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This paper presents an new approach to noise reduction for voice communication over Bluetooth technology. In the literature, several authors have compared the performance of different filtering techniques, such as the well-known Spectral Subtraction (SS), and Wiener Filter (WF) using simulated data, whereas this research uses real-time data samples collected from cars subjected to a noisy environment...
This paper provides an experimental result of non-contact vital sensing by a Doppler sensor for multiple targets. This is based on the signal processing scheme that is termed as differential of accumulation for real-time serial-to-parallel converter (DARS). To the best of authors' knowledge, there is no extant studies dealing with multiple targets with a Doppler sensor. In this experiment, we employ...
In the past period, great efforts have been made to develop methods for people detection based on monitoring their respiratory motion using ultra-wide band sensors (radars). The basic principle of these methods consists in the detection of signal components of raw radar data possessing a significant power in the frequency band 0.1 Hz-0.7 Hz (a frequency range of human respiratory rate) for a constant...
Distributed, networked communication systems, such as relay beamforming networks are typically designed without considering how the positions of the respective nodes might affect the quality of the communication. That is, network nodes are either assumed to be stationary in space, or, if some of them are moving while communicating, their trajectories are assumed to be independent of the respective...
Knowing the wind speed is an important factor that includes several scientific areas. For the types of existing anemometers, the ultrasonic model is what can be used in most applications. As part of the necessary calculus for wind speed acquisition, it is needed to find the correct ultrasonic echo emitted that has been corrupted by the environmental conditions imposed on it, and is the bigger challenge...
In the industrial field, how to find the fault and diagnosis the fault have become an urgent requirement. In which the early fault diagnosis is the most challenging, due to the information related to the early fault is almost too weak, that is hard to be found. In this paper, we focus on a classical signal processing method called synchrosqueezing transform (SST) that is re-designed to detect the...
Underwater acoustic source localization has attracted wide interests, and the source depth estimation is more difficult than that of source range and bearing. The performance of Matched Field Processing (MFP) degrades greatly under environment parameter mismatches, which makes it limited in practice. Varieties of robust methods have been proposed to relieve the mismatch problems. T. C. Yang proposed...
Most of real-life signals are nonGaussian, therefore the linear parametrization/modeling methods, suitable for Gaussian signals are neither adequate nor optimal. Using a nonlinear approach, we can significantly improve filtering results. However, the price that has to be paid is the complexity of the nonlinear treatment. In this paper we consider the nonlinear Schurtype orthogonal transformations...
This paper presents an Kalman Filter Data Fusion methodology and investigation for high dynamics and high precision multi-head angular position encoder. The proposed algorithm based on measurement of four dependent Read Heads and encoder ring for one mechanical shaft of high precision system with electric drive. The global fusion of proposed estimation provide computed value of position and additional...
This paper deals with the method of elimination of the DC offset impact on the speed estimation system which uses sine/cosine incremental position encoder. The impact of the DC offset in the input signals to the PLL-based speed estimation is shown. The problem can be solved by means of the highpass filter which should be implemented in the angle domain instead of time domain. The simulation and experimental...
This paper presents the utilization of an inertial measurement unit (IMU) for wind-characterization applications. A method of wind velocity estimation using an IMU installed on a tethered balloon is described. The system of a balloon tethered to a ground station acts as a measuring instrument for wind approximation. The wind-responding motion of tethered balloon is captured with the utilization of...
Pulse photopletysmographic signal (PPG) is modulated by the respiratory rate, so there are some algorithms capable to extract respiratory information from the derived PPG signals, as the Pulse Amplitude Variability (PAV). Previous works have shown that the use of the PPG leads to different results depending on the PPG sensor location (finger and forehead). Therefore, a database recording finger and...
In this paper, we present a time-recursive implementation of a recent hyperparameter-free group-sparse estimation technique. This is achieved by reformulating the original method, termed group-SPICE, as a square-root group-LASSO with a suitable regularization level, for which a time-recursive implementation is derived. Using a proximal gradient step for lowering the computational cost, the proposed...
This paper presents a new model order selection technique for signal processing applications related to source localization or subspace orthogonal projection techniques in large dimensional regime (Random Matrix Theory) when the noise environment is Complex Elliptically Symmetric (CES) distributed, with unknown scatter matrix. The proposed method consists first in estimating the Toeplitz structure...
When identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique,...
In Big Data Processing we typically face very large data sets that are highly structured. To save the computation and storage cost, it is desirable to extract the essence of the data from a reduced number of observations. One example of such a structural constraint is sparsity. If the data possesses a sparse representation in a suitable domain, it can be recovered from a small number of linear projections...
We propose a method to both quickly and robustly extract geometric information from trajectory data. While point density may be of interest in some applications, trajectories provide different guarantees about our data such as path densities as opposed to location densities provided by points. We aim to utilize the concise nature of quadtrees in two dimensions to reduce run time complexity of counting...
In this work, the optimization of the analog transmit waveform for joint delay-Doppler estimation under sub-Nyquist conditions is considered. Based on the Bayesian Cramer-Rao lower bound (BCRLB), we derive an estimation theoretic design rule for the Fourier coefficients of the analog transmit signal when violating the sampling theorem at the receiver through a wide analog pre-filtering bandwidth....
In this paper, we focus on tracking the signal subspace under a sparsity constraint. More specifically, we propose a two-step approach to solve the considered problem whether the sparsity constraint is on the system weight matrix or on the source signals. The first step uses the OPAST algorithm for an adaptive extraction of an orthonormal basis of the principal subspace, then an estimation of the...
This paper presents a new adaptation of Zadoff-Chu sequences for the purpose of range estimation and movement tracking. The proposed method uses Zadoff-Chu sequences utilizing a wideband ultrasonic signal to estimate the range between two devices with very high accuracy and high update rate. This range estimation method is based on time of flight (TOF) estimation using cyclic cross correlation. The...
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