APPLICATION OF NOISE REDUCTION METHOD BASED ON CURVELET THRESHOLDING NEURAL NETWORK FOR POLAR ICE RADAR DATA PROCESSING

Due to the demand of data processing for polar ice radar in our laboratory, a Curvelet Thresholding Neural Network (TNN) noise reduction method is proposed, and a new threshold function with infinite-order continuous derivative is constructed. The method is based on TNN model. In the learning process of TNN, the gradient descent method is adopted to solve the adaptive optimal thresholds of different scales and directions in Curvelet domain, and to achieve an optimal mean square error performance. In this paper, the specific implementation steps are presented, and the superiority of this method is verified by simulation. Finally, the proposed method is used to process the ice radar data obtained during the 28th Chinese National Antarctic Research Expedition in the region of Zhongshan Station, Antarctica. Experimental results show that the proposed method can reduce the noise effectively, while preserving the edge of the ice layers.

Enhancing the vertical resolution of lunar penetrating radar data using predictive deconvolution

The Yutu-2 rover onboard the Chang’E-4 mission performed the first lunar penetrating radar detection on the farside of the Moon.The high-frequency channel presented us with many unprecedented details of the subsurface structures within a depth of approximately 50 m.However,it was still difficult to identify finer layers from the cluttered reflections and scattering waves.We applied deconvolution to improve the vertical resolution of the radar profile by extending the limited bandwidth associated with the emissive radar pulse.To overcome the challenges arising from the mixed-phase wavelets and the problematic amplification of noise,we performed predictive deconvolution to remove the minimum-phase components from the Chang’E-4 dataset,followed by a comprehensive phase rotation to rectify phase anomalies in the radar image.Subsequently,we implemented irreversible migration filtering to mitigate the noise and diminutive clutter echoes amplified by deconvolution.The processed data showed evident enhancement of the vertical resolution with a widened bandwidth in the frequency domain and better signal clarity in the time domain,providing us with more undisputed details of subsurface structures near the Chang’E-4 landing site.

Data processing and initial results of Chang'e-3 lunar penetrating radar

To improve our understanding of the formation and evolution of the Moon, one of the payloads onboard the Chang＇e-3 （CE-3） rover is Lunar Penetrating Radar （LPR）. This investigation is the first attempt to explore the lunar subsurface structure by using ground penetrating radar with high resolution. We have probed the subsur- face to a depth of several hundred meters using LPR. In-orbit testing, data processing and the preliminary results are presented. These observations have revealed the con- figuration of regolith where the thickness of regolith varies from about 4 m to 6 m. In addition, one layer of lunar rock, which is about 330 m deep and might have been accumulated during the depositional hiatus of mare basalts, was detected.

Research on Data Combination for Phased-Array Ground Penetrating Radar

To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.

METHODS OF RADAR DATA COMPRESSION AND TARGET IDENTIFICATION BASED ON BIORTHOGONAL FDWT

In this paper, by using the biorthogonal quadrature filters, the biorthogonal mul-tiresolution analysis of finite dimension space equipped with inner product and the fast discrete wavelet transform (FDWT) are constructed. The dual transform method is proposed and the radar data storage is reduced by it. The method of choosing the wavelet coefficients, and the methods of correlation and nearest neighbor classification in wavelet domain based on the compressed data, are presented. The experimental results of the classification, using the high resolution range returns from six kinds of aircrafts, show that the methods of transform, compression and recognition are efficient.

Research and Implementation of a Graphic System for Doppler Radar

Doppler radar have become one of the most important instruments for weather now casting,and for meso-scale weather research because of its higher spatial and temporal resolutions. A dealing system for Doppler radar graphic was researched and implemented so as to providing a convenient tool for users. We research and realized CINRAD/XD Doppler radar's graphic system. It contains three important parts:reading,standardization and pretreatment. It can be used very easily and conveniently. Besides,the system can be expanded and transplanted simply.

Computer Control Techniques of Phased Array Radars

The computer control techniques applicable to electronically scanned multifunction radars are presented. The software and hardware architecture for the real time control and the data processing within a phased array radar are described. The software system comprising a number of tasks is written in C language and implemented. The results show that the algorithm for the multitask adaptive scheduling and the multitarget data processing is suitable for multifunction phased array radars.

A Radar Visualization System Upgrade

This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be adapted to the specific needs of each application domain in an efficient way. Replacing the visualization and processing units on existing radar platforms by this new system, a practical and inexpensive improvement is achieved.

矿井探地雷达背景杂波抑制方法综述

随着中国煤炭安全高效智能开采需求的不断提升,矿井探地雷达(ground-penetrating radar, GPR)作为一种高精度物探方法,在煤矿井下探测中有广阔的应用前景。由于探地雷达目标回波信号受系统内部噪声、外部电磁干扰、巷道回波、地下介质不均匀等干扰影响,虚警率较高。尤其对于小尺寸目标,其回波信号为弱信号,容易淹没在强烈的背景杂波中,成为目前制约探地雷达探测性能的主要因素之一,进一步实现井下煤层、构造探测、提高探测精度的关键在于对背景杂波的抑制。从对消法、滤波法、分解法和网络法出发,综述这些杂波抑制方法的基本原理、优缺点及其在探地雷达干扰抑制领域的研究进展,并探讨各种方法的适用范围和发展潜力。杂波抑制技术的不断创新将进一步提高探地雷达的信噪比与灵敏度,使其在煤矿井下探测中发挥更大的应用价值。

探地雷达在华阳一矿隐伏断层构造探测中的应用

断层构造破坏煤系地层、降低煤炭资源储量,采煤工作面通过断层,增加采煤成本,带来突水、瓦斯积聚风险,有必要在采煤工作面开展隐伏断层构造探测。目前,采煤工作面的主要物探方法有地震波法和电磁法两类,作为精细地质勘探方法,探地雷达技术可以在隐伏断层构造探测中发挥重要作用。本文针对华阳一矿地质特点分析了断层类型及其成因,采用有限时域差分法模拟了不同走向断层构造的探地雷达探测数据,分析了不同构造的数据特征,提出了基于电磁波反射路径的断层走向推断方法。通过100 MHz探地雷达对矿区内隐伏断层构造进行了探测,探测结果表明:通过结合目标反射波振幅、层位变化等信息,可以估计断层构造在回采区内的走向和范围,结合已揭露的倾角、落差等信息,为预先调整回采工作面提供依据。

多功能雷达总体数据分析系统设计与实现

多功能一体化是雷达发展的必然趋势,随着功能的增加,多模式间切换频繁调度复杂,系统调试工作量呈指数增长,数据分析与管理的难度增大。为提高多功能雷达数据分析效率,辅助问题定位分析与系统状态检查,加快雷达研制进程,分析了总体数据分析在雷达研制和使用阶段的重要作用,研究了雷达总体数据分析软件的需求与系统设计,并通过Matlab进行实现。该软件可以分析雷达多环节数据,并以表格和图像的形式呈现分析结果。经过实验数据验证,该软件能够有效地提高分析效率,进行雷达状态判断和性能评估,快速发现与定位问题。

地面坍塌隐患检测中三维地质雷达数据处理及隐患识别研究

三维地质雷达作为一种高效、无损的检测技术,已广泛应用于城市道路地下病害或坍塌隐患检测中。与传统的二维地质雷达相比,三维地质雷达在隐患识别、数据融合、工作效率等方面具有突出优势,逐渐成为城市道路地面坍塌隐患检测的主要方法。笔者总结了三维地质雷达的技术优势,通过对三维地质雷达数据处理的总结研究,提炼出了一套系统的数据处理流程,通过对不同隐患的三维地质雷达图谱特征进行分析研究,总结出了不同类型隐患的识别特征及判定依据,为城市道路地面坍塌隐患三维地质雷达检测数据的处理及隐患的识别提供参考。

雷达对抗中基于FPGA输入分块重映射的数据处理方法

雷达对抗中,干扰机侦收雷达的信号,经AD采样后输入FPGA进行处理并产生干扰信号。FPGA平台利用Xilinx等官方提供的FFTIP核对高速ADC输出的数据进行FFT处理时,需要进行“并行-串行”的数据预处理,降低了处理速度,同时也没有对FPGA内部资源进行最大化利用。基于以上问题,提出一种基于FPGA输入分块重映射的数据处理方法。该方法通过数据输入重映射模块将输入雷达数据优化为并行分块的数据流格式,再通过FFT蝶形网络输出离散傅里叶变换数据,最后进行并行结果输出。试验证明,本方法能有效节省FPGA的运算时间,提高雷达数据处理速度,优化利用了FPGA内部资源,具有实时性好、灵活性高的特点。

探地雷达在华阳一矿隐伏陷落柱构造探测中的应用

陷落柱构造破坏煤系地层、降低煤炭资源储量,采煤工作面通过陷落柱,增加采煤成本,带来突水、瓦斯积聚风险,有必要在采煤工作面开展隐伏陷落柱构造探测。目前,采煤工作面的主要物探方法有地震波法和电磁法两类,作为精细地质勘探方法,探地雷达技术在隐伏陷落柱构造探测中发挥了重要作用。本文针对华阳一矿地质特点分析了陷落柱类型及其成因,采用有限时域差分法模拟了无充填型和充水型两类陷落柱构造的探地雷达数据,分析了不同构造的数据特征。通过100 MHz探地雷达对矿区内隐伏陷落柱构造进行了探测,探测结果表明:通过探地雷达剖面的目标频率变化及衰减幅度等特征,能够判别出陷落柱类型,为风险源排查和工程作业提供参考。

基于Qt的雷达数据处理软件开发与应用

雷达数据处理作为雷达系统末端的一个重要环节,主要完成对点航迹的关联、航迹启动、航迹滤波以及航迹外推等工作,实现对目标信息的提取。通常,雷达的数据处理都在后台运行且是对外封闭的,用户无法根据任务特点进行相关参数调整。本文基于Qt框架开发了可独立运行的数据处理软件,通过网络实现点迹接收和航迹发送,开放参数设置,对虚假航迹进行判定。从使用情况来看,软件实现了数据处理参数可灵活配置,降低了虚假航迹个数,有助于提高雷达的作战应用能力。

嵌入式激光雷达下室内移动机器人动态定位方法

由于空间的限制,室内移动机器人在操作过程中对位置确认的要求较高,存在移动轨迹定位偏离的问题。为此提出嵌入式激光雷达下室内移动机器人动态定位方法。利用坐标转换以及欧式距离分割法对采集的激光雷达数据实施预处理,去除噪声对后续定位的影响。通过回波强度确定反光板的位置拟合变化,利用三边定位算法对移动机器人实施精准定位。经实验验证,该方法的定位误差较小,不仅可以实现室内移动机器人整体高精度的动态定位,而且可以很好地监测室内移动机器人的轨迹。

一种毫米波雷达里程计自主定位技术

本文通过研究毫米波雷达的数据基本特性,提出了一种毫米波雷达里程计自主定位技术。该方法通过特征匹配的方式,对毫米波雷达图像提取AKAZE特征点,并基于雷达图像自身所具备的几何先验信息,提出了3种匹配约束条件,从而大大降低了特征点误匹配率,保证了传感器位姿和里程计解算的可靠性。在牛津雷达机器人数据集上的试验结果表明,本文方法在不引入局部建图和回环检测等优化策略的情况下,水平位移相对定位误差和航向角误差可分别降低至6.8%和0.89(°)/m,单帧的定位时间仅为0.081 s,为恶劣环境下的室内外导航定位提供了新的思路。

“雷达数据处理与终端”课程教学改革探讨

“雷达数据处理与终端”课程在雷达专业课程体系中具有重要地位和作用。紧密结合学员学情特点和课程教学目标,以航迹生命周期为驱动,重构知识逻辑,优化课程教学内容,从教学组织、教学方法、资源建设、课程思政等方面进行教学改革,打通学员思维回路,有效突破教学重难点,达成教学目标。同行评价和学员评教反馈信息显示,课程改革取得了较好的成效,为雷达专业课程深化推进实施“立德树人、为战育人”教学改革提供了有益参考和借鉴。

基于深度学习的隧道岩溶GPR数据杂波抑制研究

为提高岩溶地区GPR数据的解析精度,减少杂波对GPR剖面的影响,从而更准确地圈定目标异常,提出了基于VAE-RFDB-UNet深度学习的数据处理方法。该方法先通过VAE对GPR数据进行有效信号特征提取,实现杂波的初步抑制,后利用加载RFDB模块的UNet网络对VAE处理后的数据进行深度特征学习,形成联级网络,进一步抑制杂波干扰,增强目标信号响应,提高数据的信噪比。研究结果表明:1)使用模拟数据和实测数据证明了算法的有效性和可行性;2)数值模拟的处理结果显示,处理后的岩溶反射波双曲线形态完整、连续,杂波得到了明显抑制;3)实测数据的处理结果显示,该算法有效突出了目标异常信号,能依据处理后的剖面准确推断掌子面前方的岩溶发育情况。结论是提出的VAE-RFDB-UNet深度学习算法可为岩溶地区GPR数据处理提供一种新思路。

基于人工智能的雷达虚假航迹抑制问题探讨

随着大数据时代的到来,人工智能技术获得突飞猛进的发展。仅考虑在不改变当前数据输入的情况下,针对雷达数据处理中的虚假航迹抑制问题,结合人工智能技术,从“点、面、层”3个维度探讨了虚假航迹智能化抑制方法,以达到有效减少虚假航迹的目标。最后对雷达智能化的发展进行了展望,并对如何发展雷达智能化提出了一些建议。