在一个例子APART-GAS 2019试验中,被动和主动雷达传感器联合现场测试的准备和实现的挑战

M. Brzozowski, Mariusz Pakowski, Zbigniew Jakielaszek, M. Michalczewski, Mirosław Myszka
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引用次数: 1

摘要

针对陆海空各种平台无源传感器的实际功能验证,综述了与现场训练准备、组织和执行有关的若干问题。APART-GAS试验结合了在SET小组内运行的两个北约研究任务组(RTG)的训练:SET-242在移动平台上的无源无线电定位(移动平台上的无源相干定位器)和SET-258在各种军事场景中使用的多波段有源和无源雷达(DMPAR -可部署的多波段无源雷达部署和军事场景评估)。无源传感器的特殊性及其广泛的应用范围导致在开发和执行使用不同飞机类型(包括垂直发射火箭、水上船只和陆地车辆)进行的测试场景阶段出现了许多复杂情况。本文先后论述了空军工学院(AFIT)支持华沙理工大学的活动。在单个平台上安装传感器方面,试验过程中飞机的飞行规划和协调。AFIT完成了有关记录和成像无线电定位数据的问题,这些数据来自参与试验的传感器,并与非机密雷达网络(URN)耦合。
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Challenges of preparation and realization of combined field tests of passive and active radar sensors on an example APART-GAS 2019 trials
The article reviews selected issues associated with the preparation, organization and execution of field training targeting the practical functional verification of passive sensors installed on-board various land, sea and air platforms. The APART-GAS trials combined the training of two NATO research task groups (RTG) operating within the SET Panel: SET-242 on passive radiolocation on mobile platforms (Passive Coherent Locators on Mobile Platforms) and SET-258 on multiband active and passive radars used in various military scenarios (DMPAR - Deployable Multiband Passive Active Radar Deployment and Assessment in Military Scenarios). The specificity of passive sensors, as well as the wide range of their applications resulted in numerous complications at the stage of developing and executing test scenarios conducted with the use of different aircraft types, including vertical launch rockets, water vessels and land vehicles. The article discusses successively the activities supporting the Warsaw University of Technology implemented by the Air Force Institute of Technology (AFIT). in the field of installing the sensors on individual platform, aircraft flight planning and their coordination in the course of the trials. AFIT performed the issues regarding the recording and imaging radiolocation data from the sensors participating in the trials and coupled within an Unclassified Radar Network (URN).
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