ARTINO: A New High Resolution 3D Imaging Radar System on an Autonomous Airborne Platform

The new radar system ARTINO (Airborne Radar for Three-dimensional Imaging and Nadir Observation), developed at FGAN-FHR, allows to image a direct overflown scene in three dimensions. Integrated in a small, mobile, and dismountable UAV (Unmanned Aerial Vehicle) it will be an ideal tool for various applications. This paper gives an overview about the ARTINO principle, the raw data simulation, the image formation, the technical realisation, and the status of the experimental system. I. THE ARTINO PRINCIPLE ARTINO is a new radar system integrated in a small and dismountable low-wing UAV, which allows to image the direct overflown scene in three dimensions (Figure 1). Fig. 1. Artist impression of an imaging mission using ARTINO. This new system can image the direct overflown scene in three dimensions. General side-looking SAR systems are constraint by shading effects which can hide essential information in the explored scene. The downward-looking concept of ARTINO overcomes this restriction and enables imaging of street canyons and deep terrain in mountainous areas. Moreover, the 3D imaging capability together with the small and mobile platform is an ideal tool of close in time data acquisitions of fast changing terrains, like snow slopes (danger of avalanches) and active volcanoes. This new system could be used for various applications, like DEM (Digital Elevation Model) generation, surveying, city planing, environmental monitoring, disaster relief, surveillance, and reconnaissance. In contrary to similar concepts (e.g. [1]–[3]) the ARTINO principle works with a sparse antenna array distributed along the wings, with the transmitting elements at the tips and the receiving elements in between. Virtual antenna elements are formed by the mean positions of every couple of single transmit and receive elements. Finally, one gets a fully distributed virtual antenna array. The 3D resolution cells are formed by the appliance of the synthetic aperture and a beamforming operation. A detailed description of the ARTINO principle, the used UAV (Figure 2), and the simulation of raw data can be found in [4]. The image formation using the ARTINO principle is extensively discussed in [5]. A detailed description of the technical realization and its status is given in [6]. This paper gives an overview of the concept, the processing, some first simulation results, and the technical realisation. Fig. 2. Photo of the low wing UAV ARTINO. The new radar system will be integrated in the fuselage and the wings. II. MODEL OF THE ARTINO CONCEPT A. Geometrical consideration and signal model ARTINO is supposed to fly at the altitude h along the x-axis with the velocity v. The virtual antenna is composed of Nvirt elements, which are centered at the y-axis and regularly spaced along this axis. The position of the i-th virtual antenna element with i ∈ [−Nvirt−1 2 ; Nvirt−1 2 ] is given by ηi = (x, yi, h). The transpose operator is denoted by the superscript . T denotes the pulse-to-pulse time and t the fast time. The antenna position along the x-axis at time T is given by x = v·T . Figure 3 shows the geometry of the ARTINO principle. The distance d between the virtual antenna elements was determined by simulations in order to optimize the antenna beam (reduction of grating lobes) of the whole array (Figure 4). For the demonstration of the feasibility of this new radar concept, a pulse radar is assumed. To obtain a distinct assignment of each virtual antenna element, it will be necessary for the experimental system that the real antenna elements transmit with a time multiplex from pulse to pulse. In the simulation, all virtual antenna elements transmit simultaneously. A point scatterer P is positioned at ξ = (ξx, ξy, ξz) with the reflectivity α(ξ) (Figure 3). The signal assigned to the 0-7803-9510-7/06/$20.00 © 2006 IEEE 3825 Fig. 3. Geometry for the ARTINO principle −3 −2 −1 0 1 2 3 −40 −30 −20 −10 0