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Software-Controlled Active Electronically Scanned Array Radar for Airbone Ground Surveillance

Software-Controlled Active Electronically Scanned Array Radar for Airbone Ground Surveillance
用于机载地面监视的软件控制有源电子扫描阵列雷达
批准号:
500634-2016
负责人:
Kirubarajan, Thia
金额:
$5.97万
依托单位:
依托单位国家:
加拿大
项目类别:
Department of National Defence / NSERC Research Partnership
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
翻译
跟踪移动对象(如地面车辆、船舶、飞机、人员)的状态在通信、执法、国防和生物医学工程中有着广泛的应用。各种各样的传感器(例如,雷达、视频、声纳、红外)可以用来产生测量结果,这些传感器可以是固定的或安装在移动平台(例如,飞机、卫星、船舶、汽车)上,这些测量结果又用于估计移动物体的未知状态。随着传感器、计算机硬件和软件技术的最新发展,可以实时自适应地修改传感器的处理、操作方式和配置以响应不断变化的环境。例如,使用有源电子扫描阵列(AESA)雷达,可以实时自适应地改变波形、采样时间和传感模式。自适应的目标是提供快速响应能力或敏捷性,通过自适应,可以通过尽可能地减少环境的影响、建模中的不确定性和感知中的误差来获得最准确的目标检测、状态估计和分类结果(即,最大限度地利用现有传感器)。这正是提出这项工作的动机。在这个项目中,我们提出了一套特别适用于AESA雷达机载监视系统中的多传感器多目标跟踪的自适应算法。经过一些改变,相同的概念也可以用于智能公路系统(IHS)和海上船舶交通管理服务(VTMS)系统。
英文摘要
Tracking the states of mobile objects (e.g., ground vehicles, ships, aircraft, people) has many applications in communications, law enforcement, defense and biomedical engineering. A wide variety of sensors (e.g., radar, video, sonar, infrared), which may be stationary or mounted on mobile platforms (e.g., aircraft, satellites, ships, cars), are available to generate measurements that are in turn used to estimate the unknown states of mobile objects. With the recent advances in sensor, computer hardware and software technologies, it is possible to adaptively modify the processing, operational modality and configuration of sensors in real time in response to the ever-changing environment. For example, with an active electronically scanned array (AESA) radar, one can adaptively change waveforms, sampling time and sensing mode in real time. The objective of adaptation is to provide rapid response capability or agility.With adaptation, it is possible to obtain the most accurate object detection, state estimation and classification results (i.e., get the best out of the available sensors) by mitigating as much as possible the effects of the environment, uncertainties in modeling and inaccuracies in sensing. This is precisely the motivation for the proposed work. In this project, we propose to develop a set of adaptive algorithms with particular application to multisenor-multitarget tracking in airborne surveillance systems with an AESA radar. With some changes, the same concepts can be used in intelligent highway systems (IHS) and maritime vessel traffic management service (VTMS) systems as well.
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Robust State Estimation in Uncertain Environments Using Point Process Models
  • 批准号:
    RGPIN-2017-05365
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.23万
  • 财政年份:
    2021
  • 负责人:
    Kirubarajan, Thia
  • 依托单位:
Airborne Tracking of Small Ground and Maritime Targets Under Realistic Conditions
  • 批准号:
    535810-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $26.23万
  • 财政年份:
    2021
  • 负责人:
    Kirubarajan, Thia
  • 依托单位:
Optimal Layered Resource Management and Data Processing for Threat Detection in Urban Environments
  • 批准号:
    538404-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $6.99万
  • 财政年份:
    2021
  • 负责人:
    Kirubarajan, Thia
  • 依托单位:
Multi-level adaptive systems and algorithms for agile and opportunistic sensing
  • 批准号:
    501206-2016
  • 项目类别:
    Department of National Defence / NSERC Research Partnership
  • 资助金额:
    $7.29万
  • 财政年份:
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  • 负责人:
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  • 依托单位:
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