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With the development of structural topology optimization methods, some scholars had proposed strategies to integrate existing topology optimization methods to improve the manufacturability of topology optimization result. Specifically, a topology optimization method combined the Solid Isotropic Material Penalty（SIMP） method and the Moving Morphable Components（MMC） method was proposed. Firstly, the characteristics of power function in SIMP method was used to quickly obtain the main path of force transfer. Secondly, according to the gray-scale elements generated by the SIMP method, an Otsu threshold algorithm was proposed to maximize response of the binary topological structure. On this basis, morphological thought was used to construct a component, whose boundary was the inflection point of the skeleton, then the MMC method was used to complete the optimization to finally achieve the precise control of structure size. By calculating the minimum compliance topology optimization problem of the 2 D and 3 D numerical examples, the optimization results of smooth boundary and precise size of structure are obtained, verifying the effectiveness of proposed method.

High-precision lunar scene 3D data are essential for lunar exploration and the construction of scientific research stations. Currently, most existing data from orbital imagery offers resolutions up to 0.5–2 m, which is inadequate for tasks requiring centimeter-level precision. To overcome this, our research focuses on using in situ stereo vision systems for finer 3D reconstructions directly from the lunar surface. However, the scarcity and homogeneity of available lunar surface stereo datasets, combined with the Moon's unique conditions—such as variable lighting from low albedo, sparse surface textures, and extensive shadow occlusions—pose significant challenges to the effectiveness of traditional stereo matching techniques. To address the dataset gap, we propose a method using Unreal Engine 4 (UE4) for high-fidelity physical simulation of lunar surface scenes, generating high-resolution images under realistic and challenging conditions. Additionally, we propose an optimized cost calculation method based on Census transform and color intensity fusion, along with a multi-level super-pixel disparity optimization, to improve matching accuracy under harsh lunar conditions. Experimental results demonstrate that the proposed method exhibits exceptional robustness and accuracy in our soon-to-be-released multi-scene lunar dataset, effectively addressing issues related to special lighting conditions, weak textures, and shadow occlusion, ultimately enhancing disparity estimation accuracy. [ABSTRACT FROM AUTHOR]

In this article, the parameter identification problem of the output error model is investigated under the application requirement of online parameter identification of a two‐degree‐of‐freedom servo turntable system. To eliminate the influence of colored noise in the observed output signal of the output error model on the algorithm identification accuracy, the momentum factor is introduced into the innovation term of the recursive least squares algorithm, and the momentum‐innovation recursive least squares (MI‐RLS) algorithm is proposed. Further, to improve the convergence speed and identification accuracy of the algorithm while avoiding increasing the algorithm complexity significantly, a reframed multi‐innovation strategy is introduced, and a momentum reframed multi‐innovation least squares (MR‐MILS) algorithm is developed. After analyzing the complexity of the proposed algorithms, the convergence performances of the two algorithms are verified using the theory of martingale convergence, and the results show that the reframed multi‐innovation strategy can accelerate the convergence speed of the MR‐MILS algorithm. The effectiveness of the proposed identification approach is demonstrated via simulation results. [ABSTRACT FROM AUTHOR]

The interference caused by stray light leads to the invalid attitude of star sensors in orbit, thus affecting the attitude control of satellites. In order to overcome this problem, this paper proposes a fast star-detection algorithm with strong stray-light suppression ability. The first step in the proposed method is stray-light suppression. The highlighted pixels are unified and then erosion and dilation operations based on a large template are performed. Using the background image only, which is filled with stray light, the cleaner star image is obtained by subtracting the background from the unified image. The second step in the proposed method is binarization. The binary star image is obtained by using a line-segment strategy combined with a local threshold. The third step in the proposed method is star labeling. It comprises connected-domain labeling based on the preordering of pixels and the calculation of centroid coordinates of stars in each connected domain. The experimental results show that the proposed algorithm extracts the stars stably under the interference of different stray lights. The proposed method consumes less resources, and the output delay is only 18.256 us. Moreover, the successful identification rate is 98% and the attitude accuracy of the X and Y axes is better than 5″(3σ) when the star sensor works at the speed of zero. [ABSTRACT FROM AUTHOR]

Star identification plays a key role in spacecraft attitude measurement. Currently, most star identification algorithms tend to perform well only in a scene without noise and are highly sensitive to noise. To solve this problem, this paper proposes a star identification algorithm based on the maximum spanning tree (MST) index and multi-order continuous cycle angle (CCA) intended for the lost-in-space mode. In addition, a neighboring star selection method named dynamic eight-quadrant (DEQ) is developed. First, the DEQ method is used to select high-confidence neighboring stars for the main star. Then, the star image is regarded as a graph, and the Prim algorithm is employed to construct the MST pattern for each guide star, which is then combined with the K vector index to perform the main star candidate search. Finally, the Jackard similarity voting for the multi-order CCA of the main star is used to identify the main star, and the global neighboring star identification is conducted by the multi-order CCA of neighboring stars. The simulated and real star images test results show that compared with five mainstream algorithms, when the position noise is 1 pixel, the number of false stars is five, the magnitude noise is 0.5, and the identification accuracy of the proposed algorithm is higher than 98.5%. Therefore, the proposed algorithm has excellent anti-noise ability in comparison to other algorithms. [ABSTRACT FROM AUTHOR]

Aiming at the application requirements of a field of view (FOV) gated imaging system for all-time star sensors, a key device of a microshutter array with large unit size, high duty cycle, and fast response speed based on the electromagnetic actuation is designed. The proposed microshutter array adopts the principle that the current-carrying coil is subjected to the magnetic force in the magnetic field. The coil element is deflected by the loading current and acts as a light barrier in realizing the optical switch function. The effects of the coil element parameters on the magnetic force torque, torsion beam resistance torque, and switch response time are analyzed, and the structural parameters of the coil element are determined. A sample of the proposed microshutter array based on the electromagnetic actuation with a 4-mm period and a 2.8-mm aperture is fabricated and tested. The test results demonstrate the good switching function of the proposed microshutter array and show that the switch response time of the microshutter element is approximately 2.5 ms. This proposed microshutter array is used to gate an instantaneous small FOV to suppress the sky's background radiation and make a FOV-gated imaging system realize the multi-stars detection by switching the gated FOV rapidly. This will solve the problem that only one star can be detected within the FOV by a traditional all-time star tracker and promote the all-time star sensor to realize star pattern recognition and autonomous astronomical navigation in the daytime. [ABSTRACT FROM AUTHOR]

Recent advances in the fields of driverless cars, intelligent robots and remote-sensing measurement have shown that the use of LiDAR fused with cameras can provide more comprehensive and reliable sensing of surroundings. However, since it is difficult to extract features from sparse LiDAR data to create 3D–2D correspondences, finding a method for accurate external calibration of all types of LiDAR with cameras has become a research hotspot. To solve this problem, this paper proposes a method to directly obtain the 3D–2D correspondences of LiDAR–camera systems to complete accurate calibration. In this method, a laser detector card is used as an auxiliary tool to directly obtain the correspondences between laser spots and image pixels, thus solving the problem of difficulty in extracting features from sparse LiDAR data. In addition, a two-stage framework from coarse to fine is designed in this paper, which not only can solve the perspective-n-point problem with observation errors, but also requires only four LiDAR data points and the corresponding pixel information for more accurate external calibration. Finally, extensive simulations and experimental results show that the effectiveness and accuracy of our method are better than existing methods. [ABSTRACT FROM AUTHOR]

In the South Atlantic Anomaly (SAA) area, due to the influence of transient noise caused by space radiation, a star sensor can easily stay in the lost-in-space (LIS) mode for a long time. To solve this problem, this paper proposes a fast star identification (FSI) algorithm. First, a noise suppression method based on scale assessment and neighborhood comparison is developed. Next, a fast and accurate search technique of multiple main stars based on the k-vector technique is used to realize star identification. The search technique builds a self-defined attribute database of stars, and a fast search method of a repeated star identity is proposed to realize the positioning of the main star. Lastly, the final main stars are obtained through the comparison of field of view and verification of angular distance. The experimental results showed that when the star sensor works at a speed of 0.1°/s and the level of transient noise signals is lower than 900, the successful identification rate is higher than 70%. In addition, compared with the triangle algorithm, match group algorithm, and multi-pole algorithm (MPA), the proposed FSI algorithm has the advantages of a higher successful identification rate and a faster execution speed. [ABSTRACT FROM AUTHOR]

Extracting signal photons from noisy raw data is one of the critical processes for the new generation of spaceborne photon-counting laser altimeter. Affected by vast noise photon-counting events, the extraction of weak signal events still faces challenges in complex scenarios with low signal-to-noise ratio (SNR). Aiming to improve the extraction ability of signal photon events in these scenarios, a multiscale fusion signal extraction method was proposed, characterized by combining global spatial correlation constraint with optimized local spatial correlation constraint. The local constraint is implemented based on a density-based spatial clustering of applications with noise (DBSCAN) clustering method with adaptive parameter estimation, which is used to extract possible signal photons. A subsequent global constraint based on the spatial correlation of the terrain profiles is designed to remove the pseudo-signal photons clustered in the local constraints’ step. The global constraint is implemented based on a cost function, which is used to quantify different candidate paths. Our method was verified based on the actual Ice, Cloud, and land Elevation satellite-(ICESat2) data containing vegetation, mountains, and residential areas. The experimental results show that compared with the ICESat-2 extraction method, our method can significantly improve the precision and recall rate of signal photon events from the low SNR photon-counting data. [ABSTRACT FROM AUTHOR]

This paper studies the thermal performance of an air conditioning system in a pure electric vehicle. An experiment is designed to examine the main factors affecting the performance, and the experimental results show that a heat pump with a low pressure gas-mixing system can increase the heating capacity and decrease the discharge temperature. [ABSTRACT FROM AUTHOR]

When the exhaust temperature of heat pump air conditioning system of pure electric bus is too high, the performance of the system is attenuated. In order to solve the problem, an alternative system with low pressure air supply is developed. The experimental platform is set up to reveal the main factors affecting the refrigeration and heating performance of the system. The results show that the low pressure air-supply technology can significantly reduce the exhaust temperature of the compressor [ABSTRACT FROM AUTHOR]

In order to solve the problem of serious attenuation of the performance of heat pump air conditioning system for pure electric bus at high temperature in summer and at low temperature in winter, a heat pump air conditioning system for medium-pressure air-supply pure electric bus with economizer is developed. The performance of the system working at from +50 °C to -20 °C ambient temperature and at different compressor speed is studied. The results show that the exhaust temperature of the compressor can be reduced greatly. [ABSTRACT FROM AUTHOR]

The background contains potential favorable information for visual tracking. The recent correlation filter-based tracking methods achieve great success by densely sampling at the target and its surrounding background. To further improve the tracking ability against deformation (DEF) and occlusion (OCC), we propose to utilize auxiliary objects. First, auxiliary object candidates with objectness are generated with unsupervised salient region detection. Second, the graph model between the target with all auxiliary object candidates is established when these objects are tracked individually. Third, all auxiliary objects vote for correcting the predicting result of the target tracker. Experimental results show that auxiliary objects are helpful for tracking the target, especially for improving the robustness on DEF and OCC. [ABSTRACT FROM AUTHOR]

This paper studies numerically the influence of the louver's fin thickness on heat transfer and flow performance of a parallel flow evaporator, a comprehensive evaluation and analysis of the five structures at different Reynolds numbers are systematically carried out. Comparison of the numerical results with the experimental data shows good agreement with maximal errors of 12.16% and 5.29% for the heat transfer factor and the resistance factor, respectively. The results show that the heat transfer coefficient and the pressure drop increase with the increase of the thickness of the louver fins when the Reynolds number is a constant. The analysis of the comprehensive evaluation factor shows that the A-type fin is the best, and it can effectively strengthen the heat exchange on the air side and improve the heat transfer capacity of the system. The research results can provide reference for the structural optimization of the louver fins. [ABSTRACT FROM AUTHOR]

The influence of the louver fin's structure on the heat transfer performance of a parallel flow gas cooler is studied, and a 3-D model for an elliptical louver fin is simulated for analysis of the heat transfer and flow resistance characteristics of the fin. The micro-channel structure of the fin is optimized to give the best comprehensive performance evaluation by suitable choice of fin's thickness and the space between the adjacent louvers for given range of Reynolds number. [ABSTRACT FROM AUTHOR]

With the analysis of the features of image edge based on the defocused model of optical imaging system, a blur estimation and detection method for out-of-focus images is proposed. The essential idea is to estimate the parameter of the point spread function, which reflects the blurriness of image. Based on the notion, the proposed method estimates the parameter values by different straight edges in the image, and the parameter distribution is used to measure the image blurriness. Then it can determine whether an image is blurred or not by comparing with a predetermined threshold. Experiment results show that the proposed blur metric is highly correlated to subjective visual perception, and it can be implemented to estimate and detect the blurriness for out-of-focus images with different scenes. [ABSTRACT FROM AUTHOR]

To improve the resolution in 3D range-gated imaging, an adaptive polarization-modulated method using electron multiplying charge-coupled devices (EMCCDs) is proposed in this letter. With polarization beam splitting, the returned light is separated into two orthogonal polarized components, which are modulated by cos2 function and sin2 function, respectively. Based on a dual EMCCDs structure, both a depth map and an intensity image can be reconstructed from the two modulated images instantaneously, which will enhance the performance of dynamic imaging. The results show that the range accuracy of the interested objects in the scene can be promoted from 4.4 to 0.26 m with the art of adaptive gate-opening range. [ABSTRACT FROM PUBLISHER]

Stray light, such as sunlight, moonlight, and earth-atmosphere light, can bring about light spots in backgrounds, and it affects the star detection of star sensors. To overcome this problem, this paper proposes a star detection algorithm (CMLCM) with multidirectional local contrast based on curvature. It regards the star image as a spatial surface and analyzes the difference in the curvature between the star and the background. It uses a facet model to represent the curvature and calculate the second-order derivatives in four directions. According to the characteristic of the star and the complex background, it enhances the target and suppresses the complex background by a new calculation method of a local contrast map. Finally, it divides the local contrast map into multiple 256 × 256 sub-regions for a more effective threshold segmentation. The experimental results indicated that the CMLCM algorithm could effectively detect a large number of accurate stars under stray light interference, and the detection rate was higher than other compared algorithms with a lower false alarm rate. [ABSTRACT FROM AUTHOR]

Monocular vision is one of the most commonly used noncontact six-degrees-of-freedom (6-DOF) pose estimation methods. However, the large translational DOF measurement error along the optical axis of the camera is one of its main weaknesses, which greatly limits the measurement accuracy of monocular vision measurement. In this paper, we propose a novel monocular camera and 1D laser rangefinder (LRF) fusion strategy to overcome this weakness and design a remote and ultra-high precision cooperative targets 6-DOF pose estimation sensor. Our approach consists of two modules: (1) a feature fusion module that precisely fuses the initial pose estimated from the camera and the depth information obtained by the LRF. (2) An optimization module that optimizes pose and system parameters. The performance of our proposed 6-DOF pose estimation method is validated using simulations and real-world experiments. The experimental results show that our fusion strategy can accurately integrate the information of the camera and the LRF. Further optimization carried out on this basis effectively reduces the measurement error of monocular vision 6-DOF pose measurement. The experimental results obtained from a prototype show that its translational and rotational DOF measurement accuracy can reach up to 0.02 mm and 15″, respectively, at a distance of 10 m. [ABSTRACT FROM AUTHOR]

Single-pixel noise commonly appearing in a star sensor can cause an unexpected error in centroid extraction. To overcome this problem, this paper proposes a star image denoising algorithm, named Improved Gaussian Side Window Filtering (IGSWF). Firstly, the IGSWF algorithm uses four special triangular Gaussian subtemplates for edge protection. Secondly, it exploits a reconstruction function based on the characteristic of stars and noise. The proposed IGSWF algorithm was successfully verified through simulations and evaluated in a star sensor. The experimental results indicated that the IGSWF algorithm performed better in preserving the shape of stars and eliminating the single-pixel noise and the centroid estimation error (CEE) value after using the IGSWF algorithm was eight times smaller than the original value, six times smaller than that after traditional window filtering, and three times smaller than that after the side window filtering. [ABSTRACT FROM AUTHOR]

The satellite, Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) has been equipped with a new type of spaceborne laser altimeter, which has the benefits of having small footprints and a high repetition rate, and it can produce dense footprints on the ground. Focusing on the pointing angle calibration of this new spaceborne laser altimeter, this paper proposes a fast pointing angle calibration method using only a small range of terrain surveyed by airborne lidar. Based on the matching criterion of least elevation difference, an iterative pointing angle calibration method was proposed. In the experiment, the simulated photon-counting laser altimeter data and the Ice, Cloud and Land Elevation Satellite-2 data were used to verify the algorithm. The results show that when 1 km and 2.5 km lengths of track were used, the pointing angle error after calibration could be reduced to about 0.3 arc-seconds and less than 0.1 arc-seconds, respectively. Meanwhile, compared with the traditional pyramid search method, the proposed iterative pointing angle calibration method does not require well-designed parameters, which are important in the pyramid search method to balance calculation time and calibration result, and the iterative pointing angle calibration method could significantly reduce the calibration time to only about one-fifth of that of the pyramid search method. [ABSTRACT FROM AUTHOR]

In this paper, a simple and easy high-precision calibration method is proposed for the LRF-camera combined measurement system which is widely used at present. This method can be applied not only to mainstream 2D and 3D LRF-cameras, but also to calibrate newly developed 1D LRF-camera combined systems. It only needs a calibration board to record at least three sets of data. First, the camera parameters and distortion coefficients are decoupled by the distortion center. Then, the spatial coordinates of laser spots are solved using line and plane constraints, and the estimation of LRF-camera extrinsic parameters is realized. In addition, we establish a cost function for optimizing the system. Finally, the calibration accuracy and characteristics of the method are analyzed through simulation experiments, and the validity of the method is verified through the calibration of a real system. [ABSTRACT FROM AUTHOR]

This article presents a new sensor fusion method for visual simultaneous localization and mapping (SLAM) through integration of a monocular camera and a 1D-laser range finder. Such as a fusion method provides the scale estimation and drift correction and it is not limited by volume, e.g., the stereo camera is constrained by the baseline and overcomes the limited depth range problem associated with SLAM for RGBD cameras. We first present the analytical feasibility for estimating the absolute scale through the fusion of 1D distance information and image information. Next, the analytical derivation of the laser-vision fusion is described in detail based on the local dense reconstruction of the image sequences. We also correct the scale drift of the monocular SLAM using the laser distance information which is independent of the drift error. Finally, application of this approach to both indoor and outdoor scenes is verified by the Technical University of Munich dataset of RGBD and self-collected data. We compare the effects of the scale estimation and drift correction of the proposed method with the SLAM for a monocular camera and a RGBD camera. [ABSTRACT FROM AUTHOR]

As a passive heat transfer superconductor for proton exchange membrane fuel cell (PEMFC) cooling, the heat transfer performance and temperature uniformity of flat-plate closed loop pulsating heat pipe (CLPHP) are the key factors to determine its application efficiency. Based on the geometric structure and working medium thermophysical properties of flat-plate CLPHP, this study establishes segmented and integral thermal resistance theoretical models for the heat transfer properties of each section of the flat-plate CLPHP. The calculation accuracy of the segmented and integral thermal resistance models is compared through experimental verification. The results show that the segmented thermal resistance model's temperature variation and temperature uniformity are more accurate than that of the integral thermal resistance model when the flat-plate CLPHP is started, operated stably, or at higher heating power. However, the model calculation error is relatively large when the heating power is relatively high at 400 W, but the calculation accuracy of the segmented thermal resistance model in temperature and temperature uniformity is 2.32 and 5.99 times that of the integral thermal resistance model. The segmented thermal resistance model provides a theoretical basis for improving the calculation accuracy of flat-plate CLPHP coupled PEMFC cooling. • A segmented thermal resistance model of flat-plate CLPHP is proposed. • The segmental and integral thermal resistance simulation models of flat-plate CLPHP are established. • The segmented thermal resistance model has higher temperature calculation accuracy. • Segmented thermal resistance model optimizes simulation calculations for flat-plate CLPHP integrated PEMFC cooling. [ABSTRACT FROM AUTHOR]

The construction of a guide star catalog is crucial for a star sensor to achieve accurate star map recognition and attitude determination. At present, the methods of a guide star catalog for a large field of view (FOV) star sensor have been relatively mature. However, for a small-FOV star sensor, there are still certain problems, such as a large storage capacity of a guide star catalog, uneven distribution of stars, and easy occurrence of voids. To address these problems, we propose a construction method of a small-FOV star sensor guide star catalog based on the combination of the improved spherical spiral method (ISSM) and extreme learning machine (ELM) named the ISSM-ELM. First, a spiral reference point is used as an optical axis pointing of the star sensor, and the guide stars are preliminarily screened based on the star-diagonal distance between the star and the reference point, and the star-density and magnitude characteristics of the guide star. Then the ELM is used to supplement the guide star empty sky area to construct an integrity guide star catalog. The experimental results demonstrate that the proposed method can reduce the storage capacity of the guide star catalog, and improve its uniformity, integrity, and average brightness.

The wide field of view (FOV) of traditional star sensor optical systems restricts the ability to suppress atmospheric background. An optical imaging system for an all-time star sensor based on FOV gated technology is proposed. In this system, a wide FOV telescope is used to observe a large sky area containing multiple stars. A microlens and microshutter array is employed to subdivide the wide FOV and gate a narrow FOV to suppress atmospheric background radiation. Assisted by a common imaging lens, each set of microlens and microshutter elements corresponds to a FOV gated imaging channel. With the rapid switching of gated FOV, multiple stellar images are obtained on a common detection during daytime. As an example, a FOV gated optical imaging system with 0.4° gated FOV and 61 imaging channels is designed. In addition, a simplified prototype is developed, and a preliminary experiment of FOV gated imaging is performed near the ground. The results verify the capability of multiple stellar detections during daytime. The proposed optical imaging system has a strong capability of suppressing atmospheric background radiation and provides sufficient FOV gated imaging channels to enhance the probability of detecting multiple stars. It provides an effective technical way to develop all-time star sensors based on star pattern recognition and enables a completely autonomous attitude determination possible for platforms inside the atmosphere during daytime.