Wavelet transform based error detection in signal acquired from artillery unit

In real time environment, noise often embeds with the signal during data acquisition process. Error detection will be difficult task when signals are corrupted with noise. Therefore, noise removal is the first step towards the detection of error in signal acquired from artillery unit. In this work, wavelet based signal enhancement technique is proposed to remove the noise from acquired signal. Doubechies wavelet with order 1 is used to decompose the signal up to four levels. Empirically chosen thresholds are applied in each detail coefficient and the denoised signal is reconstructed using the approximation coefficient and threshold detail coefficients. To detect the error, Doubechies wavelet with order 6 is applied to decompose the enhanced signal up to four-level. Each detail coefficient represents the distortion if original signal is erroneous. The proposed method is tested by means of signal to noise ratio, average power and spectrogram analysis. Experimental results show that the performance of the proposed method is consistently well at different SNR both off line testing and online testing, and also able to detect the error properly.