Differential fuzzy filtering for adaptive line enhancement in spread spectrum communications

Bas, Joan; Pérez, Alfonso; Lagunas, M.A.

doi:10.1016/j.sigpro.2005.08.002

Cited by 5 publications

(4 citation statements)

References 26 publications

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“…NBI rejection capability of a DSSS system can be enhanced by suitably processing the received signal prior to correlating it with the PN code 7. Over the past two decades, a significant body of research has been concerned with the development of interference suppression techniques in spread spectrum systems, such as those processing the signal in the time domain 8–11 particularly adaptive filtering 12, 13 and in the transform/frequency domain 14–16 including wavelet transform (WT) 17. Some of these techniques take advantage of the knowledge of the wide spectral shape of the desired signal's spectrum when compared with the interferer's narrow spectrum.…”

Section: Introductionmentioning

confidence: 99%

On‐line wavelet filtering of narrowband noise in signal detection of spread spectrum system for location tracking

Luo¹

2011

Int J Communication

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SUMMARY Spread spectrum signal transmitted by wireless channel for location tracking can be severely corrupted by noise due to external disturbances. Narrowband noise is the most effective interference that can make measurement signal undetected. However, the current methods for narrowband interference (NBI) suppression are either very time‐consuming or add distortion to the signal received. In this paper, an adaptive Gaussian wavelet filter with optimal time–frequency localization and variable notch depth is proposed to suppress a large number of NBIs with additive white Gaussian noise and pulsed noise that interfere with the spread spectrum communication system. The filtering of both continuous and time‐varying NBIs with fast resampling is performed in conjunction with the fast Fourier transform‐based correlation for peak detection, and is computationally efficient for real‐time operation of signal detection. The performance of the adaptive filter has been evaluated by experiments employing a reliable noise detector. Experimental results demonstrate that the proposed wavelet filter isolates the signals from the NBI in accordance with the corrupted frequency contents while preserving the desired spread spectrum signal, and improves signal to noise ratio for peak detection leading to higher accuracy of timing measurement for real‐time wireless location. Copyright © 2011 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

On‐line wavelet filtering of narrowband noise in signal detection of spread spectrum system for location tracking

Luo¹

2011

Int J Communication

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“…Narrow-band interference rejection capability of a DSSS system can be enhanced by suitably processing the received signal prior to correlating it with the PN code [25]. Over the past two decades, a significant body of research has been concerned with the development of interference suppression techniques in spread-spectrum systems, such as those processing the signal in the time domain [2,3,11,20] particularly adaptive filtering [5,19] and in the transform/frequency domain [4,16,24] including wavelet transform [14]. Some of these techniques take advantage of the knowledge of the wide spectral shape of the desired signal's spectrum as compared to the interferer's narrow spectrum.…”

Section: Introductionmentioning

confidence: 99%

Wavelet Notch Filter Design of Spread-Spectrum Communication Systems for High-Precision Wireless Positioning

Luo

2011

Circuits Syst Signal Process

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Spread-spectrum communication systems are now commonly used in the field of cellular telephone positioning. However, wireless positioning systems by lowpower spread-spectrum communication are extremely vulnerable to high-power interference, which limits achievable measurement precision. In this paper, a bandwidth variable wavelet notch filter design method is proposed to suppress a large number of jammers in multiple locations with noise interfering with spread-spectrum systems. The filter uses combinations of Gaussian wavelets with optimal time-frequency localization and computational efficiency for real-time operation of denoising. The performance of the adaptive filter has been evaluated by experiments associated with a spread-spectrum communication system model employing a reliable noise detector to locate the filter notch. Experimental results demonstrate that the proposed wavelet notch filter removes the narrow-band interference in accordance with the corrupted frequency contents while minimizing signal distortion and information loss, which leads to high-precision wireless positioning.

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“…Nevertheless, the linguistic information is a feature of the human reasoning and not of the mechanical components or programs. In consequence, this tool has achieved widespread applications and success in many areas such as control, supervision, image filtering and communications [6][7][8][9]. The essential characteristics of fuzzy logic are as follows [10]:…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Filtering of Sensors Signals in Manufacturing Systems with Time Constraints

Mhalla¹,

Jerbi²,

Dutilleul

et al. 2010

INT J COMPUT COMMUN

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Abstract:The presented work is dedicated to the supervision of manufacturing job-shops with time constraints. Such systems have a robustness property towards time disturbances. The main contribution of this paper is a fuzzy filtering approach of sensors signals integrating the robustness values. This new approach integrates a classic filtering mechanism of sensors signals and fuzzy logic techniques. The strengths of these both techniques are taken advantage of the avoidance of control freezing and the capability of fuzzy systems to deal with imprecise information by using fuzzy rules. Finally, to demonstrate the effectiveness and accuracy of this new approach, an example is depicted. The results show that the fuzzy approach allows keeping on producing, but in a degraded mode, while providing the guarantees of quality and safety based on expert knowledge integration.

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Differential fuzzy filtering for adaptive line enhancement in spread spectrum communications

Cited by 5 publications

References 26 publications

On‐line wavelet filtering of narrowband noise in signal detection of spread spectrum system for location tracking

On‐line wavelet filtering of narrowband noise in signal detection of spread spectrum system for location tracking

Wavelet Notch Filter Design of Spread-Spectrum Communication Systems for High-Precision Wireless Positioning

Fuzzy Filtering of Sensors Signals in Manufacturing Systems with Time Constraints

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