3D Photogrammetry from HAPS for HADR and Jettison Protection Systems for HAPS Payloads

QinetiQ正在开发一种新的主动光学遥感技术，软件定义多功能激光雷达(SDML)，旨在在单个组件中提供多种传感、成像和通信能力。这项针对高空智能跨部门创新挑战的建议旨在通过评估通过摄影测量生成大范围、高分辨率和照片级逼真的3D模型的潜力，进一步扩展SDML的能力。Raven Space Systems(RSS)将通过一份关于系统硬件和部署方案的论文研究，将这些项目联系起来，并进一步扩大产品范围。由于SDML提供多种操作模式，将需要额外的飞行测试，所有这些都是单一硬件故障点。此次发行将研究在HAPS平台发生故障时SDML硬件的风险缓解措施，并投资扩建平流层气球进行测试。摄影测量学是一项成熟的图像处理技术，它将从不同角度拍摄的大量同一区域的照片组合在一起，重建建筑物、自然对象和地形的3D模型。我们的合作伙伴组织伍斯特大学拥有从该技术生成多种数据产品的丰富经验，最常见的是从小型无人驾驶飞行器(UAV)生成数据，而从HAPS平台生成的数据在该领域提供了独特的机会。HAPS在关键任务区域的持续性提供了在许多平方公里范围内收集数百--甚至数千--这样的高分辨率图像的机会。SDML的FSOC模式将在相对较短的时间内将数千兆字节的图像数据快速传输到入射区域附近的地面终端。然后可以对这些数据进行处理，以便为民事和国防人道主义援助和救灾方案提供时间紧迫和可采取行动的信息，使支助人员能够迅速和有效地采取行动。例如，高分辨率的3D地形模型可以及时分析洪水水位、滑坡体积以及建筑物和基础设施的破坏情况。该项目将使用SDML硬件(硬件在环模拟)来光学模拟从平流层高度捕获地面图像。这些图像将被传递给伍斯特大学进行分析和生成3D模型，这些模型将用于评估SDML硬件和HAPS平台在多个用例中的技术可行性。

QinetiQ is developing a new active optical remote sensing technology, Software Defined Multifunction Lidar (SDML), designed to provide multiple sensing, imaging and communications capabilities within a single package.This proposal into the High Altitude Intelligence Cross-Sector Innovation Challenge is designed to expand the SDML capability further by evaluating the potential to generate wide-area, high resolution and photo-realistic 3D models via photogrammetry. Linking the projects and to expand the offering further, work by Raven Space Systems (RSS) will investigate payload recovery options through a paper study on the system hardware and deployment scenarios. With SDML providing multiple operating modes, additional flight testing would be required, all with a single hardware point of failure. This offering will investigate risk mitigations for the SDML hardware in the event of HAPS platform failure and also investing expansion for testing on stratospheric balloons.Photogrammetry is a mature image processing technique wherein a large numbers of photos, taken of the same area from different view-points are combined to reconstruct a 3D model of buildings, natural objects and terrain. Our partner organisation, University of Worcester, have extensive experience generating multiple data products from this technique, most commonly from small uncrewed aerial vehicles (UAVs), however data generated from a HAPS platform provides a unique opportunity in this space. The persistence of HAPS over mission critical areas provides the opportunity to collect hundreds -- maybe thousands -- of such high resolution images over many square kilometres. SDML's FSOC mode would enable the fast transfer of the multiple gigabytes of image data in a relatively short period of time to a ground terminal near the incident area. This data can then be processed to provide time-critical and actionable information for both civil and defence Humanitarian Assistance and Disaster Relief (HADR) scenarios, enabling support personnel to act quickly and effectively. As an example of this, high resolution 3D terrain models could enable timely analysis of flood water levels, land-slide volume and building and infrastructure damage.The project will optically simulate capture of ground images from stratospheric altitudes using SDML hardware (hardware in the loop simulation). These images will be passed to University of Worcester for analysis and generation of 3D models that will be used to assess the viability of the technique from the SDML hardware and from the HAPS platform for multiple use cases.