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首页> 外文会议>Conference on unattended ground, sea and air sensor technologies and applications XI; 20090413-16; Orlando, FL(US) >General framework for predicting environmental effects on signatures and sensor performance in complex environments
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General framework for predicting environmental effects on signatures and sensor performance in complex environments

机译：在复杂环境中预测环境对特征和传感器性能的影响的通用框架

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摘要

The performance and utility of battlefield and homeland security sensors depends on many complicated environmental and mission-related factors. This paper describes a general software design for predicting performance of such sensors. It is intended for application to a wide range of sensing modalities and based on an object-oriented framework that can be incorporated into Army command and control (C2) systems, decision support tools (DSTs), and force-on-force simulations. The approach breaks down sensor performance prediction into the following steps: (1) information gathering and construction of the tactical and environmental scenario, (2) translation of the scenario information, (3) target and noise signature prediction models, (4) prediction of sensor performance metrics, and (5) display of and interaction with the information. The main components for Steps 3 and 4 involve operations on signature features, which are described statistically by signal-model objects. These are the units of information needed by the sensor platforms for producing inferences such as the presence or location of a target. The features are generated by emitter platforms, propagated through the environment by feature transmitters (which use scenario translators, Step 2, to convert the atmospheric and terrain descriptions to the necessary model parameters), and then processed by the sensor platforms. To avoid generation and transmission of unneeded data, the architecture is based on a data "pull" (request) from the sensor platforms rather than the more commonly used approach in DSTs of data "push" from the emitter platforms.
机译：战场和国土安全传感器的性能和实用性取决于许多复杂的环境和与任务相关的因素。本文介绍了用于预测此类传感器性能的通用软件设计。它旨在应用于广泛的传感模式，并且基于面向对象的框架，该框架可以并入陆军指挥与控制（C2）系统，决策支持工具（DST）和部队对部队的模拟。该方法将传感器性能预测分为以下步骤：（1）信息收集以及战术和环境情景的构建，（2）情景信息的转换，（3）目标和噪声特征预测模型，（4）预测传感器性能指标，以及（5）信息的显示和交互。步骤3和4的主要组件涉及对签名功能的操作，这些功能由信号模型对象进行统计描述。这些是传感器平台用于生成推断（例如目标的存在或位置）所需的信息单位。这些特征由发射器平台生成，然后由特征发射器（使用场景转换器，第2步，将大气和地形描述转换为必要的模型参数）在环境中传播，然后由传感器平台进行处理。为了避免产生和传输不需要的数据，该体系结构基于来自传感器平台的数据“拉”（请求），而不是来自发射器平台的数据“推”的DST中更常用的方法。

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