Motivated by politics and economy, the monitoring of the world wide ship traffic is a field of high topicality. To detect illegal activities like piracy, illegal fishery, ocean dumping and refugee transportation is of great value. The analysis of satellite images on the ground delivers a great contribution to situation awareness. However, for many applications the up-to-dateness of the data is crucial. With ground based processing, the time between image acquisition and delivery of the data to the end user is in the range of several hours. The highest influence to the duration of ground based processing is the delay caused by the transmission of the large amount of image data from the satellite to the processing centre on the ground. One expensive solution to this issue is the usage of data relay satellites systems like EDRS. Another approach is to analyse the image data directly on-board of the satellite. Since the product data (e.g. ship position, heading, velocity, characteristics) is very small compared to the input image data, real-time connections provided by satellite telecommunication services like Iridium or Orbcomm can be used to send small packets of information directly to the end 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 a real-time low bandwidth communication. The operation of a prototype on-board ship detection system will be demonstrated on an airborne platform. In this article, the scope, aim and design of a flight experiment for an on-board ship detection system scheduled for mid of 2018 is presented. First, the scope and the constraints of the experiment are explained in detail. The main goal is to demonstrate the operability of an automatic ship detection system on board of an airplane. For data acquisition the optical high resolution DLR MACS-MARE camera (VIS/NIR) is used. The system will be able to send product data, like position, size and a small image of the ship directly to the user’s smart-phone by email. The time between the acquisition of the image data and the delivery of the product data to the end-user is aimed to be less than three minutes. For communication, the SMS-like Iridium Short Burst Data (SBD) Service was chosen, providing a message size of around 300 Bytes. Under optimal sending/receiving conditions, messages can be transmitted bidirectional every 20 seconds. Due to the very small data bandwidth, not all product data may be transmittable at once, for instance, when flying over busy ships traffic zones. Therefore the system offers two services: a query and a push service. With the query service the end user can explicitly request data of a defined location and fixed time period by posting queries in an SQL-like language. With the push service, events can be predefined and messages are received automatically, if and when the event occurs. Finally, the hardware set-up, details of the ship detection algorithms and the current status of the experiment is presented.
The detection of ships from remote sensing data has become an essential task for maritime security. The variety of application scenarios includes piracy, illegal fishery, ocean dumping and ships carrying refugees. While techniques using data from SAR sensors for ship detection are widely common, there is only few literature discussing algorithms based on imagery of optical camera systems. A ship detection algorithm for optical pushbroom data has been developed. It takes advantage of the special detector assembly of most of those scanners, which allows apart from the detection of a ship also the calculation of its heading out of a single acquisition. The proposed algorithm for the detection of moving ships was developed with RapidEye imagery. It algorithm consists mainly of three steps: the creation of a land-watermask, the object extraction and the deeper examination of each single object. The latter step is built up by several spectral and geometric filters, making heavy use of the inter-channel displacement typical for pushbroom sensors with multiple CCD lines, finally yielding a set of ships and their direction of movement. The working principle of time-shifted pushbroom sensors and the developed algorithm is explained in detail. Furthermore, we present our first results and give an outlook to future improvements.