Communication
Mahdieh Mohammadi; Hadi Zayyani; Mehdi Bekrani
Abstract
Target localization in wireless sensor networks (WSNs) is essential for various applications. This study investigates received signal strength (RSS)-based localization in the presence of malicious anchor nodes that intentionally alter signal power levels to mislead the fusion center (FC) and degrade ...
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Target localization in wireless sensor networks (WSNs) is essential for various applications. This study investigates received signal strength (RSS)-based localization in the presence of malicious anchor nodes that intentionally alter signal power levels to mislead the fusion center (FC) and degrade positioning accuracy. To address this challenge, we adopt a Maximum a Posteriori (MAP) estimator, which estimates the target location even when the path loss exponent is unknown. We show that the MAP estimation method can estimate the WSN unknown parameters, including the path loss exponent, the distance between the target node and anchor nodes, and the received signal strength. Simulation results demonstrate that the MAP method achieves lower localization errors than other competing approaches when the Signal-to-Noise Ratio (SNR) exceeds 10 dB, although it entails higher computational complexity in terms of simulation run time. The proposed approach is particularly efficient in applications in transportation, military operations, security, smart industries, and mapping.
Communication
Mozhgan Ehsani; Mehdi Bekrani; Solyman Garousi
Abstract
The delay-and-sum (DS) beamforming and delay-weight-and-sum (DWS) beamforming are primary methods in ultrasonic imaging with phased arrays. Total focusing method (TFM) and Minimum Variance (MV) based adaptive beamforming are well-known methods within DS and DWS beamforming, respectively. The MV-based ...
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The delay-and-sum (DS) beamforming and delay-weight-and-sum (DWS) beamforming are primary methods in ultrasonic imaging with phased arrays. Total focusing method (TFM) and Minimum Variance (MV) based adaptive beamforming are well-known methods within DS and DWS beamforming, respectively. The MV-based adaptive beamforming significantly reduces interferences and provides high-resolution image compared to TFM beamforming, at the cost of high computational complexity, and sensitivity to input statistics for matrix inversion. To address these challenges, recently, iterative MV (IMV) has been proposed to alleviate computational burdens without the need for matrix inversion. The delay-multiply-and-sum (DMAS) beamforming enhances TFM beamforming performance by employing spatial information of the array signals. However, the resulting images remain susceptible to speckle and background noises in all of these beamformers. In this paper, we aim to improve these beamforming methods so that speckle and Gaussian background noise are reduced while preserving the quality of the reflective echoes in ultrasonic images. In the proposed method, a wavelet transform with a novel threshold function is applied to the received signals to initially reduce the noise, followed by the application of the beamformer. Subsequently, the coherence weighting using the denoised signals is derived, and the obtained coherence weighting is then integrated into the beamforming process. Simulation results demonstrate that the proposed method achieves a significant reduction in background noise and speckles of the above beamformer, and particularly reduces background noise and speckles of beamformer up to approximately -27dB while preserving the detection capability of reflective points.
Power systems
Mehdi Bekrani; Mojtaba Heydari; Seyedeh Tahereh Behrooz
Abstract
In this paper, a new adaptive control method is proposed for direct matrix converters. The proposed method uses interval type-2 fuzzy logic integrated with sliding mode control. Employing the sliding mode control in matrix converters leads to an efficient choice of switching combinations and a reliable ...
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In this paper, a new adaptive control method is proposed for direct matrix converters. The proposed method uses interval type-2 fuzzy logic integrated with sliding mode control. Employing the sliding mode control in matrix converters leads to an efficient choice of switching combinations and a reliable reference tracking. The main problem of the sliding mode control is the chattering phenomenon that degrades the controller performance through injecting high-frequency variations in the controller variables. The proposed method incorporates the interval type-2 fuzzy with the sliding mode control to mitigate the chattering problem. The sliding mode switch surface can be adjusted adaptively according to the system state and the proposed fuzzy compensation based on the Lyapunov stability theorem, so that the control system has the characteristics of low chattering effect and appropriate operation quality. Comprehensive evaluations of the waveforms are conducted for the new matrix converter through various simulations. Simulation results verify the effectiveness of the proposed adaptive control method for matrix converter in various conditions, and its superiority in chattering suppression in comparison to the conventional sliding mode control and the boundary layer method.
