Simon Batzdorfer

Aerial Tracking and GNSS-Reference Localization with a Robotic Total Station

Precise navigation for small unmanned aerial systems is of high interest for disaster scenarios and many other tasks. Advanced navigation technologies for future low-altitude applications in completely or partly unknown environments are carried out by DLRs Unmanned Aircraft Department in cooperation with the Institute of Flight Guidance from the Technical University Braunschweig. This paper describes the usage of a robotic total station as a reference localization system in order to benchmark current and developing satellite, inertial, and optical navigation techniques. Such devices perform laser-based distance measurements to the aircraft and track the moving vehicle. Since total stations are not mainly designed for aerial applications, the paper includes the description of some required extensions like faster automatic targeting and time synchronization. The paper concludes with the analysis of helicopter flight tests, where satellite-based localization results from different receivers are compared with the total station reference measurements.

A Flight State Estimator that Combines Stereo-Vision, INS, and Satellite Pseudo-Ranges

This paper presents a flight state estimator which couples stereo vision, inertial (INS), and global navigation satellite system (GNSS) data. The navigation filter comes with different operation modes that allow loosely coupled GNSS/INS positioning and, for difficult conditions, improvements using visual odometry and a tighter coupling with GNSS pseudo-range (PSR) data. While camera systems are typically used as an additional relative movement sensor to enable positioning without GNSS for a certain amount of time, the PSR data filtering allows to use satellite navigation also when less than four satellites are available. This makes the filter even more robust against temporary dropouts of the full GNSS solution. The application is the navigation of unmanned aircraft in disaster scenarios which includes flights close to ground in urban or mountainous areas. The filter performance is evaluated with sensor data from unmanned helicopter flight tests where different conditions of the GNSS signal reception are simulated. It is shown that the use of PSR data improves the positioning significantly compared to the dropout when the signals of less than four satellites are available.

The far-infrared space interferometer study IRASSI: motivation, principle design, and technical aspects

The far-infrared (FIR) regime is one of the few wavelength ranges where no astronomical data with sub-arcsecond spatial resolution exist yet. Also medium-term satellite projects like SPICA, Millimetron or OST will not resolve this malady. For many research areas, however, information at high spatial and spectral resolution in the FIR, taken from atomic fine-structure lines, from highly excited CO and especially from water lines would open the door for transformative science. These demands call for interferometric concepts. We present here first results of our feasibility study IRASSI (Infrared Astronomy Satellite Swarm Interferometry) for an FIR space interferometer. Extending on the principal concept of the previous study ESPRIT, it features heterodyne interferometry within a swarm of 5 satellite elements. The satellites can drift in and out within a range of several hundred meters, thereby achieving spatial resolutions of <0.1 arcsec over the whole wavelength range of 1–6 THz. Precise knowledge on the baselines will be ensured by metrology employing laser frequency combs, for which first ground-based tests have been designed by members of our study team. In this contribution, we first give a motivation how the science requirements translated into operational and design parameters for IRASSI. Our consortium has put much emphasis on the navigational aspects of such a free-flying swarm of satellites operating in relatively close vicinity. We hence present work on the formation geometry, the relative dynamics of the swarm, and aspects of our investigation towards attitude estimation. Furthermore, we discuss issues regarding the real-time capability of the autonomous relative positioning system, which is an important aspect for IRASSI where, due to the large raw data rates expected, the interferometric correlation has to be done onboard, quasi in real-time. We also address questions regarding the spacecraft architecture and how a first thermomechanical model is used to study the effect of thermal perturbations on the spacecraft. This will have implications for the necessary internal calibration of the local tie between the laser metrology and the phase centres of the science signals.

Mobile ad-hoc communication in machine swarms for relative positioning based on GNSS-raw data exchange

The increasing automation of mobile working machines and the progressive use of more than one machine up to machine swarms for cooperative tasks demands information about the relative position between the machines as well as between the machines and their attachments. This is especially necessary and important when carrying out tasks on distributed machines in a formation. Examples for application are parallel harvesting process in agricultural business or the cooperative search for survivors after a snow slide or e.g. an earthquake in urban scenarios. Moreover, it is very important to ensure relative position information in case of partial failure or a poor reception of the GNSS receiver, for example to avoid the collision between the machines. Options to handle this problem are the coupling of Global Navigation Satellite System (GNSS) measurements with measurements of an Inertial Measurement Unit (IMU). A further improvement or stabilization can be done by vision based systems, like 2D- or 3D-camera system using methods of optical flow for motion estimation. Another possibility for improvement for determining the swarm geometry, which will be described in this paper, is the so called swarm positioning method. This method is based on the exchange of the measured GNSS raw data, i.e. range measurements, between each participant in the swarm using a mobile ad-hoc network. Additionally, GNSS raw measurements and inertial measurements are coupled using multiple filters in order to detect degraded GNSS measurements and exclude these from further data processing. The challenge of the mobile ad-hoc network is the time variant network structure and the small available transmission rate in combination with a high demand for quick data exchange. The requirement to respond very flexibly to changes in topology and to compensate the loss of individual network participants as well as to spontaneously integrate further participants forbids the use of a fixed coordinator. Therefore different routing algorithms have to be combined and developed to ensure an information exchange in various scenarios.