Application Of Background Noise Adaptive Cancellation In Magnetic Anomaly Detection

Using magnetic field anomalies to detect the target is a passive detection.Theoretically it can detect the existence of any ferromagnetic object on the earth,and is basically not affected by the weather.This paper modeled the magnetic anomaly signal,and analyzed the characteristics of magnetic anomaly signal and the characteristics of geomagnetic fields both in time domain and frequency domain,the similarities and differences of magnetic anomaly signal and geomagnetic field are summarized by comparing the characteristics of the two,then the adaptive noise cancellation method is used to detect the magnetic anomaly signals.Due to the partial overlap of magnetic anomaly signals and geomagnetic signals in the frequency domain,in this paper,two sensors are used to measure the magnetic signal,one is mainly used to measure the geomagnetic background noise signal,and the other is mainly used to detect the magnetic anomaly signal.The adaptive coherent noise suppression algorithm is adopted for these two signals to suppress the geomagnetic background in the full frequency domain.Considering the existence of geomagnetic gradient and the interference of geomagnetic diurnal variation,and the prominence of magnetic anomaly signals in the triaxial component of geomagnetic field and the flat background signal,we propose an improved adaptive coherent noise suppression algorithm based on multidimensional signals,which improves and optimizes the original algorithm from the aspects of signal preprocessing,detection calculation and subsequent waveform processing.The effectiveness of the algorithm is verified by simulation analysis.The SNR of the improved algorithm is 16 d B higher than that of the original algorithm.Considering the natural gradient and diurnal variation of geomagnetic field,as well as the accuracy of probability density estimation,we proposed an improved minimum entropy detector based on multi-dimensional differential signals.Kernel density estimation is used to calculate the probability density function of the normal geomagnetic field,then the triaxial components are respectively differentiated and entropy is calculated.Finally,the final result is calculated by adaptive linear weighting.The algorithm improved in this paper performs better than the original one,which can be indicated through the simulation results.In this paper,OSVI-CFAR detector is used to carry out adaptive calculation on the early warning threshold of the output signal,which can accurately identify the target signal.We carried out several outdoor experiments and collected a large number of geomagnetic field data in different places and magnetic field data containing target signals.By analyzing and calculating the experimental data,the validity of the two algorithms is verified,and the detection of magnetic abnormal signals is realized.The results show that our method is better than the OBF method.