Peculiarities of Correlation Processing of Pseudo Noise Signals in Controlled-Source Electromagnetic Instruments

Abstract—The paper presents the algorithm for eliminating structured noise (SN) appearing in the transient electromagnetic (TEM) response curves during correlation processing of recorded pseudo noise signals. The algorithm is based on the detection and elimination of pulses of structured noise (SNP) with energies exceeding optimal detection threshold (calculated from the TEM curve) against the background of the smoothly (slowly) varying TEM sounding signal. The method provides reliable SNP detection with high correct recognition and low false alarm rate as well the subsequent elimination of SN field from the recorded TEM curves. For automatic calculation of SNP optimal detection threshold, it is proposed to use the criterion that the noise and interference signals remaining in the TEM curve after SNP removal are maximally close to normal distribution. Selection and setting of the optimal detection threshold is performed by successive sweep through its values (from maximum to minimum) with a given step which determines the accuracy of detection threshold. The procedure of selecting the detection threshold is reduced to finding, at each step, the maximum value of the Pearson correlation coefficient between the probability density distribution functions of amplitudes of noise and interference signals remaining in TEM curve after SN removal and the calculated normal distribution. This approach has made data processing maximally automated and increased its speed, which is very important in the field work. The algorithm was tested on TEM signals recorded at Chunkurchak experimental site in the field work with electromagnetic measurement system using pseudo noise signals (EMS PNS). Application of the algorithm has significantly improved (approximately by a factor of 450) the signal to noise ratio in the TEM response curve in the interval of late times.