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This paper presents a novel automatic carrier landing controller which holds a constant angle of attack during final approach with prescribed performance in the presence of external disturbances and carrier deck motion. Based on the nonlinear model of the aircraft, backstepping technique is adopted as the main control frame. To improve the stability during final approach, a novel control structure which maintains a constant angle of attack is proposed. By using performance constrained guidance law, the proposed controller is capable of guaranteeing trajectory tracking errors within prescribed performance, which means that the tracking errors are confined within prescribed convergence rates and maximum overshoots. Moreover, considering the deck motion of the carrier and inherent phase lag of the aircraft, deck motion compensation is included. Furthermore, nonlinear disturbance observers are introduced to eliminate the affects of unknown disturbances, while command filters are employed as well, avoiding complicated computations for time derivatives of virtual controls. Finally, simulation results clarify and verify the proposed control scheme.

In inverse synthetic aperture radar (ISAR) systems, image quality often suffers from the non-uniform rotation of non-cooperative targets. Rotational motion compensation (RMC) is necessary to perform refocused ISAR imaging via estimated rotational motion parameters. However, estimation errors tend to accumulate with the estimated processes, deteriorating the image quality. A novel RMC algorithm is proposed in this study to mitigate the impact of cumulative errors. The proposed method uses an iterative approach based on a novel criterion, i.e., the minimum residual norm of the signal phases, to estimate different rotational parameters independently to avoid the issue caused by cumulative errors. First, a refined inverse function combined with interpolation is proposed to perform the RMC procedure. Then, the rotation parameters are estimated using an iterative procedure designed to minimize the residual norm of the compensated signal phases. Finally, with the estimated parameters, RMC is performed on signals in all range bins, and focused images are obtained using the Fourier transform. Furthermore, this study utilizes simulated and real data to validate and evaluate the performance of the proposed algorithm. The experimental results demonstrate that the proposed algorithm shows dominance in the aspects of estimation accuracy, entropy values, and focusing characteristics.

Fatigue cracks that develop in civil infrastructure such as steel bridges due to repetitive loads pose a major threat to structural integrity. Despite being the most common practice for fatigue crack detection, human visual inspection is known to be labor intensive, time-consuming, and prone to error. In this study, a computer vision-based fatigue crack detection approach using a short video recorded under live loads by a moving consumer-grade camera is presented. The method detects fatigue crack by tracking surface motion and identifies the differential motion pattern caused by opening and closing of the fatigue crack. However, the global motion introduced by a moving camera in the recorded video is typically far greater than the actual motion associated with fatigue crack opening/closing, leading to false detection results. To overcome the challenge, global motion compensation (GMC) techniques are introduced to compensate for camera-induced movement. In particular, hierarchical model-based motion estimation is adopted for 2D videos with simple geometry and a new method is developed by extending the bundled camera paths approach for 3D videos with complex geometry. The proposed methodology is validated using two laboratory test setups for both in-plane and out-of-plane fatigue cracks. The results confirm the importance of motion compensation for both 2D and 3D videos and demonstrate the effectiveness of the proposed GMC methods as well as the subsequent crack detection algorithm.

The wide-field imaging system carried on a high-altitude or near-space vehicle takes high-resolution images of the ground to measure and map targets. With the improvement of imaging resolution and measurement accuracy, the focal length of the wide-field imaging system is getting longer. The requirement for image motion compensation (IMC) accuracy is getting higher, and the influence of optical path coupling is increasing within the process of two-dimensional (2D) IMC. To further improve the IMC accuracy of the wide-field imaging system, an innovative IMC method is first proposed in this paper. The method is based on the 2D motion of the scanning platform and secondary mirror. Secondly, to solve the optical coupling problem in the process of 2D IMC, the coupling phenomenon is analyzed. The coupling relationships between 2D scanning motion, 2D secondary mirror motion and image motion is derived from the compensation process. A complete 2D IMC model is established, and a 2D IMC method, including an optical path decoupling correct regulator (ODCR), is designed. Finally, the method is verified in laboratory and field flight tests. The results show that the proposed method can effectively correct the coupling error of the optical path in the process of IMC and achieve high-resolution 2D IMC. When the scanning speed is 60°/s and the exposure time is 2 ms, the accuracy of the 2D IMC is up to 0.57pixels (RMS) in the pitch direction, and 0.46 pixels (RMS) in the roll direction.

Synthetic aperture radar (SAR) is a critical enabling technology for maritime surveillance. However, maneuvering ships often appear defocused in SAR images, posing significant challenges for subsequent ship detection and recognition. To address this problem, this study proposes an improved iteration phase gradient resampling autofocus (IIPGRA) method. First, we extract the defocused ships from SAR images, followed by azimuth decompression and translational motion compensation. Subsequently, a centerline-driven adaptive azimuth partitioning strategy is proposed: the geometric centerline of the vessel is extracted from coarsely focused images using an enhanced RANSAC algorithm, and the target is partitioned into upper and lower sub-blocks along the azimuth direction to maximize the separation of rotational centers between sub-blocks, establishing a foundation for the accurate estimation of spatially variant phase errors. Next, phase gradient autofocus (PGA) is employed to estimate the phase errors of each sub-block and compute their differential. Then, resampling the original echoes based on this differential phase error linearizes non-uniform rotational motion. Furthermore, this study introduces the Rotational Uniformity Coefficient (β) as the convergence criterion. This coefficient can stably and reliably quantify the linearity of the rotational phase, thereby ensuring robust termination of the iterative process. Simulation and real airborne SAR data validate the effectiveness of the proposed algorithm.

The multichannel synthetic aperture radar (SAR) possesses the capability to acquire high-resolution, wide-swath SAR imagery, which has great potential for application. However, similar to traditional single-channel SAR systems, it suffers from imaging quality degradation due to motion errors. Many motion compensation algorithms have been used to improve the quality of single-channel SAR images, while fewer studies have been conducted on multichannel SAR motion compensation methods. The sub-image motion compensation method utilizes the single channel motion errors to perform multichannel motion errors compensation, considering that multiple channels have the same phase errors. To improve the quality of multichannel SAR imaging when multiple channel motion errors are inconsistent, this paper proposes a motion compensation method with multichannel phase correction for HRWS SAR. First, the method derives the phase errors estimation model via maximum sharpness to simultaneously estimate multichannel phase. Then, it compensates for the motion errors of all channels during backprojection imaging. The inconsistent motion errors of multiple channels can be compensated by estimating the phase errors of all channels, improving the image quality. The channel phase errors can be corrected while compensating for the motion errors. Moreover, the experimental results of point targets and complex scenes validate the effectiveness of the proposed method.

This paper addresses the automatic carrier landing problem in the presence of deck motion, carrier airwake disturbance, wind shears, wind gusts, and atmospheric turbulences. By transforming the 6-DOF aircraft model into an affine dynamic with angle of attack controlled by thrust, the equations associated to the resultant disturbances are deduced; then, a deck motion prediction block (based on a recursive-least squares algorithm) and a tracking differentiator-based deck motion compensation block are designed. After obtaining the aircraft reference trajectory, the backstepping control method is employed to design a novel automatic carrier landing system with three functional parts: a guidance control system, an attitude control system, and an approach power compensation system. The design of the attitude subsystem involves the flight path control, the control of the attitude angles, and the control of the angular rates. To obtain convergence performance for the closed-loop system, the backstepping technique is combined with sliding mode-based command differentiators for the computation of the virtual commands and extended state observers for the estimation of the disturbances. The global stability of the closed-loop architecture is analyzed by using the Lyapunov theory. Finally, simulation results verify the effectiveness of the proposed carrier landing system, the aircraft reference trajectory being accurately tracked.

Translational motion compensation constitutes a pivotal and essential procedure in inverse synthetic aperture radar (ISAR) imaging. Many researchers have previously proposed their methods to address this requirement. However, conventional methods may struggle to produce satisfactory results when dealing with non-stationary moving targets or operating under conditions of low signal-to-noise ratios (SNR). Aiming at this challenge, this article proposes a parametric non-search method that contains two main stages. The radar echoes can be modeled as polynomial phase signals (PPS). In the initial stage, the energy of the received two-dimensional signal is coherently integrated into a peak point by leveraging phase difference (PD) and Lv’s distribution (LVD), from which the high-order polynomial coefficients can be obtained accurately. The estimation of the first-order coefficients is conducted during the second stage. The auto-cross-correlation function for range profiles is introduced to enhance the accuracy and robustness of estimation. Subsequently, a novel mathematical model for velocity estimation is proposed, and its least squares solution is derived. Through this model, a sub-resolution solution can be obtained without requiring interpolation. By employing all the estimated polynomial coefficients, the non-stationary motion of the target can be fully compensated, yielding the acquisition of a finely focused image. Finally, the experimental findings validate the superiority and robustness of the proposed method in comparison to state-of-the-art approaches.

When a target is moving at high-speed, its high-resolution range profile (HRRP) will be stretched by the high-order phase error caused by the high velocity. In this case, the inverse synthetic aperture radar (ISAR) image would be seriously blurred. To obtain a well-focused ISAR image, the phase error induced by target velocity should be compensated. This article exploits the variation continuity of a high-speed moving target’s velocity and proposes a noise-robust high-speed motion compensation algorithm for ISAR imaging. The target’s velocity within a coherent processing interval (CPI) is modeled as a high-order polynomial based on which a parametric high-speed motion compensation signal model is developed. The entropy of the ISAR image after high-speed motion compensation is treated as an evaluation metric, and a parametric minimum entropy optimization model is established to estimate the velocity and compensate it simultaneously. A gradient-based solver of this optimization is then adopted to iteratively find the optimal solution. Finally, the high-order phase error caused by the target’s high-speed motion can be iteratively compensated, and a well-focused ISAR image can be obtained. Extensive simulation experiments have verified the noise robustness and effectiveness of the proposed algorithm.

Terahertz Synthetic Aperture Radar (THz-SAR) is highly sensitive to platform vibrations and trajectory deviations, which introduce severe phase errors and limited resolution. Typically, platform vibrations and trajectory deviations are investigated individually, and vibrations are modeled as a stationary sine term. In this work, a hybrid motion compensation (MOCO) scheme is proposed to address both platform vibrations and trajectory deviations simultaneously, achieving improved imaging quality. The scheme initiates with a parameter self-adaptive quadratic Kalman filter designed to resolve severe phase wrapping. Then, platform vibration is modeled as a non-stationary multi-sine term, whose components are accurately extracted using an improved signal decomposition algorithm enhanced by a dynamic noise adjustment mechanism. Subsequently, the trajectory deviation is parameterized following subaperture division, estimated using a hybrid optimizer that combines particle swarm optimization and gradient descent. Additionally, a composite modulated waveform application ensures low sidelobes and a low probability of intercept (LPI). Extensive simulations on point targets and complex scenes under various signal-to-noise-ratio (SNR) conditions are applied for SAR image reconstruction, demonstrating robust suppression of motion errors. Under identical simulated error conditions, the proposed method achieves an azimuth resolution of 4.28 cm, which demonstrates superior performance compared to the reported MOCO techniques.