Unmanned Aerial Vehicles (UAVs) have recently shown great performance collecting visual data through autonomous exploration and mapping, which are widely used in reconnaissance, surveillance, and target acquisition (RSTA) applications. In this paper, we present an onboard vision-based system for low-cost UAVs to autonomously track a moving target. Real-time visual tracking is achieved by using an object detection algorithm based on the Kernelized Correlation Filter (KCF) tracker. A 3-axis gimbaled camera with separate Inertial Measurement Unit (IMU) is used to aim at the selected target during flights. The flight control algorithm for tracking tasks is implemented on a customized quadrotor equipped with an onboard computer and a microcontroller. The proposed system is experimentally validated by successfully chasing a ground and aerial target in an outdoor environment, which has proven its reliability and efficiency.

In this paper, an onboard vision-based system for the autonomous landing of a low-cost quadrotor is presented. A novel landing pad with different optical markers sizes is carefully designed to be robustly recognized at different distances. To provide reliable pose information in a GPS (Global Positioning System)-denied environment, a vision algorithm for real-time landing pad recognition and pose estimation is implemented. The dynamic model of the quadrotor is established and a system scheme for autonomous landing control is presented. A series of autonomous flights have been successfully performed, and a video of the experiment is available online. The efficiency and accuracy of the presented vision-based system is demonstrated by using its position and attitude estimates as control inputs for the autonomous landing of a self-customized quadrotor.

In recent years, the strapdown system has become the significant trend of the development of precision guided weapons. In order to effectively hit the lightly armored targets, researchers have done a series of studies on the impact angle control. However, most of them ignored the field-of-view constraint of the strapdown seeker. The existing impact angle control guidance laws with the field-of-view constraint have obvious drawbacks to some extent. For example, most of them are only applicable against nonmaneuvering targets and some of them suffer sudden hopping of guidance command due to the use of switching logic. Taking the strapdown seeker missile as the research object, this paper studies the field-of-view constrained impact angle control guidance problem against stationary targets, constant speed targets and maneuvering targets. According to the sliding mode control theory, two kinds of sliding surfaces are designed to make the missile achieve high precision attack under a desired impact angle within the field-of-view constraint. A quadratic barrier Lyapunov function and a logarithm barrier Lyapunov function are used to guarantee that the sliding surfaces designed for the impact angle constraint and the field-of-view constraint can converge to zero in finite time respectively. Then, a nonlinear extended state observer is proposed to estimate the unmeasurable disturbance of the system and alleviate the undesirable chattering by compensating it with the estimation of the disturbance. Finally, the feasibility of the proposed law is verified by numerical simulations.

The proportional integral differential (PID) controller is improved to meet control system requirements for the boost-glide rocket with difficulty in manual adjusting parameters. A method is proposed that directly takes the simulated results with the nonlinear six-degree-freedom model of the rocket as the objective function value, the genetic algorithm is adopted to adjust parameters adaptively for the global optimal control effect with a given range, and the convergence of the algorithm to search the global optimal value under given conditions is analyzed. This method introduces the measured angular velocity into the differential term of the PID controller, which is convenient to establish the system model and adjust control parameters. Parameter adjustment based on the nonlinear dynamic model can avoid deviations caused by model linearization and facilitate parallel search by genetic algorithm, then reasonable parameters can be quickly obtained with the specified value range. The proposed method is compared with the classical test method in time domain simulation. The simulated results indicate that the proposed method can adjust the parameters adaptively, the maximum deviation of attitude angle is less than 2°, the mean of deviation and the standard deviation of attitude angle deviation are less than 1°, and the control precision is obviously better than that of the classical test method. The experiments from the hardware-in-the-loop simulation show that the attitude control of the selected control parameters is stable, the deviation converges to 0°, and the control effect is good.

A prerequisite for implementing precision strike is to keep the target locked within the seeker’s field-of-view (FOV). To address this constraint, a novel impact angle control guidance law based on the dynamic surface control and time-varying asymmetric Barrier Lyapunov Function is proposed. The FOV constraint, in this paper, is equally transformed to a time-varying asymmetric limitation on the missile-target relative velocity perpendicular to the line-of-sight (LOS). Under the proposed guidance law, the velocity component is prevented from overstepping its limitation and eventually approaches zero, thus satisfying the homing requirement and the FOV constraint in an integrated manner. Compared to previous studies, the proposed guidance law does not require the target information and is applicable against moving targets. Also, the proposed guidance law does not use any switching logic, and consequently the synthesized guidance command is free from abrupt-jumping phenomenon. Numerical simulations and performance comparison fully demonstrates the effectiveness and superiority of the proposed guidance law.

For a given device, the rapidity and accuracy of device error coefficient calibration and attitude alignment of the rotational inertial navigation system mainly depend on the convergence rate of the nonlinear filtering algorithm. The traditional extended Kalman filter method has no theoretical convergence guarantee for non-linear systems and requires a long time in the actual calibration process. Since the attitude is subject to the 3-dimensional rotation transformation group, the error transfer equation can be better linearized by defining the error on the lie group to use the new observation information fully. This paper proposes a primary method of using the invariant extended Kalman filter to carry out an inertial navigation system. In the continuous rotation of the framework, the accelerometer, gyroscope, and framework angle are used to calibrate the error coefficient of the accelerometer and gyroscope and estimate the base alignment error Angle. Simulation and experiment results show that the proposed method can accomplish alignment and calibration in 10 minutes under a large initial attitude error.