Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

移动机器人铣削制孔系统基准检测

结合航空大部件的数字化对接装配需求,设计了一套用于对接面铣削制孔的移动机器人加工系统,并提出具体的加工工艺流程。研究了基于激光轮廓扫描仪的大量散乱点云数据的预处理算法,提出基于栅格法和迭代拟合法的对接面特征提取算法。针对移动机器人加工系统在大场景下的高精度定位问题,提出基于扫描线法和最小二乘法原理的对接基准孔坐标找正算法。通过产品的加工实验验证,对接面铣削和制孔精度满足系统要求的各项技术指标,证明了本文提出的移动机器人铣削制孔系统的装配对接面加工方法能够精确地完成大部件数字化装配任务,对提高装配质量和效率具有重要意义。     

基于YOLO智能网络的红外弱小多目标检测技术

复杂背景下的红外弱小多目标检测是红外目标检测的难点,现有算法的稳健性难以满足实际弹载应用需求。针对弹载环境下的红外场景图像开展了基于典型深度学习网络模型的目标检测应用研究,提出一种基于YOLO(you only look once)网络的智能目标检测方法,通过高维特征学习表征和推理实现红外弱小多目标检测。采用传统的模板匹配算法和YOLO深度学习算法进行识别性能对比分析,验证了YOLO网络在红外弱小多目标检测方面的良好性能。实验结果表明:YOLO算法的检测概率可达92.2%,平均检测精度为0.844,与传统的模板匹配方法相比,YOLO具有明显的优势。     

某机载探测系统自主回收技术的实现

针对某机载探测系统探头回收自动化程度低的问题，提出了在无需操作员干预情况下实现探头自主回收的技术方法。采用了先进的控制算法，将缆位角与探头、缆长进行结合并引入了绞车控制系统，使绞车对探头的回收速度及缆长可进行实时调整，并给出了3种不同缆位角摆动条件下缆长与探头回收速度的控制曲线关系。研发了自主回收装置，设计了能够实现自主回收功能的探头回收机构。实验验证表明：在无需人为干预的条件下，在缆位控制系统及自主回收机构的配合下，系统实现了对探头快速、安全的回收。     

夜气辉对天基光学碎片探测的影响分析

设计并完成了夜气辉背景下的天基碎片观测试验，获取了综合谱段的观测数据。基于观测数据进行夜气辉的辐射特性及其对天基碎片探测的影响分析。结果表明，夜气辉辐射随纬度和高度呈现一定的分布特点，这些特点均符合夜气辉的理论分布规律。在约90 km处辐射最强，亮度可达到单位积分时间每平方角秒近15星等，这对恒星及碎片提取概率影响较大，其中，13等星的提取概率仅为40.5%。     

空间目标监视雷达信号频率的优选准则

随着在轨微小卫星及空间碎片数量不断增加，为保证在轨卫星的运行安全，需要对微小目标进行有效跟踪探测及稳定编目。雷达作为近地空间目标监视的主用设备，在对厘米级小目标进行探测跟踪时，其工作频率是决定其能否可靠探测关键因素，高频有利于探测小目标，并可获得相对稳定的RCS，但高频信号的波束小、搜索能力较低，实现难度大，也使得成本过高。为适于实际工程应用，需从效费比出发，对频率进行优选。本文从目标RCS的角度提出一种空间目标监视雷达信号频率的优选准则，给出该准则下周长波长比ka的取值范围。为了更加清楚地说明该优选准则的应用，给出了直径5 cm和10 cm的目标在该准则下信号频率的取值范围，并与国外工作做了比较，证明该准则可行。     

硅半球深腔结构无损检测技术

半球深腔的加工质量是决定硅基MEMS半球陀螺精度的关键因素之一，及时检测半球深腔的形貌参数并将其反馈至加工过程，是确保高性能MEMS半球陀螺研制成功的重要措施。由于硅半球深腔的深度较大，台阶仪和光学显微成像系统无法对半球深腔的形貌特征进行有效测量。因此,需要将硅深腔结构剖开后采用扫描电镜(SEM)进行检测。这种检测方式时间周期长，且属于破坏性的样本检测，效率和测试精度都较低。提出以硅半球深腔为模具，利用PDMS铸模将硅半球深腔的结构尺寸和表面形貌转移到PDMS凸起的半球模型上，通过检测PDMS半球模型的尺寸结构和表面形貌，即可反推出硅半球深腔的尺寸特征。经实验验证，脱模后的PDMS模型可以准确地反映出半球深腔的尺寸信息，测量结果的不确定度小于5‰，有效解决了硅半球深腔无损检测的难题。     

合理运用SI技术快速收敛高速数字电路设计

随着数字电路集成度和工作频率的不断提高,信号完整性(Signal Integrity, SI)问题在产品研制过程中越来越突出。以惯导系统中的某导航计算机为例,针对故障信号回路,使用仿真软件对其SDRAM时钟信号进行信号完整性仿真,并进行优化设计。通过对比优化前和优化后的仿真与测量结果,验证了由于端接参数不匹配造成SDRAM时钟信号的非单调性畸变问题。仿真与测量结果表明,在产品研制流程中加入信号完整性仿真环节有利于设计快速收敛,提前规避风险,缩短研发周期,降低设计成本,提高电路产品的可靠性和电磁兼容性。     

Bayesian network-based extraction of lunar impact craters from optical images and DEM data

Impact craters are among the most noticeable geomorphological features on the planetary surface and yield significant information about terrain evolution and the history of the solar system. Thus, the recognition of impact craters is an important branch of modern planetary studies. Aiming at addressing problems associated with the insufficient and inaccurate detection of lunar impact craters, a decision fusion method within the Bayesian network (BN) framework is developed in this paper to handle multi-source information from both optical images and associated digital elevation model (DEM) data. First, we implement the edge-based method for efficiently searching crater candidates which are the image patches that can potentially contain impact craters. Secondly, the multi-source representations of an impact crater derived from both optical images and DEM data are proposed and constructed to quantitatively describe the two-dimensional (2D) and three-dimensional (3D) morphology, consisting of Histogram of Oriented Gradient (HOG), Histogram of Multi-scale Slope (HMS) and Histogram of Multi-scale Aspect (HMA). Finally, a BN-based framework integrates the multi-source representations of impact craters, which can provide reductant and complementary information, for distinguishing craters from non-craters. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on three lunar scenes using both orthoimages from the Lunar Reconnaissance Orbiter (LRO) and DEM data acquired by the Lunar Orbiter Laser Altimeter (LOLA). Experimental results demonstrate that integrating optical images with DEM data significantly decreases the number of false positives compared with using optical images alone, with F₁-score of 84.8% on average. Moreover, compared with other existing fusion methods, our proposed method was quite advantageous especially for the detection of small-scale craters with diameters less than 1000 m.     

一种利用ILSP的同步DS-CDMA信号快速盲解扩算法

针对同步DS-CDMA信号的盲解扩问题，本文提出了一种基于迭代最小二乘投影算法(ILSP)的快速盲解扩算法。本算法首先通过对截获信号的协方差矩阵进行特征分解，估计出由各用户扩频序列张成的信号子空间，然后结合扩频码序列的有限符号集特性，利用ILSP算法消除由特征分解产生的酉矩阵模糊问题，得到扩频序列的精确估计，最后利用估计得到的扩频序列对截获信号解扩得到信息码序列，完成DS-CDMA信号的盲解扩。仿真结果表明本算法在低信噪比条件下具有良好的盲解扩性能，且相较传统算法本文提出算法大大降低了计算复杂度 。