MACS-Mar: a real-time remote sensing system for maritime security applications

Brauchle, Jörg; Bayer, Steven; Hein, Daniel; Berger, Ralf; Pless, Sebastian

doi:10.1007/s12567-018-0207-7

Cited by 11 publications

(7 citation statements)

References 21 publications

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“…This was done by measuring projection errors of known ground control points (GCP) captured by aerial imagery from an altitude of 1300 m above sea level. The investigation provides an absolute spatial pixel accuracy of approximately 2 m (2σ) horizontally [39]. This level of projection accuracy with direct georeferencing can be considered sufficient for disaster assessment and management tasks.…”

Section: Resultsmentioning

confidence: 94%

Integrated UAV-Based Real-Time Mapping for Security Applications

Hein

Kraft

Brauchle

et al. 2019

IJGI

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Security applications such as management of natural disasters and man-made incidents crucially depend on the rapid availability of a situation picture of the affected area. UAV-based remote sensing systems may constitute an essential tool for capturing aerial imagery in such scenarios. While several commercial UAV solutions already provide acquisition of high quality photos or real-time video transmission via radio link, generating instant high-resolution aerial maps is still an open challenge. For this purpose, the article presents a real-time processing tool chain, enabling generation of interactive aerial maps during flight. Key element of this tool chain is the combination of the Terrain Aware Image Clipping (TAC) algorithm and 12-bit JPEG compression. As a result, the data size of a common scenery can be reduced to approximately 0.4% of the original size, while preserving full geometric and radiometric resolution. Particular attention was paid to minimize computational costs to reduce hardware requirements. The full workflow was demonstrated using the DLR Modular Airborne Camera System (MACS) operated on a conventional aircraft. In combination with a commercial radio link, the latency between image acquisition and visualization in the ground station was about 2 s. In addition, the integration of a miniaturized version of the camera system into a small fixed-wing UAV is presented. It is shown that the described workflow is efficient enough to instantly generate image maps even on small UAV hardware. Using a radio link, these maps can be broadcasted to on-site operation centers and are immediately available to the end-users.

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Section: Resultsmentioning

confidence: 94%

Integrated UAV-Based Real-Time Mapping for Security Applications

Hein

Kraft

Brauchle

et al. 2019

IJGI

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“…The nadir mounted camera systems we used so far were all equipped with high-grade 2 GNSS receiver and mid-grade 3 MEMS-based IMU sensors, resulting in a typical projection precision in the order of decimetres at flight levels of about 300...500 metres above ground, referred to consecutive images. The absolute positional accuracy of direct georeferencing with the aforementioned set-up has been evaluated in (Brauchle et al, 2018). It states a typical horizontal position error of less than 2 metres for the configuration with a standard utility aircraft and a flight altitude of 2, 600f t (approx.…”

Section: Resultsmentioning

confidence: 99%

Terrain Aware Image Clipping for Real-Time Aerial Mapping

Hein

Berger

2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Many remote sensing applications demand for a fast and efficient way of generating orthophoto maps from raw aerial images. One prerequisite is direct georeferencing, which allows to geolocate aerial images to their geographic position on the earth’s surface. But this is only half the story. When dealing with a large quantity of highly overlapping images, a major challenge is to select the most suitable image parts in order to generate seamless aerial maps of the captured area. This paper proposes a method that quickly determines such an optimal (rectangular) section for each single aerial image, which in turn can be used for generating seamless aerial maps. Its key approach is to clip aerial images depending on their geometric intersections with a terrain elevation model of the captured area, which is why we call it terrain aware image clipping (TAC). The method has a modest computational footprint and is therefore applicable even for rather limited embedded vision systems. It can be applied for both, real-time aerial mapping applications using data links as well as for rapid map generation right after landing without any postprocessing step. Referring to real-time applications, this method also minimizes transmission of redundant image data. The proposed method has already been demonstrated in several search-and-rescue scenarios and real-time mapping applications using a broadband data link and diffent kinds of camera and carrier systems. Moreover, a patent for this technology is pending.

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“…Images were acquired using the instrument MACS (Modular Aerial Camera System), cf. [36,37]. A picture of the MACS camera system can be found on figure 5.…”

Section: Macs and Image Datamentioning

confidence: 99%

AMARO—An On-Board Ship Detection and Real-Time Information System

Willburger

Schwenk

Brauchle

2020

Sensors

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The monitoring of worldwide ship traffic is a field of high topicality. Activities like piracy, ocean dumping, and refugee transportation are in the news every day. The detection of ships in remotely sensed data from airplanes, drones, or spacecraft contributes to maritime situational awareness. However, the crucial factor is the up-to-dateness of the extracted information. With ground-based processing, the time between image acquisition and delivery of the extracted product data is in the range of several hours, mainly due to the time consumed by storing and transmission of the large image data. By processing and analyzing them on-board and transmitting the product data directly as ship position, heading, and velocity, the delay can be shortened to some minutes. Real-time connections via satellite telecommunication services allow small packets of information to be sent directly to the user without significant delay. The AMARO (Autonomous Real-Time Detection of Moving Maritime Objects) project at DLR is a feasibility study of an on-board ship detection system involving on-board processing and real-time communication. The operation of a prototype system was successfully demonstrated on an airborne platform in spring 2018. The on-ground user could be informed about detected vessels within minutes after sighting without a direct communication link. In this article, the scope, aim, and design of the AMARO system are described, and the results of the flight experiment are presented in detail.Sensors 2020, 20, 1324 2 of 23 collision avoidance. Ships send out their identification, position, course, speed, and several other traffic-related data. This data is then received by other ships and ground stations in close range. Nowadays, to be able to track ships globally in real-time, satellites are also used to receive AIS data [7]. However, based on AIS data only, the detection of illegal activities like water pollution, illegal fishing, or smuggling is limited.To improve maritime domain awareness, Earth observation (EO) satellite data is a valuable source of information. Great efforts are made in researching the potential of vessel detection in optical and radar satellite images [8][9][10]. However, in most cases, these images are analyzed long after the data have been acquired [11]. To tackle this bottleneck, there is also promising progress in establishing near-real-time services on the ground, which today can provide information in, at best, the range of 15 min, measured from on-ground data reception [12,13]. However, the most significant time delay occurs between data acquisition on-board and data reception on-ground, since image data are comparatively huge and their downlink requires a direct contact to a ground station. This delay can amount to hours or even days [14].A second drawback of EO satellites for time-critical applications is their inability to continuously monitor a defined region of interest. Satellites with a reasonable spatial resolution for ship detection orbit in LEO (low Earth orbit) with speeds of a...

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MACS-Mar: a real-time remote sensing system for maritime security applications

Cited by 11 publications

References 21 publications

Integrated UAV-Based Real-Time Mapping for Security Applications

Integrated UAV-Based Real-Time Mapping for Security Applications

Terrain Aware Image Clipping for Real-Time Aerial Mapping

AMARO—An On-Board Ship Detection and Real-Time Information System

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