On Denoising of Spread Spectrum Communication for Wireless Location

Wireless location by spread spectrum communication can be severely corrupted by noise. Narrowband noise is the most effective interference that can make measurement signal undetected. In this paper, an adaptive wavelet filter is presented to suppress single and multiple narrowband interferences with additive white Gaussian noise that interferes with spread spectrum signals. The filter uses combinations of Gaussian wavelets with optimal time-frequency localization and computational efficiency for real-time denoising. The performance of the wavelet filter has been evaluated by experiments with spread spectrum communication system. Experimental results demonstrate that the proposed wavelet filter mitigates the narrowband noise in accordance with the corrupted frequency contents, and improves signal to noise ratio (SNR) for peak detection leading to higher accuracy of timing measurement for real-time wireless location.