雷达地图测绘信息对飞机位置的修正

本文讨论了利用工作在地图测绘方式下的机载多功能雷达所提供的对已知地标的测量信息,对惯导系统所给出的飞机瞬时位置进行修正的数学模型及实施方法。

雷达地图的制作

介绍了雷达地图的一种制作方法。

雷达信号与遥感地图融合的深度学习低慢小目标检测算法

雷达复杂环境低慢小目标检测是一项具有挑战性的任务,而利用深度学习以及数据特征融合等方法是解决这一难题的有效手段。本文在雷达地图融合检测网络(Radar Map fusion Detection Network,RMDN)的基础上进行了优化,主要优化方向为将雷达与地图信息在检测过程中进行重要性程度区分,具体优化内容为减少地图特征提取模块的网络深度,加入通道注意力机制,让神经网络自主学习雷达信息与地图信息特征的权重,使神经网能够更好地利用地图信息对雷达目标进行辅助检测。在此优化基础上,本文重新设计出了雷达地图融合检测网络RMDN-V2。算法的主要思想为利用卫星遥感地图来提供背景环境信息,作为雷达信号检测的辅助,通过将目标背景中的特征信息融入检测决策中,提高目标检测的准确性和鲁棒性,减少对强杂波和移动物体的干扰敏感性,改善目标检测算法在复杂环境下的表现。最后的无人机雷达实测数据实验结果表明,本文所做的针对性优化是有效的,RMDN-V2的检测性能优于原始的RMDN,同时本文算法检测性能远超传统的雷达检测算法,同时也优于目前主流的一些深度学习雷达目标检测算法。本文为解决当下低慢小目标检测的难题提出了新的算法。

雷达视频地图的坐标变换

主要阐述了在雷达系统中所使用的雷达视频地图与地理点间的坐标变换问题。使用球极平面投影法，将地球上的点与线变换成平面上的点与线。

全景制作流程及地图雷达的应用研究

本文使用PTGui Pro软件进行全景拼接,再应用pano2vr软件实现场景的漫游、导航以及场景转换,并完成了全景的网络发布。主要研究了地图雷达的制作,实现了雷达与导航地图间的对应关系,完成地图雷达的方位跟踪功能。

矢量量化编码用于电子海图及雷达视频地图的数据压缩

无论电子海图还是全部存贮法实现的雷达视频地图,均需要大量的存贮量.这不仅使电路复杂,而且使计算机有限内存存贮的海图数量大大减少.本文提出了一种基于矢量量化编码的子标准图技术来实现海图数据的压缩.这种方法可以将存贮量压缩八倍,有效地解决了大范围存贮与存贮量之间的矛盾.由于这种方法直观和算法简便,使得数据的压缩和恢复非常容易实现.

TMS34010图形系统处理器在高分辨率光栅扫描雷达显示系统中的应用

介绍了高分辨率光栅扫描雷达显示系统的硬件结构和实现雷达工作画面与雷达地图叠加显示的方案 ,重点介绍了 TMS34 0

基于激光雷达的道路可通行区域检测

随着城市化进程的发展,城市人口密度日益增高,随之而来的城市交通拥堵问题也日渐显著,而无人驾驶车辆作为改善这一问题的一个可能手段,也得到了越来越多的关注。无人驾驶车辆的安全性无疑是其研发过程中十分重要的一环。该文提出了一种使用3个激光雷达进行的道路可通行区域检测方法,该方法包括道路边界检测与障碍物检测两部分。道路边界检测将道路剖面的弧度考虑在内,使用了二次函数进行拟合,提高了模型的准确性,并将最终结果表示于1个以圆弧为基础的栅格地图内。该表示方法能更好地贴合车辆实际运动模型。

Underwater topography detection of Taiwan Shoal with SAR images

Under suitable conditions of tidal current and wind, underwater topography can be detected by synthetic aperture radar (SAR) indirectly. Underwater topography SAR imaging includes three physical processes: radar ocean surface backscattering, the modulation of sea surface short wave spectrum by the variations in sea surface currents, and the modulation of sea surface currents by the underwater topography. The first process is described usually by Bragg scattering theory because the incident angle of SAR is always between 20°-70°. The second process is described by the action balance equation. The third process is described by an ocean hydrodynamic model. Based on the SAR imaging mechanism for underwater topography, an underwater topography SAR detection model and a simplified method for its calculation are introduced. In the detection model, a two-dimensional hydrodynamic model – the shallow water model is used to describe the motion of tidal current. Due to the difficulty of determining the expression of SAR backscattering cross section in which some terms can not be determined, the backscattering cross section of SAR image used in the underwater topography SAR detection is pro-processed by the simulated SAR image of the coarse-grid water depth to simplify the calculation. Taiwan Shoal, located at the southwest outlet of Taiwan Strait, is selected as an evaluation area for this technique due to the occurrence of hundreds of sand waves. The underwater topography of Taiwan Shoal was detected by two scenes of ERS-2 SAR images which were acquired on 9 January 2000 and 6 June 2004. The detection results are compared with in situ measured water depths for three profiles. The average absolute and relative errors of the best detection result are 2.23 m and 7.5 %, respectively. These show that the detection model and the simplified method introduced in the paper is feasible.

Identifying soil structure along headwater hillslopes using ground penetrating radar based technique

Soil structure plays an important role in understanding soil attributes as well as hydrological processes. Effective method to obtain high quality soil map is therefore important for both soil science research and soil work ability improvement. However,traditional method such as digging soil pits is destructive and time-consuming. In this study, the structure of headwater hillslopes from Hemuqiao catchment(Taihu Basin, China) have been analyzed both by indirect(ground penetrating radar, GPR) and direct(excavation or soil auger) methods. Four transects at different locations of hillslopes in the catchment were selected for GPR survey. Three of them(#1, #2, and #3) were excavated to obtain fullscale soil information for interpreting radar images.We found that the most distinct boundary that can be detected by GPR is the boundary between soil and underlain bedrock. In some cases(e.g., 8-17 m in transect #2), in which the in situ soil was scarcely affected by colluvial process, different soil layers can be identified. This identification process utilized the sensitive of GPR to capture abrupt changes of soil characteristics in layer boundaries, e.g., surface organic layer(layer #1) and bamboo roots layer(layer#2, contain stone fragments), illuvial deposits layer(layer #3) and regolith layer(layer #4). However, in areas where stone fragments were irregularly distributed in the soil profile(highly affected bycolluvial and/or fluvial process), it was possible to distinguish which part contains more stone fragments in soil profile on the basis of reflection density(transect #3). Transect #4(unexcavated) was used to justify the GPR method for soil survey based on experiences from former transects. After that, O horizon thickness was compared by a hand auger.This work has demonstrated that GPR images can be of a potential data source for hydrological predictions.

Wavelength Estimation Method Based on Radon Transform and Image Texture

In order to overcome the shortcoming of poor accuracy and non-serious intuitivism of traditional wavelength calculation method in serious noise, a revised Radon transform algorithm is proposed by using a straight-line instead of using the wave＇s texture approximately applied to wavelength estimation. Firstly, Radon transform of the radar image is analyzed. Then, to obtain its fitting straight line combined with wave texture, the distance is calculated between straight lines to get the wavelength. Finally, the algorithm is programmed with Matlab on PC. The experimental results show that the proposed algorithm can improve the estimation accuracy of the wavelength with good visibility.

Mapping Deciduous Broad-leaved Forested Swamps Using ALOS/Palsar Data

Accurate, updated information on the distribution of wetlands is essential for estimating net fluxes of greenhouse gases and for effectively protecting and managing wetlands. Because of their complex community structure and rich surface vegetation, deciduous broad-leaved forested swamps are considered to be one of the most difficult types of wetland to classify. In this research, with the support of remote sensing and geographic information system, multi-temporal radar images L-Palsar were used initially to extract the forest hydrological layer and phenology phase change layer as two variables through image analysis. Second, based on the environmental characteristics of forested swamps, three decision tree classifiers derived from the two variables were constructed to explore effective methods to identify deciduous broad-leaved forested swamps. Third, this study focused on analyzing the classification process between flat-forests, which are the most severely disturbed elements, and forested swamps. Finally, the application of the decision tree model will be discussed. The results showed that: 1) L-HH band(a L band with wavelength of 0–235 m in HH polarization mode; HH means Synthetic Aperture Radars transmit pulses in horizontal polarization and receive in horizontal polarization) in the leaf-off season is shown to be capable of detecting hydrologic conditions beneath the forest; 2) the accuracy of the classification(forested swamp and forest plat) was 81.5% based on hydrologic features, and 83.5% was achieved by combining hydrologic features and phenology response features, which indicated that hydrological characteristics under the forest played a key role. The HHOJ(refers to the band created by the subtraction with HH band in October and HH band in July) achieved by multi-temporal radar images did improve the classification accuracy, but not significantly, and more leaf-off radar images may be more efficient than multi-seasonal radar images for inland forested swamp mapping; 3) the lower separability between forested swamps dominated by vegetated surfaces and forest plat covered with litter was the main cause of the uncertainty in classification, which led to misleading interpretations of the pixel-based classification. Finally, through the analysis with kappa coefficients, it was shown that the value of the intersection point was an ideal choice for the variable.

Repair wind field in oil contaminated areas with SAR images

In this paper,we compared the normalized radar cross section in the cases of oil spill,biogenic slicks,and clean sea areas with image samples made from 11-pixel NRCS average,and determined their thresholds of the NRCS of the synthetic aperture radar. The results show that the thresholds of oil and biogenic slicks exhibit good consistency with the corresponding synthetic aperture radar images. In addition,we used the normalized radar cross section of clean water from adjacent patches of oil or biogenic slicks areas to replace that of oil or biogenic slicks areas,and retrieve wind field by CMOD5.n and compare wind velocity mending of oil and biogenic slicks areas with Weather Research and Forecasting modeled data,from which the root mean squares of wind speed(wind direction) inversion are 0.89 m/s(20.26°) and 0.88 m/s(7.07°),respectively. Therefore,after the occurrence of oil spill or biogenic slicks,the real wind field could be repaired using the method we introduced in this paper. We believe that this method could improve the accuracy in assessment of a real wind field on medium and small scales at sea,and enhance effectively the monitoring works on similar oil or biogenic slicks incidents at sea surface.

意大利ALENIA二次雷达系统地图的输入和更改方法

二次雷达系统的主要作用是为管制员提供准确、及时、连续的飞行信息,为飞行安全提供可靠的保障。管制员主要通过使用终端显示器来掌握飞机动态,实现对空指挥。我们知道,实际工作中显示器地图因导航设备或机场有关数据的改变等原因,必须做相应的改变或调整。

Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China

Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.