Edge detection is a requisite task in the interpretation of potential field data. The existed edge detectors have the disadvantages that they cannot balance the edges of strong and weak amplitude anomalies simultaneously, or the identified edges of deep geological bodies are divergence and fuzzy. In order to overcome this problem, this paper presents the normalized enhanced analytic signal detectors to extract the edges, which can improve the disadvantages effectively. The normalized enhanced analytic signal detectors use different orders vertical derivatives of potential field data to normalize the different orders enhanced analytic signals. The new detectors are tested on synthetic gravity data, which can not only display the edges of shallow and deep geological bodies clearly at the same time, also can identify the edges more precisely and clearly. Finally, these detectors are demonstrated on real gravity and magnetic data from China, which can bring out more edge information.

In order to further improve the performance of compound UAVs at high and low speed with heavy loading, a type of compound coaxial UAV with fixed wings and tail ducted-rotor thrusters was proposed to meet technology requirement. The lift and thrust aerodynamic characteristics were analyzed to get some relative characteristic and the aerodynamic coupling relationships between the fixed wings and tail propulsion system. And an optimization method based on hybrid Fuzzy-PSO (HFPSO) algorithm was proposed to obtain the optimal configuration plan that can reach the best aerodynamic performance without considering the coaxial architecture. The optimal configuration plan was finally obtained by applying the HFPSO method which also proves the method is effective and reasonable through comparison.

No abstract