基于EKF算法的弹道导弹助推段跟踪建模与仿真

围绕弹道导弹助推段跟踪问题,分析了助推段反弹道导弹的基本作战过程,建立了弹道导弹助推段动力学模型,分别就单传感器/单弹道导弹和多传感器/多弹道导弹两种情况建立了基于EKF算法的弹道导弹助推段跟踪模型,并通过算例验证了模型和算法的有效性,可为助推段反弹道导弹建模与仿真提供一定的参考。     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

Visual-attention gabor filter based online multi-armored target tracking

The multi-armored target tracking (MATT) plays a crucial role in coordinated tracking and strike. The occlusion and insertion among targets and target scale variation is the key problems in MATT. Most state-of-the-art multi-object tracking (MOT) works adopt the tracking-by-detection strategy, which rely on compute-intensive sliding window or anchoring scheme in detection module and neglect the target scale variation in tracking module. In this work, we proposed a more efficient and effective spatial-temporal attention scheme to track multi-armored target in the ground battlefield. By simulating the structure of the retina, a novel visual-attention Gabor filter branch is proposed to enhance detection. By introducing temporal information, some online learned target-specific Convolutional Neural Networks (CNNs) are adopted to address occlusion. More importantly, we built a MOT dataset for armored targets, called Armored Target Tracking dataset (ATTD), based on which several comparable experiments with state-of-the-art methods are conducted. Experimental results show that the proposed method achieves outstanding tracking performance and meets the actual application requirements.     

基于二进小波变换的噪声图像自适应增强新算法

针对图像增强算法通常会放大原图像中噪声分量的问题,提出了一种基于二进小波变换的图像增强新算法。该算法充分利用了二进小波变换的平移不变性和各尺度上小波系数间的相关性,有效改善了增强过程中噪声放大和边缘失真问题。此外,算法具有高度的自适应能力,适用性更强。实验结果表明,与目前已有的各类多尺度图像增强算法相比,该算法在抑制噪声和凸显图像特征两方面均有明显改进。     

态势生成中一种非线性运动模型的建立

探讨了在信息融合仿真试验床的态势生成部分,建立飞行实体运动模型的方法;通过保留运动学方程,简化动力学方程的方法,给出了一种常见的机动飞行方式(俯冲爬升类运动)的运动模型的计算公式;并对这种运动模型的非线性和机动性进行了分析和讨论;通过仿真,比较了几种机动目标跟踪算法对该运动模型的跟踪效果,验证了该方法的有效性。     

机载雷达系统测距算法

给出了机载雷达系统独立判定接近距离及接近速度的多回路跟踪测量器的状态模型和观测模型,并对这些模型进行了论证分析。基于最优控制的相关理论,重点分析研究了跟踪测量器的最优调节算法,并分析给出了该算法的权重系数选定原则和方法,最后通过仿真算例,推证了算法的可行性。利用上述算法可为研究机载雷达系统跟踪高度机动的目标问题提供参考。     

型号项目工期风险管理决策模型与自适应遗传算法

针对型号项目的过程特点,建立了型号项目工期风险的管理决策模型。模型考虑了型号项目中活动重叠、活动迭代、活动执行时间的不确定性和可更新资源总量等重要的工期风险影响因素。从模型的特点出发,给出了问题求解的基于自适应遗传算法的仿真优化方法。算例显示,该算法能较好地求解本文的工期风险管理决策问题。     

中继卫星调度问题的CSP模型

中继卫星在地球同步静止轨道上运行,既能直视中、低轨道用户航天器,又能直视地面站,是沟通用户航天器与地面站的桥梁。中继卫星调度问题是一类非常重要的调度问题。基于约束满足理论,通过分析中继卫星调度问题的特点与约束条件,建立了中继卫星调度问题的CSP模型。利用卫星工具箱STK进行模拟仿真,对CSP模型进行了求解。结果表明,所建立的CSP模型是合理的。     

基于反馈线性化及滑模控制的俯冲机动制导方法

以高超声速飞行器为研究对象,针对俯冲段精确制导及机动突防问题,基于反馈线性化与滑模控制研究了机动突防滑模跟踪制导方法。首先设计纵向俯冲及侧向机动弹道,其次利用反馈线性化将非线性运动方程转化为线性方程,基于该线性方程利用滑模控制对已设计的弹道进行跟踪,最终将线性跟踪制导律转换到非线性系统中获得非线性滑模跟踪制导律,该制导律完全基于飞行器当前运动状态,所需的相对运动信息大大减少。CAV-H飞行器制导实例仿真表明,该方法能够实现俯冲段精确制导及机动飞行,且对初始及过程偏差具有较强的鲁棒性,能够为高超声速飞行器俯冲段制导提供有益参考。     

基于期望系统噪声的自适应机动目标跟踪研究

状态估计是目标跟踪中的基本问题,也是目标跟踪的一个难点。首先对标准IMM算法的优缺点进行了论述,针对其缺点和不足,提出了基于期望系统噪声模型（MIMM）的自适应多模型算法,该算法能有效地对机动目标的状态进行自适应估计。仿真结果表明,该算法比标准的IMM算法有较好的改善。