High-performance control of inertial stabilization imaging sensors (ISISs) is always challenging because of the complex nonlinearities induced by friction, mass imbalance, and external disturbances. To overcome this problem, a terminal sliding mode controller (TSMC) based on a novel exponential reaching law (NERL) method with a high-order terminal sliding mode observer (HOTSMO) is suggested. First, the TSMC based on NERL is adopted to improve system performance. The NERL incorporates the power term and switching gain term of the system state variables into the conventional exponential reaching law, and the convergent speed of the TSMC is accelerated. Then, an HOTSMO is designed, which considers the speed and lumped disturbances of the system as the observation object. The estimated disturbance is then provided as a compensation for the controller, which enhances the disturbance rejection ability of the system. Comparative simulation and experimental results show that the proposed method achieves the best tracking performance and the strongest robustness than PID and the traditional TSMC methods.

Sensor differential signals are widely used in many systems. The tracking differentiator (TD) is an effective method to obtain signal differentials. Differential calculation is noise-sensitive. There is the characteristics of low-pass filter (LPF) in the TD to suppress the noise, but phase lag is introduced. For LPF, fixed filtering parameters cannot achieve both noise suppression and phase compensation lag compensation. We propose a fuzzy self-tuning tracking differentiator (FSTD) capable of adaptively adjusting parameters, which uses the frequency information of the signal to achieve a trade-off between the phase lag and noise suppression capabilities. Based on the frequency information, the parameters of TD are self-tuning by a fuzzy method, which makes self-tuning designs more flexible. Simulations and experiments using motion measurement sensors show that the proposed method has good filtering performance for low-frequency signals and improves tracking ability for high-frequency signals compared to fixed-parameter differentiator.

Scanning imaging can be used to obtain wide field-of-view, high-resolution remote-sensing images with a telescope lens. However, the motion between the image and the sensor causes blurring during scanning, which reduces the image quality. In this paper, a motion compensation method based on multi-actuator control with modal switching is proposed. In this method, the tracking controller realizes scanning and compensation; the cooperative controller reduces the relative motion that causes motion blur, and modal switching solves the travel limitation of the linear actuator. Further, to improve the control performance, an adaptive sliding mode controller is proposed and combined with a disturbance observer. The stability theorems for multi-actuator and modal switching are studied. Experimental results show that the accuracy, robustness, and frame rate of the proposed method improved compared with those of traditional methods. Compared with the non-cooperative structure using a PD controller, the root mean square error is reduced by $76.61\%$.

Vibration greatly impairs the imaging quality of airborne synthetic aperture ladar (SAL), so the vibration phase error must be estimated and compensated before imaging. Limited by the laser’s average power, the high pulse repetition frequency of the SAL will result in lower peak-power of the laser, thereby reducing the echo signal’s single-pulse signal-to-noise ratio (SNR). In the case of a low SNR, the coherence between channels worsens, and the vibration phase-error compensation method based on interferometry is difficult to apply. We analyze the imaging SNR and resolution of the echo signal when the airborne SAL observes noncooperative targets by intentionally broadening the transmitting and receiving beams, discussing the imaging processing flow of the low SNR signal under conditions of beam-broaden and platform vibration. The data processing flow includes the phase correction of the echo signal using the transmitting reference channel signal. Based on the flight parameters of the airborne SAL, the echo was dechirped and narrow-band filtered to reduce noise. After subaperture division, the spatial correlation algorithm was used to estimate and compensate the vibration phase error, and the range-Doppler algorithm was used to achieve strip imaging. At the same time, the phase gradient autofocus algorithm was introduced to improve the focusing effect. The processing results of flight experiment data of the airborne SAL corresponding to noncooperative targets at 1 km demonstrated the effectiveness of the proposed method.