Earth observation from space – The issue of environmental sustainability

Remote sensing scientists work under assumptions that should not be taken for granted and should, therefore, be challenged. These assumptions include the following:1. Space, especially Low Earth Orbit (LEO), will always be available to governmental and commercial space entities that launch Earth remote sensing missions.2. Space launches are benign with respect to environmental impacts.3. Minimization of Type 1 error, which provides increased confidence in the experimental outcome, is the best way to assess the significance of environmental change.4. Large-area remote sensing investigations, i.e. national, continental, global studies, are best done from space.5. National space missions should trump international, cooperative space missions to ensure national control and distribution of the data products.At best, all of these points are arguable, and in some cases, they're wrong. Development of observational space systems that are compatible with sustainability principles should be a primary concern when Earth remote sensing space systems are envisioned, designed, and launched. The discussion is based on the hypothesis that reducing the environmental impacts of the data acquisition step, which is at the very beginning of the information stream leading to decision and action, will enhance coherence in the information stream and strengthen the capacity of measurement processes to meet their stated functional goal, i.e. sustainable management of Earth resources. We suggest that unconventional points of view should be adopted and when appropriate, remedial measures considered that could help to reduce the environmental footprint of space remote sensing and of Earth observation and monitoring systems in general. This article discusses these five assumptions in the context of sustainable management of Earth's resources. Taking each assumption in turn, we find the following:(1) Space debris may limit access to Low Earth Orbit over the next decades.(2) Relatively speaking, given that they're rare event, space launches may be benign, but study is merited on upper stratospheric and exospheric layers given the chemical activity associated with rocket combustion by-products.(3) Minimization of Type II error should be considered in situations where minimization of Type I error greatly hampers or precludes our ability to correct the environmental condition being studied.(4) In certain situations, airborne collects may be less expensive and more environmentally benign, and comparative studies should be done to determine which path is wisest.(5) International cooperation and data sharing will reduce instrument and launch costs and mission redundancy. Given fiscal concerns of most of the major space agencies – e.g. NASA, ESA, CNES – it seems prudent to combine resources.     

拦截高速目标的比例与反比例导引捕获区分析

针对拦截高速目标的作战特点,分析了比例导引(PN)与反比例导引(RPN)的捕获区。首先,通过分析拦截弹与目标的相对运动关系,推导得到了顺轨和逆轨的零控拦截条件,此条件由目标和拦截弹的速度前置角以及二者速度比确定;其次,以拦截弹和目标速度前置角为坐标系,推导得到了PN以及RPN捕获区以及各自导航比设置范围。PN的捕获区由逆轨零控拦截条件以及与其相切且斜率为1/(N-1)的两条直线构成,RPN的捕获区由顺轨零控拦截条件以及与其相切且斜率为1/(-N-1)的两条直线构成;然后,利用函数对称性将PN与RPN捕获区转换到同一坐标区间,得到了相同条件下RPN捕获区要大于PN捕获区的结论;最后,开展了四种情形下的仿真,验证了本文捕获区分析的合理性及有效性。     

点目标假设下的二维精度体系研究

点目标假设下,在二维圆概率偏差线性公式的基础上,给出了基于纵横向均方根误差分段的精确公式。同时应用概率论正态分布理论,对二维情况下均方根误差、圆概率偏差和概率偏差的相互关系进行了研究,通过理论推导和数值计算给出了二维精度指标相互转换的拟合公式,完善了满足工程应用的二维精度体系。研究结果可在精度指标的论证、设计和考核中使用。     

基于类脑模型与深度神经网络的目标检测与跟踪技术研究

目标检测与跟踪技术广泛应用于交通、医疗、安保和航天等领域.目前,目标检测与跟踪技术面临目标微弱、背景复杂、目标被遮挡等挑战.同时,随着脑科学研究的不断深入,人们对人脑视觉系统的理解逐渐透彻,利用类脑计算解决复杂背景下高精度目标检测与跟踪问题成为相关领域的重要研究方向.本文结合神经工程导向的类脑模型和计算机工程导向的深度神经网络(Deep Neural Networks, DNNs),提出多种基于类脑模型与深度神经网络的目标检测与跟踪算法,包括：基于演算侧抑制的目标检测算法,基于结构 对比度(Structure Contrast, SC)视觉注意模型的弱小目标检测算法和基于记忆机制与分层卷积特征的目标跟踪算法.实验结果表明,将类脑模型和深度神经网络应用于目标检测和跟踪领域,有利于实现复杂条件下的高精度目标检测和鲁棒性目标跟踪.     

星载多频段双极化共馈微波辐射计天线

作为“神州四号飞船”留轨段主载荷的多模态微波遥感系统中的微波辐射计天线是我国第一个工作到毫米波段的航天器天线，其工作频段跨越近6个倍频程，采用了多频、双极化共馈源偏置抛物反射面天线系统，首次应用就获成功。本文着重阐述该微波辐射计天线的多频、双极化共馈系统设计和毫米波高精度反射面天线的实现。文中还介绍了空间反射面天线的计算机机电热一体化设计。     

基于Murty方法的多目标跟踪快速算法

JPDA是一种有效的多目标跟踪算法，但算法的复杂度随着目标和观测值的增加而显著增长。为了减少JPDA算法所需要的存贮空间和计算时间，通过Murty方法，得到K个最优的目标与观测值对应关系，再利用这K个最优对应关系实现JPDA算法。仿真结果表明，新算法跟踪成功率与JPDA相近，所需的时间远低于JPDA算法。     

基于频域DPCA的星载SAR动目标检测、测速与定位

给出基于频域DPCA的星载合成孔径雷达 (SAR)动目标检测、测速及定位的实现方法。首先建立星载SAR沿航迹向三孔径天线空间几何模型 ,并详细分析星载SAR三孔径天线机理及信号特性 ,然后分析并推导基于频域DPCA实现对地面背景杂波淹没的运动目标检测、径向速度分量估计以及目标定位的方法。最后 ,计算机仿真结果验证其有效性     

海洋目标探测卫星的通用效能模型初探

为有效构建海洋目标探测卫星体系，建立一套能对各类卫星的海洋目标探测效果进行分析与评估的通用效能模型非常重要。初步建立了以目标探测概率为度量的海洋目标探测卫星通用效能模型，可用于光学成像、雷达成像和电子侦察卫星等。模型考虑了影响目标探测概率的三类主要因素即观测区域与目标特性、卫星平台参数和卫星有效载荷特性，分析了卫星技术性能指标和作战性能指标的相互关系，可作为海洋目标探测卫星体系需求分析、顶层设计以及效能评估的依据。并以大型舰船为探测目标用仿真结果说明了模型的适用性。     

雷达／红外综合探测系统抗干扰能力的建模

选择目标探测概率这一性能参数衡量雷达/红外综合探测系统的抗干扰能力,建立了压制式干扰情况下该综合探测系统的目标探测能力的数学模型,并通过计算机仿真验证了该模型的适用性。     

反导系统中的目标识别技术及其发展趋势

指出了反导系统目标识别的难点和特点。回顾了反导系统中的红外识别技术和雷达识别技术,并探讨了反导系统目标识别技术的发展趋势。