve this problem, various schemes based on Least Mean Square (LMS) and its improved variants have been proposed. This paper presents an adaptive algorithm for channel estimation in non-Gaussian environment. The proposed...
Channel estimation is an important component of wireless communications. This paper deals with the comparison between Mean Square Error (MSE) based neural networks and Minimum Error Entropy (MEE) based neural networks in additive non-Gaussian noise channel estimation. This essay analyzes MEE and MSE algorithms in several channel models utilizing neural networks. The aim of this study is first to compare...
Conventional radar generally uses fixed transmit waveform, which is difficult to obtain optimal target detection performance in the presence of interference. To solve this problem, a joint optimization algorithm of waveform and receiving filter for MIMO radar is proposed. Firstly, the maximization of output signal to interference plus noise ratio is used as objective function. The joint optimization...
Image restoration and reconstruction from blurry and noisy images have proved to be challenging problem. Noise removal plays any important role in preserving the meaningful and useful information in images. Our paper is based on a denoising technique known as total variation (TV). Over the years, high quality images and videos have become a trend. However, noise has remained an integral part in images...
This paper proposes a novel algorithm for the joint estimation of DOA, range and frequency of mixed far-field and near-field sources. Based on the second order statistics of a symmetric uniform linear array, this method constructs two correlation matrices in the first step to obtain the estimates of DOA and frequency parameters. In the second step, two more correlation matrices are derived. The range...
In this work, a single-input multiple-output (SIMO) continuous-wave Doppler radar sensor (DRS) system is designed and implemented for motion separation. A blind motion separation approach is proposed to separate the combinations of triangular and sinusoidal motions can with amplitude accuracy. Experiments show that combinations of different motions can be linearly separated. These results imply the...
In this paper, a new algorithm to broaden the width of null is proposed. The algorithm is based on the property of subspace orthogonal principle between signal and noise and on virtual antenna array. Also diagonal loading technique is used to form robust beam pattern. With the theoretical analysis and computer simulations, it's shown that the superiority of proposed algorithm over other null broadening...
Two-dimensional zero-attraction projection (2DZAP) algorithm for single snapshot direction of arrival (DOA) estimation is proposed in this paper. Compared with the traditional DOA estimation, the proposed 2D-ZAP algorithm can estimate DOA exactly by ℓ-norm with the same number of sensors, although each sensor samples the signal only one time. In addition, 2D-ZAP algorithm can reduce the noise interference...
Wireless SAW resonant sensors have been widely used in many applications, especially in harsh environment. The sensor is detected when the echo signal spectrum processed by Fourier transform exceeds a threshold. Because of complicated noise and electromagnetic interference in wireless channel, the threshold should be adaptive to interference in order to detect the sensor accurately. However, few researches...
Compressed Sensing is a novel sampling technique that can be used to faithfully recover sparse signals from fewer measurements than those proposed by the Nyquist theorem. A simple and intuitive measure of sparsity in a signal is ℓ0-norm. However, the ℓ0-norm function does not satisfy all the axiomatic properties of a true mathematical norm. The discrete and discontinuous nature of ℓ0-norm poses many...
This paper evaluates the application of three methods for Sound Source Separation (SSS) in industrial acoustic condition monitoring scenarios. To evaluate the impact of SSS, we use a machine learning approach where a classifier is trained to detect a specific operating machine. The evaluation procedure is based on simulated and measured data, comprising three different machine sounds as targets and...
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