Step and stare imaging with staring arrays has become the main approach to realizing wide area coverage and high resolution imagery of potential targets. In this paper, a backscanning step and stare imaging system is described. Compared with traditional step and stare imaging systems, this system features a much higher frame rate by using a small-sized array. In order to meet the staring requirements, a fast steering mirror is employed to provide backscan motion to compensate for the image motion caused by the continuously scanning of the gimbal platform. According to the working principle, the control system is designed to step/stare the line of sight at a high frame rate with a high accuracy. Then a proof-of-concept backscanning step and stare imaging system is established with a CMOS camera. Finally, the modulation transfer function of the imaging system is measured by the slanted-edge method, and a quantitative analysis is made to evaluate the performance of image motion compensation. Experimental results confirm that both high frame rate and image quality improvement can be achieved by adopting this method.

This article proposes a comprehensive approach to achieve high-precision modeling, high bandwidth, and robust control for the voice coil actuator fast steering mirror (VCA-FSM). This approach includes the Hankel matrix identification method, $H_{\infty }$ sensitivity control, disturbance observer (DOB), and zero phase error tracking control (ZPETC) algorithms. The superiority and practicality of the proposed control techniques are discussed by comparing control methods, such as $H_{\infty }$ , sliding mode control (SMC), linear-quadratic-regulator (LQR), and proportional-integral-derivative (PID) through experiments. Especially, this proposed method serves as a good guide for controller designs of other servo mechanisms.

Fast steering mirrors (FSMs) have been used for decades to improve the performance of electro-optical imaging systems, such as airborne imaging systems and space-based optical surveillance systems. With the advantage of increasing the accuracy of image motion compensation and the efficiency of scanning imaging, backscanning step-and-stare imaging has become the main approach to realizing wide-area surveillance for airborne imaging systems. According to the operating mode and motion profile of the FSM in the imaging system, a combined optimized profile (COP) is designed to avoid abrupt changes in the velocity and acceleration of the FSM. The angular position sensor based on a four-quadrant detector is used in FSMs to expand the measuring range and cut the cost at the expense of larger measurement noise. Combining a Kalman filter with a disturbance observer and zero-phase error tracking control, a control method is proposed to improve the control precision and bandwidth while suppressing measurement noise. Simulation and experimental results show that the profile designed by COP is smooth enough to meet the special requirements of FSM’s backscanning image motion compensation and that the Kalman filter-based FSM control method can significantly improve the control accuracy.

This article proposes an enhanced disturbance observer (DOB) design method to address the high-bandwidth control challenges of flexible fast steering mirror (FSM) systems. FSMs rapidly adjust mirror orientation through precision control systems, enabling them to meet the dynamic tracking requirements of various high-precision optical applications. Due to the stringent precision demands of optical systems, FSMs are susceptible to external disturbances, sensor measurement noise, and parameter variations. DOB is widely employed in motion control systems to estimate and compensate for these disturbances. However, existing DOB design methods often rely on oversimplified models, treating dynamic characteristics such as flexible resonance as model uncertainties, which limits their performance in flexible systems. Through a comprehensive analysis, this article demonstrates that in flexible resonant systems, the disturbance estimation bandwidth of the existing DOB is frequently constrained by robust stability requirements, leading to suboptimal performance. With the increasing demands on the control bandwidth of FSMs driven by modern technological advancements, model mismatches arising from high-frequency unmodeled dynamics have become a critical bottleneck. Existing DOB is unable to effectively address model mismatches in the high-frequency range of flexible systems. This article proposes an enhanced DOB design method based on the $H_{\infty } $ control framework and Hankel matrix system identification, which simultaneously satisfies multiple performance indicators. By precisely selecting the nominal model and estimating uncertainties, the existing DOB design method is optimized. Experimental results demonstrate that the proposed enhanced DOB effectively suppresses external disturbances and model mismatches, significantly improving the system’s disturbance rejection performance compared to existing methods.

In order to address the realtime performance and robustness issues in UAV aerial image stitching, an improved SURF-based algorithm is proposed. This algorithm enhances the stitching process for UAV aerial images by first employing the Speeded-Up Robust Features SURF algorithm for rapid and robust feature point detection and localization. Subsequently, binary BRISK descriptors are used for feature description. In the feature matching phase, an initial coarse matching is performed using the Nearest-Neighbor Distance Ratio NNDR algorithm to filter out correct match pairs. Then, precise matching is achieved through the application of the PROSAC algorithm. Finally, a weighted fusion algorithm is employed for seamless image stitching. Experimental results demonstrate significant improvements in both matching efficiency and accuracy achieved by this algorithm. It serves as a robust and highly accurate solution with excellent stitching outcomes for UAV aerial image stitching.