The path following control under disturbance was studied for an underactuated unmanned surface vehicle (USV) subject to the rudder angle and velocity constraints. For this reason, a variable look-ahead integral line-of-sight (LOS) guidance law was designed on the basis of the disturbance estimation and compensation, and a cascade path following control system was created following the heading control law based on the model prediction. Firstly, the guidance law was designed using the USV three-degree-of-freedom (DOF) motion model and the LOS method, while the tracking error state was introduced to design the real-time estimation of disturbance observer and compensate for the influence of ocean current. Moreover, the stability of the system was analyzed. Secondly, sufficient attention was paid to the rudder angle and velocity constraints and the influence of system delay and other factors in the process of path following when the heading control law was designed with the USV motion response model and the model predictive control (MPC). The moving horizon optimization strategy was adopted to achieve better dynamic performance, effectively overcome the influence of model and environmental uncertainties, and further prove the stability of the control law. Thirdly, a simulation experiment was carried out to verify the effectiveness and advancement of the proposed algorithm. Fourthly, the “Sturgeon 03” USV was used in the lake test of the proposed control algorithm to prove its feasibility in the engineering practices.

The path following control under disturbance was studied for an underactuated unmanned surface vehicle (USV) subject to the rudder angle and velocity constraints. For this reason, a variable look-ahead integral line-of-sight (LOS) guidance law was designed on the basis of the disturbance estimation and compensation, and a cascade path following control system was created following the heading control law based on the model prediction. Firstly, the guidance law was designed using the USV three-degree-of-freedom (DOF) motion model and the LOS method, while the tracking error state was introduced to design the real-time estimation of disturbance observer and compensate for the influence of ocean current. Moreover, the stability of the system was analyzed. Secondly, sufficient attention was paid to the rudder angle and velocity constraints and the influence of system delay and other factors in the process of path following when the heading control law was designed with the USV motion response model and the model predictive control (MPC). The moving horizon optimization strategy was adopted to achieve better dynamic performance, effectively overcome the influence of model and environmental uncertainties, and further prove the stability of the control law. Thirdly, a simulation experiment was carried out to verify the effectiveness and advancement of the proposed algorithm. Fourthly, the “Sturgeon 03” USV was used in the lake test of the proposed control algorithm to prove its feasibility in the engineering practices.

To analyze the characteristics of the aeromagnetic scalar gradient detection method, a uniformly magnetized ellipsoid is used to simulate an unexploded ordnance, and a magnetic field detection model is established in the International Geomagnetic Reference Field based on rotation matrices. Furthermore, the spatial distribution of the target’s magnetic field is simulated. The results indicate that the scalar gradient detection curve is closely related to the unmanned aerial vehicle (UAV) heading, geomagnetic direction, and target attitude. According to the measured data, the aeromagnetic detection system exhibits differences in the detection of different headings, indicating that some “blind areas” exist in the scalar gradient magnetic detection method. The experimental measurement by a quadrotor UAV equipped with two optical pump magnetometers verifies that the scalar gradient detection method can effectively eliminate the geomagnetic field as well as the interferences of the UAV itself. Furthermore, the angular relationship between the target magnetic field contour distribution and the heading is found to be the main reason that the scalar gradient detection system enters the “blind detection area.” Therefore, a flight strategy of “positive direction + orthogonal grid” is proposed. This method effectively reduces the missed detection rate of scalar gradient detection and provides strategic guidance for the detection path of aeromagnetic scalar gradient system.