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

• Authors: G. Y. Luo
• Venue: International Journal of Communication Systems
• Year: 2012

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. (The technology innovation of the proposed filtering lies in that the developed wavelet filter with the property of optimal time-frequency localization and with notch depth adjusted with respect to the interference power at the frequency located by noise detection can effectively suppress interferences in real-time in the receiver, while maintaining a minimal distortion and information loss.)