一种无人机自主避障与目标追踪方法

针对无人机自主避障与目标追踪问题,以深度Q网络(DQN)算法为基础,提出一种多经验池深度Q网络(MP DQN)算法,使无人机避障与追踪的成功率和算法的收敛性得到优化。更进一步,赋予无人机环境感知能力,并在奖励函数中设计了方向奖惩函数,提升了无人机对环境的泛化能力以及算法的整体性能。仿真结果表明,相较于DQN和双重DQN(DDQN)算法,MP DQN算法具有更快的收敛速度、更短的追踪路径和更强的环境适应性。     

Investigation of flow unsteadiness in a highly-loaded compressor cascade using a dynamic mode decomposition method

Unsteady flow in the hub endwall region has long been a hot topic in the turbomachinery community. However important it is to the performance of the whole engine, the coherent unsteady flow phenomena are still not well understood. In this paper, the complex flow field in the hub endwall of a cantilevered compressor cascade has been investigated through numerical approach. The predicted results were validated by experimental data. To highlight the dominant flow structures among irregular and chao...     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

Observations of a quasi-90-day oscillation in the MLT winds and tides over an equatorial station using meteor radar winds

An evident signature of a least studied quasi-90-day oscillation is found in the winds and tides in the MLT from an equatorial station, São João do Cariri (7.4°S, 36.5°W). The oscillation is found to appear mainly in certain intervals with small but appreciable seasonal (fourth harmonic of annual oscillation) contribution. The maximum amplitude of the oscillation is found to be around 10 m/s in the zonal wind. The enhancement peak of the oscillation exhibits downward movement indicating a plausible role of upward moving waves/tides in carrying its imprint from below to the MLT. Similar oscillation feature in the tropospheric zonal wind and ozone may imply its lower atmospheric origin as a component of the intraseasonal oscillation (ISO) that moves upward by modulating the tides. Subsequently, the propagating tides (mainly semidiurnal) are enhanced by the ozone in the stratosphere through absorption of solar UV radiation and finally manifest the oscillation in the MLT. Consistency of the present findings with the past investigations are observed in some aspects of the oscillation, whereas existing mismatches in others are believed to be due to geophysical variability depending on space and time among various locations on the globe.     

A novel framework for liquid propellant engine’s cooling system design by sensitivity analysis based on RSM and multi-objective optimization using PSO

One of the challenges of combustion chamber and nozzle design in a Liquid Propellant Engine (LPE) is to predict the behavior and performance of the cooling system. Therefore, while designing, the optimization of the cooling system is always of great importance. This paper presents the multi-objective optimization of the LPE’s cooling system. To this end, a novel framework has been developed, resulting from the application of the Response Surface Method (RSM) and the correlation coefficients matrix, sensitivity analysis and the The Particle Swarm Optimization (PSO). based on this method, the input variables, constraints, objective functions, and their surfaces were identified. In terms of multi-optimization algorithms, RSM and PSO are utilized to get global optimum. In conclusion, the methodology capability is to optimize the LPE’s cooling system, 6 percentage increase in total heat transfer and 7 bar decrease cooling system pressure loss, which resulted in a 1.2-seconds increase in the specific impulse of the engine.     

电子对抗技术发展综述

随着雷达低截获技术、通信系统抗干扰技术的发展和战场上智能化电子信息装备部署的应用,战场电磁频谱环境的复杂程度日益增加。如何提高电子战感知环境-适应环境-做出决策-采取行动(OODA)环路速度,实现电磁敏捷,是电子战应对未来复杂战场环境挑战需要解决的关键科学技术问题。通过分析现代雷达技术发展对传统电子战系统的挑战,阐述认知电子战发展的必要性,并从认知概念演变、人工智能技术发展、认知电子战关键技术等方面,对传统电子战向认知电子战发展过程中人工智能技术的应用情况进行分析与总结。     

协同空战与多智能体强化学习下的关键问题

自从协同作战的概念提出后,各军事强国在协同空战领域均取得了重大进展,协同成为提升作战能力的倍增器。近数十年来,作为解决序列问题的现代智能方法,强化学习在各领域高速发展。然而,面对高维变量问题时,传统的单智能体强化学习往往表现不佳,多智能体强化学习算法为解决复杂多维问题提出新的可能。通过对多智能体强化学习算法原理、训练范式与协同空战的适应性进行分析,提出了协同空战与多智能体强化学习的未来发展方向,为更好地把多智能体强化学习应用于协同空战提供思路。     

Precise orbit determination and precision comparison for FY3C and FY3D with receiver antenna GPS and BDS PCV using spaceborne BDS and GPS observation data

The FY3C and FY3D satellites were equipped with global navigation satellite occultation detector (GNOS) receivers that received both GPS and BDS-2 signals. For further improving precise orbit determination (POD) precisions, we estimated receiver GPS and BDS signal phase center variations (PCV) models with 2° and 5° resolutions and set the different weights for GPS and BDS-2 observations in the combined POD. The BDS-based POD precision using BDS-2 satellite antenna phase center offset (PCO) values from the China Satellite Navigation Office (CSNO) are not as accurate as those obtained from the International GNSS Service (IGS) Multi-GNSS experiments project (MGEX). The estimated receiver GPS and BDS PCV models with 2° and 5° resolutions were estimated from the GPS phase residuals of GPS-based POD and BDS phase residuals of combined POD, respectively. In most cases, the POD precisions using the estimated PCVs with 2° resolution are superior to those with 5° resolution. The precisions of the BDS-based POD and combined POD were both improved by introducing the receiver BDS PCV models. The weighting for GPS and BDS-2 observations can further improve the precision of the combined POD. The tested results of selected weights are better than those with equal weight in the combined POD. The experiment results show that orbital precisions of FY3C are worse than those of FY3D.     

Very low thrust station-keeping for low Earth orbiting satellites

Traditional station-keeping for Earth observation satellites with chemical thrusters generally involves maneuvers every couple months that are able to change significantly the semi-major axis and the inclination. These strategies do not scale down to very low thrust level (a few hundreds of μN) electrical thrusters. This paper presents both in-plane and out-of-plane strategies that spread corrections over very long arcs and discretize them to tiny maneuvers every couple orbits, taking into account mission-constraints on maneuvers locations. These strategies scale up to medium thrust strategies, filling the gap between propulsion technologies. The out-of-plane strategy although features a new no-deadband property and controls the full orbital momentum. All strategies allow control very close to the reference (a few hundreds meters in osculating parameters) and very low cost.