To reduce the impact of magnetization direction and stripe noise on the positioning accuracy of magnetic target and improve the positioning accuracy of underground shallow unexploded ordnance with different attitudes, this paper studies a normalized magnetic source intensity localization method based on Gaussian convolutional kernel. The traditional normalized magnetic source intensity method is not affected by the magnetization direction, but the stripe noise generated by the method itself can affect the positioning result. The use of Gaussian convolutional kernel can eliminate the influence of stripe noise. The actual flight test shows that the proposed method can eliminate stripe noise and is not affected by magnetization direction, and the maximum positioning error for five different attitudes of simulated unexploded ordnance on the ground is less than 15cm. Therefore, this method can be used for high-precision positioning of underground shallow unexploded ordnance with different attitudes.
For the impact of magnetic prospecting unmanned aerial vehicle route planning on the positioning accuracy of simulated unexploded ordnance, we conduct unmanned aeromagnetic prospecting flight tests and complete the localization of simulated unexploded ordnance using the normalized magnetic source intensity method, then analyze the localization results. The results indicate that as the survey line interval decreases to 0.5 m, the positioning error tends to stabilize. As the flight speed decreases from 5 m/s to 1 m/s, the positioning accuracy is significantly improved. As the flight altitude decreases from 3m to 1.5m, the positioning error decreases. By analyzing the impact of key parameters in magnetic prospecting unmanned aerial vehicle route planning on the positioning accuracy of simulated unexploded ordnance, we provide an empirical reference for the efficient and safe detection strategy of unexploded ordnance.
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